I think I will just load an existing expressionset generated from openswath.
osw_matrix <- new.env()
loaded <- load("protein_expt-v20181112.rda", envir=osw_matrix)
osw_matrix <- osw_matrix[["expt"]]
osw_counts <- exprs(osw_matrix)
colnames(osw_counts)
## [1] "s2018_0817BrikenTrypsinDIA01" "s2018_0817BrikenTrypsinDIA02"
## [3] "s2018_0817BrikenTrypsinDIA03" "s2018_0817BrikenTrypsinDIA11"
## [5] "s2018_0817BrikenTrypsinDIA12" "s2018_0817BrikenTrypsinDIA13"
## [7] "s2018_0817BrikenTrypsinDIA07" "s2018_0817BrikenTrypsinDIA08"
## [9] "s2018_0817BrikenTrypsinDIA09" "s2018_0817BrikenTrypsinDIA17"
## [11] "s2018_0817BrikenTrypsinDIA18" "s2018_0817BrikenTrypsinDIA19"
enc_metadata <- hpgltools:::read_metadata("sample_sheets/Mtb_dia_samples_encyclopedia_20190327.xlsx")
rownames(enc_metadata) <- paste0("s", enc_metadata[["sampleid"]])
enc_matrix <- read.table("encyclopedia/most_samples_quant_report.elib.proteins.txt", header=TRUE)
enc_pep_matrix <- read.table("encyclopedia/most_samples_quant_report.elib.proteins.txt", header=TRUE)
rownames(enc_matrix) <- enc_matrix[["Protein"]]
enc_matrix <- enc_matrix[, -1]
enc_matrix <- enc_matrix[, -1]
enc_matrix <- enc_matrix[, -1]
colnames(enc_matrix)
## [1] "X2018_0502BrikenDIA01.mzML"
## [2] "X2018_0502BrikenDIA02.mzML"
## [3] "X2018_0502BrikenDIA03.mzML"
## [4] "X2018_0502BrikenDIA04.mzML"
## [5] "X2018_0502BrikenDIA05.mzML"
## [6] "X2018_0502BrikenDIA06.mzML"
## [7] "X2018_0502BrikenDIA07.mzML"
## [8] "X2018_0502BrikenDIA08.mzML"
## [9] "X2018_0502BrikenDIA09.mzML"
## [10] "X2018_0502BrikenDIA10.mzML"
## [11] "X2018_0502BrikenDIA11.mzML"
## [12] "X2018_0502BrikenDIA12.mzML"
## [13] "X2018_0726Briken01.mzML"
## [14] "X2018_0726Briken02.mzML"
## [15] "X2018_0726Briken03.mzML"
## [16] "X2018_0726Briken04.mzML"
## [17] "X2018_0726Briken05.mzML"
## [18] "X2018_0726Briken06.mzML"
## [19] "X2018_0726Briken07.mzML"
## [20] "X2018_0726Briken08.mzML"
## [21] "X2018_0726Briken09.mzML"
## [22] "X2018_0726Briken11.mzML"
## [23] "X2018_0726Briken12.mzML"
## [24] "X2018_0726Briken13.mzML"
## [25] "X2018_0726Briken14.mzML"
## [26] "X2018_0726Briken15.mzML"
## [27] "X2018_0726Briken16.mzML"
## [28] "X2018_0726Briken17.mzML"
## [29] "X2018_0726Briken18.mzML"
## [30] "X2018_0726Briken19.mzML"
## [31] "X2018_0817BrikenTrypsinDIA01.mzML"
## [32] "X2018_0817BrikenTrypsinDIA02.mzML"
## [33] "X2018_0817BrikenTrypsinDIA03.mzML"
## [34] "X2018_0817BrikenTrypsinDIA04.mzML"
## [35] "X2018_0817BrikenTrypsinDIA05.mzML"
## [36] "X2018_0817BrikenTrypsinDIA06.mzML"
## [37] "X2018_0817BrikenTrypsinDIA07.mzML"
## [38] "X2018_0817BrikenTrypsinDIA08.mzML"
## [39] "X2018_0817BrikenTrypsinDIA09.mzML"
## [40] "X2018_0817BrikenTrypsinDIA11.mzML"
## [41] "X2018_0817BrikenTrypsinDIA12.mzML"
## [42] "X2018_0817BrikenTrypsinDIA13.mzML"
## [43] "X2018_0817BrikenTrypsinDIA14.mzML"
## [44] "X2018_0817BrikenTrypsinDIA15.mzML"
## [45] "X2018_0817BrikenTrypsinDIA16.mzML"
## [46] "X2018_0817BrikenTrypsinDIA17.mzML"
## [47] "X2018_0817BrikenTrypsinDIA18.mzML"
## [48] "X2018_0817BrikenTrypsinDIA19.mzML"
colnames(enc_matrix) <- gsub(pattern="X", replacement="s", x=colnames(enc_matrix))
colnames(enc_matrix) <- gsub(pattern="\\.mzML", replacement="", x=colnames(enc_matrix))
colnames(enc_matrix) <- gsub(pattern="^X", replacement="s", x=colnames(enc_matrix))
colnames(enc_matrix)
## [1] "s2018_0502BrikenDIA01" "s2018_0502BrikenDIA02"
## [3] "s2018_0502BrikenDIA03" "s2018_0502BrikenDIA04"
## [5] "s2018_0502BrikenDIA05" "s2018_0502BrikenDIA06"
## [7] "s2018_0502BrikenDIA07" "s2018_0502BrikenDIA08"
## [9] "s2018_0502BrikenDIA09" "s2018_0502BrikenDIA10"
## [11] "s2018_0502BrikenDIA11" "s2018_0502BrikenDIA12"
## [13] "s2018_0726Briken01" "s2018_0726Briken02"
## [15] "s2018_0726Briken03" "s2018_0726Briken04"
## [17] "s2018_0726Briken05" "s2018_0726Briken06"
## [19] "s2018_0726Briken07" "s2018_0726Briken08"
## [21] "s2018_0726Briken09" "s2018_0726Briken11"
## [23] "s2018_0726Briken12" "s2018_0726Briken13"
## [25] "s2018_0726Briken14" "s2018_0726Briken15"
## [27] "s2018_0726Briken16" "s2018_0726Briken17"
## [29] "s2018_0726Briken18" "s2018_0726Briken19"
## [31] "s2018_0817BrikenTrypsinDIA01" "s2018_0817BrikenTrypsinDIA02"
## [33] "s2018_0817BrikenTrypsinDIA03" "s2018_0817BrikenTrypsinDIA04"
## [35] "s2018_0817BrikenTrypsinDIA05" "s2018_0817BrikenTrypsinDIA06"
## [37] "s2018_0817BrikenTrypsinDIA07" "s2018_0817BrikenTrypsinDIA08"
## [39] "s2018_0817BrikenTrypsinDIA09" "s2018_0817BrikenTrypsinDIA11"
## [41] "s2018_0817BrikenTrypsinDIA12" "s2018_0817BrikenTrypsinDIA13"
## [43] "s2018_0817BrikenTrypsinDIA14" "s2018_0817BrikenTrypsinDIA15"
## [45] "s2018_0817BrikenTrypsinDIA16" "s2018_0817BrikenTrypsinDIA17"
## [47] "s2018_0817BrikenTrypsinDIA18" "s2018_0817BrikenTrypsinDIA19"
## [1] "s2018_0502BrikenDIA01" "s2018_0502BrikenDIA02"
## [3] "s2018_0502BrikenDIA03" "s2018_0502BrikenDIA04"
## [5] "s2018_0502BrikenDIA05" "s2018_0502BrikenDIA06"
## [7] "s2018_0502BrikenDIA07" "s2018_0502BrikenDIA08"
## [9] "s2018_0502BrikenDIA09" "s2018_0502BrikenDIA10"
## [11] "s2018_0502BrikenDIA11" "s2018_0502BrikenDIA12"
## [13] "s2018_0726Briken01" "s2018_0726Briken02"
## [15] "s2018_0726Briken03" "s2018_0726Briken04"
## [17] "s2018_0726Briken05" "s2018_0726Briken06"
## [19] "s2018_0726Briken07" "s2018_0726Briken08"
## [21] "s2018_0726Briken09" "s2018_0726Briken11"
## [23] "s2018_0726Briken12" "s2018_0726Briken13"
## [25] "s2018_0726Briken14" "s2018_0726Briken15"
## [27] "s2018_0726Briken16" "s2018_0726Briken17"
## [29] "s2018_0726Briken18" "s2018_0726Briken19"
## [31] "s2018_0817BrikenTrypsinDIA01" "s2018_0817BrikenTrypsinDIA02"
## [33] "s2018_0817BrikenTrypsinDIA03" "s2018_0817BrikenTrypsinDIA04"
## [35] "s2018_0817BrikenTrypsinDIA05" "s2018_0817BrikenTrypsinDIA06"
## [37] "s2018_0817BrikenTrypsinDIA07" "s2018_0817BrikenTrypsinDIA08"
## [39] "s2018_0817BrikenTrypsinDIA09" "s2018_0817BrikenTrypsinDIA11"
## [41] "s2018_0817BrikenTrypsinDIA12" "s2018_0817BrikenTrypsinDIA13"
## [43] "s2018_0817BrikenTrypsinDIA14" "s2018_0817BrikenTrypsinDIA15"
## [45] "s2018_0817BrikenTrypsinDIA16" "s2018_0817BrikenTrypsinDIA17"
## [47] "s2018_0817BrikenTrypsinDIA18" "s2018_0817BrikenTrypsinDIA19"
na_idx <- is.na(enc_matrix)
enc_matrix[na_idx] <- 0
enc_expt <- create_expt(metadata=enc_metadata, count_dataframe=enc_matrix, gene_info=NULL)
## Reading the sample metadata.
## The sample definitions comprises: 48 rows(samples) and 28 columns(metadata fields).
## Matched 2632 annotations and counts.
## Bringing together the count matrix and gene information.
## The final expressionset has 2632 rows and 48 columns.
Ok so that was 100% weird. Let us next NA all the entries which are currently 0.
I think that somewhere along the way some set of samples got mis-ordered?
enc_test <- normalize_expt(enc_expt, transform="log2", convert="cpm",
norm="quant", filter="pofa", p=0.99, A=1000)
## This function will replace the expt$expressionset slot with:
## log2(cpm(quant(pofa(data))))
## It will save copies of each step along the way
## in expt$normalized with the corresponding libsizes. Keep libsizes in mind
## when invoking limma. The appropriate libsize is non-log(cpm(normalized)).
## This is most likely kept at:
## 'new_expt$normalized$intermediate_counts$normalization$libsizes'
## A copy of this may also be found at:
## new_expt$best_libsize
## Not correcting the count-data for batch effects. If batch is
## included in EdgerR/limma's model, then this is probably wise; but in extreme
## batch effects this is a good parameter to play with.
## Step 1: performing count filter with option: pofa
## Removing 2551 low-count genes (81 remaining).
## Removing 0 low-count genes (2632 remaining).
## Step 2: normalizing the data with quant.
## Using normalize.quantiles.robust due to a thread error in preprocessCore.
## Step 3: converting the data with cpm.
## Step 4: transforming the data with log2.
## transform_counts: Found 2353 values equal to 0, adding 1 to the matrix.
## Step 5: not doing batch correction.
## Warning in MASS::cov.trob(data[, vars]): Probable convergence failure
## Warning in MASS::cov.trob(data[, vars]): Probable convergence failure
## Warning in MASS::cov.trob(data[, vars]): Probable convergence failure
## Warning in MASS::cov.trob(data[, vars]): Probable convergence failure
## The original expressionset has 48 samples.
## The final expressionset has 18 samples.
combined_test <- normalize_expt(enc_combined, transform="log2", convert="cpm",
norm="quant", filter="pofa", p=0.99, A=10000)
## This function will replace the expt$expressionset slot with:
## log2(cpm(quant(pofa(data))))
## It will save copies of each step along the way
## in expt$normalized with the corresponding libsizes. Keep libsizes in mind
## when invoking limma. The appropriate libsize is non-log(cpm(normalized)).
## This is most likely kept at:
## 'new_expt$normalized$intermediate_counts$normalization$libsizes'
## A copy of this may also be found at:
## new_expt$best_libsize
## Not correcting the count-data for batch effects. If batch is
## included in EdgerR/limma's model, then this is probably wise; but in extreme
## batch effects this is a good parameter to play with.
## Step 1: performing count filter with option: pofa
## Removing 1555 low-count genes (1077 remaining).
## Removing 0 low-count genes (2632 remaining).
## Step 2: normalizing the data with quant.
## Using normalize.quantiles.robust due to a thread error in preprocessCore.
## Step 3: converting the data with cpm.
## Step 4: transforming the data with log2.
## transform_counts: Found 692 values equal to 0, adding 1 to the matrix.
## Step 5: not doing batch correction.
## This data will benefit from being displayed on the log scale.
## If this is not desired, set scale='raw'
## Some entries are 0. We are on log scale, setting them to 0.5.
## Changed 9744 zero count features.
## There were 18, now there are 9 samples.
## This function will replace the expt$expressionset slot with:
## pofa(data)
## It will save copies of each step along the way
## in expt$normalized with the corresponding libsizes. Keep libsizes in mind
## when invoking limma. The appropriate libsize is non-log(cpm(normalized)).
## This is most likely kept at:
## 'new_expt$normalized$intermediate_counts$normalization$libsizes'
## A copy of this may also be found at:
## new_expt$best_libsize
## Leaving the data in its current base format, keep in mind that
## some metrics are easier to see when the data is log2 transformed, but
## EdgeR/DESeq do not accept transformed data.
## Leaving the data unconverted. It is often advisable to cpm/rpkm
## the data to normalize for sampling differences, keep in mind though that rpkm
## has some annoying biases, and voom() by default does a cpm (though hpgl_voom()
## will try to detect this).
## Leaving the data unnormalized. This is necessary for DESeq, but
## EdgeR/limma might benefit from normalization. Good choices include quantile,
## size-factor, tmm, etc.
## Not correcting the count-data for batch effects. If batch is
## included in EdgerR/limma's model, then this is probably wise; but in extreme
## batch effects this is a good parameter to play with.
## Step 1: performing count filter with option: pofa
## Removing 352 low-count genes (2280 remaining).
## Removing 21 low-count genes (2611 remaining).
## Step 2: not normalizing the data.
## Step 3: not converting the data.
## Step 4: not transforming the data.
## Step 5: not doing batch correction.
## There were 18, now there are 9 samples.
## This function will replace the expt$expressionset slot with:
## pofa(data)
## It will save copies of each step along the way
## in expt$normalized with the corresponding libsizes. Keep libsizes in mind
## when invoking limma. The appropriate libsize is non-log(cpm(normalized)).
## This is most likely kept at:
## 'new_expt$normalized$intermediate_counts$normalization$libsizes'
## A copy of this may also be found at:
## new_expt$best_libsize
## Leaving the data in its current base format, keep in mind that
## some metrics are easier to see when the data is log2 transformed, but
## EdgeR/DESeq do not accept transformed data.
## Leaving the data unconverted. It is often advisable to cpm/rpkm
## the data to normalize for sampling differences, keep in mind though that rpkm
## has some annoying biases, and voom() by default does a cpm (though hpgl_voom()
## will try to detect this).
## Leaving the data unnormalized. This is necessary for DESeq, but
## EdgeR/limma might benefit from normalization. Good choices include quantile,
## size-factor, tmm, etc.
## Not correcting the count-data for batch effects. If batch is
## included in EdgerR/limma's model, then this is probably wise; but in extreme
## batch effects this is a good parameter to play with.
## Step 1: performing count filter with option: pofa
## Removing 1524 low-count genes (1108 remaining).
## Removing 71 low-count genes (2561 remaining).
## Step 2: not normalizing the data.
## Step 3: not converting the data.
## Step 4: not transforming the data.
## Step 5: not doing batch correction.
keeper <- list("delta_wt" = c("delta_filtrate","wt_filtrate"))
enc_whole_de <- all_pairwise(enc_whole, parallel=FALSE,
force=TRUE, do_ebseq=TRUE, model_batch=FALSE)
## This function will replace the expt$expressionset slot with:
## log2(cpm(quant(cbcb(data))))
## It will save copies of each step along the way
## in expt$normalized with the corresponding libsizes. Keep libsizes in mind
## when invoking limma. The appropriate libsize is non-log(cpm(normalized)).
## This is most likely kept at:
## 'new_expt$normalized$intermediate_counts$normalization$libsizes'
## A copy of this may also be found at:
## new_expt$best_libsize
## Not correcting the count-data for batch effects. If batch is
## included in EdgerR/limma's model, then this is probably wise; but in extreme
## batch effects this is a good parameter to play with.
## Step 1: performing count filter with option: cbcb
## Removing 165 low-count genes (2467 remaining).
## Removing 102 low-count genes (2530 remaining).
## Step 2: normalizing the data with quant.
## Using normalize.quantiles.robust due to a thread error in preprocessCore.
## Step 3: converting the data with cpm.
## Step 4: transforming the data with log2.
## transform_counts: Found 102 values equal to 0, adding 1 to the matrix.
## Step 5: not doing batch correction.
## Plotting a PCA before surrogates/batch inclusion.
## Assuming no batch in model for testing pca.
## Starting basic_pairwise().
## Starting basic pairwise comparison.
## Leaving the data alone, regardless of normalization state.
## Basic step 0/3: Transforming data.
## Basic step 1/3: Creating median and variance tables.
## Basic step 2/3: Performing 6 comparisons.
## Basic step 3/3: Creating faux DE Tables.
## Basic: Returning tables.
## Starting deseq_pairwise().
## Starting DESeq2 pairwise comparisons.
## About to round the data, this is a pretty terrible thing to do. But if you, like me, want to see what happens when you put non-standard data into deseq, then here you go.
## Warning in choose_binom_dataset(input, force = force): This data was
## inappropriately forced into integers.
## Choosing the non-intercept containing model.
## DESeq2 step 1/5: Including only condition in the deseq model.
## Warning in import_deseq(data, column_data, model_string, tximport =
## input[["tximport"]][["raw"]]): Converted down 1619 elements because they
## are larger than the maximum integer size.
## converting counts to integer mode
## DESeq2 step 2/5: Estimate size factors.
## DESeq2 step 3/5: Estimate dispersions.
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## Using a parametric fitting seems to have worked.
## DESeq2 step 4/5: nbinomWaldTest.
## Starting ebseq_pairwise().
## The data should be suitable for EdgeR/DESeq/EBSeq. If they freak out, check the state of the count table and ensure that it is in integer counts.
## Starting EBSeq pairwise subset.
## Choosing the non-intercept containing model.
## Starting EBTest of comp_whole vs. delta_whole.
## Copying ppee values as ajusted p-values until I figure out how to deal with them.
## Starting EBTest of comp_whole vs. wt_whole.
## Copying ppee values as ajusted p-values until I figure out how to deal with them.
## Starting EBTest of delta_whole vs. wt_whole.
## Copying ppee values as ajusted p-values until I figure out how to deal with them.
## Starting edger_pairwise().
## Starting edgeR pairwise comparisons.
## About to round the data, this is a pretty terrible thing to do. But if you, like me, want to see what happens when you put non-standard data into deseq, then here you go.
## Warning in choose_binom_dataset(input, force = force): This data was
## inappropriately forced into integers.
## Choosing the non-intercept containing model.
## EdgeR step 1/9: Importing and normalizing data.
## EdgeR step 2/9: Estimating the common dispersion.
## EdgeR step 3/9: Estimating dispersion across genes.
## EdgeR step 4/9: Estimating GLM Common dispersion.
## EdgeR step 5/9: Estimating GLM Trended dispersion.
## EdgeR step 6/9: Estimating GLM Tagged dispersion.
## EdgeR step 7/9: Running glmFit, switch to glmQLFit by changing the argument 'edger_test'.
## EdgeR step 8/9: Making pairwise contrasts.
## Starting limma_pairwise().
## Starting limma pairwise comparison.
## Leaving the data alone, regardless of normalization state.
## libsize was not specified, this parameter has profound effects on limma's result.
## Using the libsize from expt$libsize.
## Limma step 1/6: choosing model.
## Choosing the non-intercept containing model.
## Limma step 2/6: running limma::voom(), switch with the argument 'which_voom'.
## Using normalize.method=quantile for voom.
## Limma step 3/6: running lmFit with method: ls.
## Limma step 4/6: making and fitting contrasts with no intercept. (~ 0 + factors)
## Limma step 5/6: Running eBayes with robust=FALSE and trend=FALSE.
## Limma step 6/6: Writing limma outputs.
## Limma step 6/6: 1/3: Creating table: delta_whole_vs_comp_whole. Adjust=BH
## Limma step 6/6: 2/3: Creating table: wt_whole_vs_comp_whole. Adjust=BH
## Limma step 6/6: 3/3: Creating table: wt_whole_vs_delta_whole. Adjust=BH
## Limma step 6/6: 1/3: Creating table: comp_whole. Adjust=BH
## Limma step 6/6: 2/3: Creating table: delta_whole. Adjust=BH
## Limma step 6/6: 3/3: Creating table: wt_whole. Adjust=BH
## Comparing analyses.
enc_whole_table <- combine_de_tables(
enc_whole_de,
keepers=keeper,
excel=glue::glue("excel/enc_whole_combined_de-v{ver}.xlsx"))
## Writing a legend of columns.
## Printing a pca plot before/after surrogates/batch estimation.
## The keepers has no elements in the coefficients.
## Here are the keepers: delta_filtrate, wt_filtrate
## Here are the coefficients: delta_whole, comp_whole, wt_whole, comp_whole, wt_whole, delta_whole
## Error in combine_de_tables(enc_whole_de, keepers = keeper, excel = glue::glue("excel/enc_whole_combined_de-v{ver}.xlsx")): Unable to find the set of contrasts to keep, fix this and try again.
enc_filtrate_de <- all_pairwise(enc_filtrate, parallel=FALSE, force=TRUE,
do_ebseq=TRUE, model_batch=FALSE)
## This function will replace the expt$expressionset slot with:
## log2(cpm(quant(cbcb(data))))
## It will save copies of each step along the way
## in expt$normalized with the corresponding libsizes. Keep libsizes in mind
## when invoking limma. The appropriate libsize is non-log(cpm(normalized)).
## This is most likely kept at:
## 'new_expt$normalized$intermediate_counts$normalization$libsizes'
## A copy of this may also be found at:
## new_expt$best_libsize
## Not correcting the count-data for batch effects. If batch is
## included in EdgerR/limma's model, then this is probably wise; but in extreme
## batch effects this is a good parameter to play with.
## Step 1: performing count filter with option: cbcb
## Removing 1172 low-count genes (1460 remaining).
## Removing 1018 low-count genes (1614 remaining).
## Step 2: normalizing the data with quant.
## Using normalize.quantiles.robust due to a thread error in preprocessCore.
## Step 3: converting the data with cpm.
## Step 4: transforming the data with log2.
## transform_counts: Found 6 values equal to 0, adding 1 to the matrix.
## Step 5: not doing batch correction.
## Plotting a PCA before surrogates/batch inclusion.
## Assuming no batch in model for testing pca.
## Starting basic_pairwise().
## Starting basic pairwise comparison.
## Leaving the data alone, regardless of normalization state.
## Basic step 0/3: Transforming data.
## Basic step 1/3: Creating median and variance tables.
## Basic step 2/3: Performing 6 comparisons.
## Basic step 3/3: Creating faux DE Tables.
## Basic: Returning tables.
## Starting deseq_pairwise().
## Starting DESeq2 pairwise comparisons.
## About to round the data, this is a pretty terrible thing to do. But if you, like me, want to see what happens when you put non-standard data into deseq, then here you go.
## Warning in choose_binom_dataset(input, force = force): This data was
## inappropriately forced into integers.
## Choosing the non-intercept containing model.
## DESeq2 step 1/5: Including only condition in the deseq model.
## Warning in import_deseq(data, column_data, model_string, tximport =
## input[["tximport"]][["raw"]]): Converted down 425 elements because they are
## larger than the maximum integer size.
## converting counts to integer mode
## DESeq2 step 2/5: Estimate size factors.
## DESeq2 step 3/5: Estimate dispersions.
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## Using a parametric fitting seems to have worked.
## DESeq2 step 4/5: nbinomWaldTest.
## Starting ebseq_pairwise().
## The data should be suitable for EdgeR/DESeq/EBSeq. If they freak out, check the state of the count table and ensure that it is in integer counts.
## Starting EBSeq pairwise subset.
## Choosing the non-intercept containing model.
## Starting EBTest of comp_filtrate vs. delta_filtrate.
## Copying ppee values as ajusted p-values until I figure out how to deal with them.
## Starting EBTest of comp_filtrate vs. wt_filtrate.
## Copying ppee values as ajusted p-values until I figure out how to deal with them.
## Starting EBTest of delta_filtrate vs. wt_filtrate.
## Copying ppee values as ajusted p-values until I figure out how to deal with them.
## Starting edger_pairwise().
## Starting edgeR pairwise comparisons.
## About to round the data, this is a pretty terrible thing to do. But if you, like me, want to see what happens when you put non-standard data into deseq, then here you go.
## Warning in choose_binom_dataset(input, force = force): This data was
## inappropriately forced into integers.
## Choosing the non-intercept containing model.
## EdgeR step 1/9: Importing and normalizing data.
## EdgeR step 2/9: Estimating the common dispersion.
## EdgeR step 3/9: Estimating dispersion across genes.
## EdgeR step 4/9: Estimating GLM Common dispersion.
## EdgeR step 5/9: Estimating GLM Trended dispersion.
## EdgeR step 6/9: Estimating GLM Tagged dispersion.
## EdgeR step 7/9: Running glmFit, switch to glmQLFit by changing the argument 'edger_test'.
## EdgeR step 8/9: Making pairwise contrasts.
## Starting limma_pairwise().
## Starting limma pairwise comparison.
## Leaving the data alone, regardless of normalization state.
## libsize was not specified, this parameter has profound effects on limma's result.
## Using the libsize from expt$libsize.
## Limma step 1/6: choosing model.
## Choosing the non-intercept containing model.
## Limma step 2/6: running limma::voom(), switch with the argument 'which_voom'.
## Using normalize.method=quantile for voom.
## Warning in t(counts + 0.5)/(lib.size + 1): longer object length is not a
## multiple of shorter object length
## Warning in t(fitted.cpm) * (lib.size + 1): longer object length is not a
## multiple of shorter object length
## Limma step 3/6: running lmFit with method: ls.
## Limma step 4/6: making and fitting contrasts with no intercept. (~ 0 + factors)
## Limma step 5/6: Running eBayes with robust=FALSE and trend=FALSE.
## Limma step 6/6: Writing limma outputs.
## Limma step 6/6: 1/3: Creating table: delta_filtrate_vs_comp_filtrate. Adjust=BH
## Limma step 6/6: 2/3: Creating table: wt_filtrate_vs_comp_filtrate. Adjust=BH
## Limma step 6/6: 3/3: Creating table: wt_filtrate_vs_delta_filtrate. Adjust=BH
## Limma step 6/6: 1/3: Creating table: comp_filtrate. Adjust=BH
## Limma step 6/6: 2/3: Creating table: delta_filtrate. Adjust=BH
## Limma step 6/6: 3/3: Creating table: wt_filtrate. Adjust=BH
## Comparing analyses.
enc_filtrate_table <- combine_de_tables(
keepers=keeper,
enc_filtrate_de,
excel=glue::glue("excel/enc_filtrate_combined_de-v{ver}.xlsx"))
## Deleting the file excel/enc_filtrate_combined_de-v20190310.xlsx before writing the tables.
## Writing a legend of columns.
## Printing a pca plot before/after surrogates/batch estimation.
## Working on 1/1: delta_wt which is: delta_filtrate/wt_filtrate.
## Found inverse table with wt_filtrate_vs_delta_filtrate
## 20181210 a pthread error in normalize.quantiles leads me to robust.
## Used Bon Ferroni corrected t test(s) between columns.
## Used Bon Ferroni corrected t test(s) between columns.
## Used Bon Ferroni corrected t test(s) between columns.
## Adding venn plots for delta_wt.
## Limma expression coefficients for delta_wt; R^2: 0.799; equation: y = 0.927x - 0.661
## Edger expression coefficients for delta_wt; R^2: 0.557; equation: y = 0.198x + 16
## DESeq2 expression coefficients for delta_wt; R^2: 0.523; equation: y = 0.133x + 21.6
## Writing summary information.
## Attempting to add the comparison plot to pairwise_summary at row: 23 and column: 1
## Performing save of the workbook.
## Note: zip::zip() is deprecated, please use zip::zipr() instead
I am going to mostly copy/paste some of the material from 03_swath2stats_20190327.Rmd here.
mtb_gff <- "reference/mycobacterium_tuberculosis_h37rv_2.gff.gz"
mtb_annotations <- sm(load_gff_annotations(mtb_gff, type="gene"))
colnames(mtb_annotations) <- gsub(pattern="\\.", replacement="", x=colnames(mtb_annotations))
mtb_annotations[["description"]] <- gsub(pattern="\\+", replacement=" ",
x=mtb_annotations[["description"]])
mtb_annotations[["function"]] <- gsub(pattern="\\+", replacement=" ",
x=mtb_annotations[["function"]])
rownames(mtb_annotations) <- mtb_annotations[["ID"]]
ver <- "20190327"
tric_data <- read.csv(
paste0("results/tric/", ver, "/whole_8mz_tuberculist/comet_HCD.tsv"), sep="\t")
tric_data[["ProteinName"]] <- gsub(pattern="^(.*)_.*$", replacement="\\1",
x=tric_data[["ProteinName"]])
sample_annot <- extract_metadata(paste0("sample_sheets/Mtb_dia_samples_", ver, ".xlsx"))
kept <- ! grepl(x=rownames(sample_annot), pattern="^s\\.\\.")
sample_annot <- sample_annot[kept, ]
devtools::load_all("~/scratch/git/SWATH2stats_myforked")
## Loading SWATH2stats
s2s_exp <- sample_annotation(data=tric_data,
sample_annotation=sample_annot,
fullpeptidename_column="fullpeptidename")
## Found the same mzXML files in the annotations and data.
sample_cor <- plot_correlation_between_samples(
s2s_exp, size=2,
fun.aggregate=sum,
comparison=transition_group_id ~ condition + bioreplicate,
column.values="intensity")
## Number of non-decoy peptides: 20811
## Number of decoy peptides: 1002
## Decoy rate: 0.0481
## The average FDR by run on assay level is 0.007
## The average FDR by run on peptide level is 0.007
## The average FDR by run on protein level is 0.023
## Target assay FDR: 0.02
## Required overall m-score cutoff: 0.0070795
## achieving assay FDR: 0.019
## Target protein FDR: 0.02
## Required overall m-score cutoff: 0.00089125
## achieving protein FDR: 0.0172
## Original dimension: 232977, new dimension: 222739, difference: 10238.
##filtered_fq <- filter_mscore_freqobs(filtered_ms, 0.01, 0.8, rm.decoy=FALSE)
filtered_ms_fdr <- filter_mscore_fdr(filtered_ms, FFT=0.7,
overall_protein_fdr_target=prot_score,
upper_overall_peptide_fdr_limit=0.05)
## Target protein FDR: 0.000891250938133746
## Required overall m-score cutoff: 0.01
## achieving protein FDR: 0
## filter_mscore_fdr is filtering the data...
## finding m-score cutoff to achieve desired protein FDR in protein master list..
## finding m-score cutoff to achieve desired global peptide FDR..
## Target peptide FDR: 0.05
## Required overall m-score cutoff: 0.01
## Achieving peptide FDR: 0
## Proteins selected:
## Total proteins selected: 3044
## Final target proteins: 3044
## Final decoy proteins: 0
## Peptides mapping to these protein entries selected:
## Total mapping peptides: 20243
## Final target peptides: 20243
## Final decoy peptides: 0
## Total peptides selected from:
## Total peptides: 20243
## Final target peptides: 20243
## Final decoy peptides: 0
## Individual run FDR quality of the peptides was not calculated
## as not every run contains a decoy.
## The decoys have been removed from the returned data.
## Number of proteins detected: 3059
## Protein identifiers: Rv1270c, Rv0161, Rv1613, Rv0440, Rv0053, Rv0242c
## Number of proteins detected that are supported by a proteotypic peptide: 2929
## Number of proteotypic peptides detected: 20091
## Number of proteins detected: 2931
## First 6 protein identifiers: Rv1270c, Rv0161, Rv1613, Rv0440, Rv0053, Rv0242c
## Before filtering:
## Number of proteins: 2929
## Number of peptides: 20091
##
## Percentage of peptides removed: 19.21%
##
## After filtering:
## Number of proteins: 2903
## Number of peptides: 16232
## Before filtering:
## Number of proteins: 2903
## Number of peptides: 16232
##
## Percentage of peptides removed: 0.02%
##
## After filtering:
## Number of proteins: 2674
## Number of peptides: 16229
matrix_prefix <- file.path("results", "swath2stats", ver)
if (!file.exists(matrix_prefix)) {
dir.create(matrix_prefix)
}
protein_matrix_filtered <- write_matrix_proteins(
filtered_all_filters, write.csv=TRUE,
filename=file.path(matrix_prefix, "protein_matrix_filtered.csv"))
## Protein overview matrix results/swath2stats/20190327/protein_matrix_filtered.csv written to working folder.
## [1] 2674 44
peptide_matrix_filtered <- write_matrix_peptides(
filtered_all_filters, write.csv=TRUE,
filename=file.path(matrix_prefix, "peptide_matrix_filtered.csv"))
## Peptide overview matrix results/swath2stats/20190327/peptide_matrix_filtered.csv written to working folder.
## [1] 171784 44
rt_cor <- plot_correlation_between_samples(
filtered_all_filters, column.values="intensity", fun.aggregate=sum, size=2)
## I have no effing clue what this plot means.
variation <- plot_variation(filtered_all_filters, fun.aggregate=sum)
cols <- colnames(filtered_all_filters)
disaggregated <- disaggregate(filtered_all_filters, all.columns=TRUE)
## The library contains 5 transitions per precursor.
## The data table was transformed into a table containing one row per transition.
## One or several columns required by MSstats were not in the data. The columns were created and filled with NAs.
## Missing columns: productcharge, isotopelabeltype
## isotopelabeltype was filled with light.
prot_mtrx <- read.csv(file.path("results", "swath2stats", ver, "protein_matrix_filtered.csv"))
rownames(prot_mtrx) <- gsub(pattern="^1\\/", replacement="", x=prot_mtrx[["proteinname"]])
prot_mtrx <- prot_mtrx[, -1]
## Important question: Did SWATH2stats reorder my data?
colnames(prot_mtrx) <- gsub(pattern="^(.*)(2018.*)$", replacement="s\\2", x=colnames(prot_mtrx))
reordered <- colnames(prot_mtrx)
metadata <- sample_annot[reordered, ]
protein_expt <- sm(create_expt(metadata,
count_dataframe=prot_mtrx,
gene_info=mtb_annotations))
whole_expt <- subset_expt(protein_expt, subset="collectiontype=='whole'")
## There were 43, now there are 17 samples.
## There were 43, now there are 26 samples.
## The factor comp_filtrate_01 has 2 rows.
## The factor comp_filtrate_02 has 3 rows.
## The factor comp_filtrate_03 has 3 rows.
## The factor delta_filtrate_01 has 2 rows.
## The factor delta_filtrate_02 has 3 rows.
## The factor delta_filtrate_03 has 2 rows.
## The factor wt_filtrate_01 has 4 rows.
## The factor wt_filtrate_02 has 3 rows.
## The factor wt_filtrate_03 has 4 rows.
## Reading the sample metadata.
## Warning in `[<-.factor`(`*tmp*`, iseq, value = c("undefined",
## "undefined", : invalid factor level, NA generated
## The sample definitions comprises: 9 rows(samples) and 29 columns(metadata fields).
## Matched 663 annotations and counts.
## Bringing together the count matrix and gene information.
## The final expressionset has 663 rows and 9 columns.
cf_combined_norm <- normalize_expt(cf_mean, filter=TRUE, convert="cpm",
norm="quant", transform="log2")
## This function will replace the expt$expressionset slot with:
## log2(cpm(quant(cbcb(data))))
## It will save copies of each step along the way
## in expt$normalized with the corresponding libsizes. Keep libsizes in mind
## when invoking limma. The appropriate libsize is non-log(cpm(normalized)).
## This is most likely kept at:
## 'new_expt$normalized$intermediate_counts$normalization$libsizes'
## A copy of this may also be found at:
## new_expt$best_libsize
## Not correcting the count-data for batch effects. If batch is
## included in EdgerR/limma's model, then this is probably wise; but in extreme
## batch effects this is a good parameter to play with.
## Step 1: performing count filter with option: cbcb
## Removing 0 low-count genes (663 remaining).
## Removing 0 low-count genes (663 remaining).
## Step 2: normalizing the data with quant.
## Using normalize.quantiles.robust due to a thread error in preprocessCore.
## Step 3: converting the data with cpm.
## Step 4: transforming the data with log2.
## Step 5: not doing batch correction.
## This function will replace the expt$expressionset slot with:
## log2(cpm(quant(cbcb(data))))
## It will save copies of each step along the way
## in expt$normalized with the corresponding libsizes. Keep libsizes in mind
## when invoking limma. The appropriate libsize is non-log(cpm(normalized)).
## This is most likely kept at:
## 'new_expt$normalized$intermediate_counts$normalization$libsizes'
## A copy of this may also be found at:
## new_expt$best_libsize
## Not correcting the count-data for batch effects. If batch is
## included in EdgerR/limma's model, then this is probably wise; but in extreme
## batch effects this is a good parameter to play with.
## Step 1: performing count filter with option: cbcb
## Removing 0 low-count genes (663 remaining).
## Removing 0 low-count genes (663 remaining).
## Step 2: normalizing the data with quant.
## Using normalize.quantiles.robust due to a thread error in preprocessCore.
## Step 3: converting the data with cpm.
## Step 4: transforming the data with log2.
## Step 5: not doing batch correction.
## Plotting a PCA before surrogates/batch inclusion.
## Using limma's removeBatchEffect to visualize with(out) batch inclusion.
## Starting basic_pairwise().
## Starting basic pairwise comparison.
## Leaving the data alone, regardless of normalization state.
## Basic step 0/3: Transforming data.
## Basic step 1/3: Creating median and variance tables.
## Basic step 2/3: Performing 6 comparisons.
## Basic step 3/3: Creating faux DE Tables.
## Basic: Returning tables.
## Starting deseq_pairwise().
## Starting DESeq2 pairwise comparisons.
## About to round the data, this is a pretty terrible thing to do. But if you, like me, want to see what happens when you put non-standard data into deseq, then here you go.
## Warning in choose_binom_dataset(input, force = force): This data was
## inappropriately forced into integers.
## The condition+batch model failed. Does your experimental design support both condition and batch? Using only a conditional model.
## Choosing the non-intercept containing model.
## DESeq2 step 1/5: Including batch and condition in the deseq model.
## converting counts to integer mode
## DESeq2 step 2/5: Estimate size factors.
## DESeq2 step 3/5: Estimate dispersions.
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## Using a parametric fitting seems to have worked.
## DESeq2 step 4/5: nbinomWaldTest.
## Starting ebseq_pairwise().
## The data should be suitable for EdgeR/DESeq/EBSeq. If they freak out, check the state of the count table and ensure that it is in integer counts.
## Starting EBSeq pairwise subset.
## Choosing the non-intercept containing model.
## Starting EBTest of comp_filtrate vs. delta_filtrate.
## Copying ppee values as ajusted p-values until I figure out how to deal with them.
## Starting EBTest of comp_filtrate vs. wt_filtrate.
## Copying ppee values as ajusted p-values until I figure out how to deal with them.
## Starting EBTest of delta_filtrate vs. wt_filtrate.
## Copying ppee values as ajusted p-values until I figure out how to deal with them.
## Starting edger_pairwise().
## Starting edgeR pairwise comparisons.
## About to round the data, this is a pretty terrible thing to do. But if you, like me, want to see what happens when you put non-standard data into deseq, then here you go.
## Warning in choose_binom_dataset(input, force = force): This data was
## inappropriately forced into integers.
## The condition+batch model failed. Does your experimental design support both condition and batch? Using only a conditional model.
## Choosing the non-intercept containing model.
## EdgeR step 1/9: Importing and normalizing data.
## EdgeR step 2/9: Estimating the common dispersion.
## EdgeR step 3/9: Estimating dispersion across genes.
## EdgeR step 4/9: Estimating GLM Common dispersion.
## EdgeR step 5/9: Estimating GLM Trended dispersion.
## EdgeR step 6/9: Estimating GLM Tagged dispersion.
## EdgeR step 7/9: Running glmFit, switch to glmQLFit by changing the argument 'edger_test'.
## EdgeR step 8/9: Making pairwise contrasts.
## Starting limma_pairwise().
## Starting limma pairwise comparison.
## Leaving the data alone, regardless of normalization state.
## libsize was not specified, this parameter has profound effects on limma's result.
## Using the libsize from expt$libsize.
## Limma step 1/6: choosing model.
## The condition+batch model failed. Does your experimental design support both condition and batch? Using only a conditional model.
## Choosing the non-intercept containing model.
## Limma step 2/6: running limma::voom(), switch with the argument 'which_voom'.
## Using normalize.method=quantile for voom.
## Limma step 3/6: running lmFit with method: ls.
## Limma step 4/6: making and fitting contrasts with no intercept. (~ 0 + factors)
## Limma step 5/6: Running eBayes with robust=FALSE and trend=FALSE.
## Limma step 6/6: Writing limma outputs.
## Limma step 6/6: 1/3: Creating table: delta_filtrate_vs_comp_filtrate. Adjust=BH
## Limma step 6/6: 2/3: Creating table: wt_filtrate_vs_comp_filtrate. Adjust=BH
## Limma step 6/6: 3/3: Creating table: wt_filtrate_vs_delta_filtrate. Adjust=BH
## Limma step 6/6: 1/3: Creating table: comp_filtrate. Adjust=BH
## Limma step 6/6: 2/3: Creating table: delta_filtrate. Adjust=BH
## Limma step 6/6: 3/3: Creating table: wt_filtrate. Adjust=BH
## Comparing analyses.
## Writing a legend of columns.
## Working on 1/1: delta_wt which is: delta_filtrate/wt_filtrate.
## Found inverse table with wt_filtrate_vs_delta_filtrate
## 20181210 a pthread error in normalize.quantiles leads me to robust.
## Used Bon Ferroni corrected t test(s) between columns.
## Used Bon Ferroni corrected t test(s) between columns.
## Used Bon Ferroni corrected t test(s) between columns.
osw_table <- cf_table[["data"]][[1]]
enc_table <- enc_filtrate_table[["data"]][[1]]
drop_idx <- ! enc_table[["edger_logfc"]] > 10
enc_table <- enc_table[drop_idx, ]
drop_idx <- ! enc_table[["edger_logfc"]] < -10
enc_table <- enc_table[drop_idx, ]
merged_table <- merge(osw_table, enc_table, by="row.names")
cor.test(merged_table[["edger_logfc.x"]], merged_table[["edger_logfc.y"]])
##
## Pearson's product-moment correlation
##
## data: merged_table[["edger_logfc.x"]] and merged_table[["edger_logfc.y"]]
## t = 16, df = 650, p-value <2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.4682 0.5796
## sample estimates:
## cor
## 0.5262
plot_linear_scatter(merged_table[, c("deseq_logfc.x", "deseq_logfc.y")])$scatter +
ggplot2::ylim(-5, 5)
## Used Bon Ferroni corrected t test(s) between columns.
## Warning: Removed 4 rows containing missing values (geom_point).
favorite_idx <- merged_table[["edger_logfc.x"]] >= 1 &
merged_table[["edger_logfc.y"]] >= 1 &
merged_table[["edger_adjp.x"]] <= 0.05
favorites <- merged_table[favorite_idx, ]
write.csv(x=favorites, file="conservative_increased_delta_filtrate.csv")
knitr::kable(favorites)
Row.names | seqnames | start | end | width | strand | source | type | score | phase | id | locustag | gene | description | function. | deseq_logfc.x | deseq_adjp.x | edger_logfc.x | edger_adjp.x | limma_logfc.x | limma_adjp.x | basic_nummed.x | basic_denmed.x | basic_numvar.x | basic_denvar.x | basic_logfc.x | basic_t.x | basic_p.x | basic_adjp.x | deseq_basemean.x | deseq_lfcse.x | deseq_stat.x | deseq_p.x | ebseq_fc.x | ebseq_logfc.x | ebseq_postfc.x | ebseq_mean.x | ebseq_ppee.x | ebseq_ppde.x | ebseq_adjp.x | edger_logcpm.x | edger_lr.x | edger_p.x | limma_ave.x | limma_t.x | limma_b.x | limma_p.x | limma_adjp_fdr.x | deseq_adjp_fdr.x | edger_adjp_fdr.x | basic_adjp_fdr.x | lfc_meta.x | lfc_var.x | lfc_varbymed.x | p_meta.x | p_var.x | deseq_logfc.y | deseq_adjp.y | edger_logfc.y | edger_adjp.y | limma_logfc.y | limma_adjp.y | basic_nummed.y | basic_denmed.y | basic_numvar.y | basic_denvar.y | basic_logfc.y | basic_t.y | basic_p.y | basic_adjp.y | deseq_basemean.y | deseq_lfcse.y | deseq_stat.y | deseq_p.y | ebseq_fc.y | ebseq_logfc.y | ebseq_postfc.y | ebseq_mean.y | ebseq_ppee.y | ebseq_ppde.y | ebseq_adjp.y | edger_logcpm.y | edger_lr.y | edger_p.y | limma_ave.y | limma_t.y | limma_b.y | limma_p.y | limma_adjp_fdr.y | deseq_adjp_fdr.y | edger_adjp_fdr.y | basic_adjp_fdr.y | lfc_meta.y | lfc_var.y | lfc_varbymed.y | p_meta.y | p_var.y | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
4 | Rv0007 | Mtb_R24 | 9914 | 10828 | 915 | + | artemis | gene | undefined | undefined | Rv0007 | Rv0007 | Rv0007 | conserved membrane protein | Unknown | 2.606 | 0.0000 | 2.607 | 0.0000 | 2.348 | 0.0168 | 4.703 | 7.715 | 3.349e-01 | 1.227e+00 | 3.0120 | -3.429 | 4.122e-02 | 3.253e-01 | 131.40 | 0.5030 | 5.182 | 0.0000 | 0.1632 | 2.615 | 0.1678 | 103.66 | 0.0001 | 9.999e-01 | 0.0001 | 7.058 | 25.360 | 0.0000 | 6.589 | -4.622 | -0.3206 | 0.0007 | 1.676e-02 | 9.087e-06 | 2.247e-05 | 3.253e-01 | 2.549 | 1.048e-02 | 4.112e-03 | 2.430e-04 | 1.767e-07 | 2.818 | 0.0017 | 2.687 | 0.0720 | 2.5010 | 0.1356 | 21.18 | 25.35 | 5.718e+00 | 3.183e+00 | 4.180 | -3.257 | 3.493e-02 | 3.495e-01 | 3.183e+07 | 0.7824 | 3.602 | 0.0003 | 0.2043 | 2.2910 | 0.2060 | 1.789e+07 | 0.5439 | 4.561e-01 | 0.5439 | 4.890 | 6.423 | 0.0113 | 4.8370 | -2.9010 | -2.9610 | 0.0182 | 1.356e-01 | 3.088e-03 | 7.193e-02 | 3.496e-01 | 11.380 | 2.228e+02 | 1.958e+01 | 9.932e-03 | 8.146e-05 |
14 | Rv0056 | Mtb_R24 | 59409 | 59867 | 459 | + | artemis | gene | undefined | undefined | Rv0056 | Rv0056 | rplI | 50S ribosomal protein L9 | Binds to the 23S rRNA. | 1.774 | 0.0185 | 1.796 | 0.0137 | 2.040 | 0.0455 | 6.023 | 7.996 | 2.578e+00 | 4.433e-02 | 1.9730 | -2.302 | 1.438e-01 | 4.928e-01 | 224.40 | 0.5850 | 3.032 | 0.0024 | 0.2791 | 1.841 | 0.2819 | 160.66 | 0.0028 | 9.972e-01 | 0.0028 | 7.823 | 10.460 | 0.0012 | 7.407 | -3.612 | -2.0680 | 0.0041 | 4.552e-02 | 1.897e-02 | 1.373e-02 | 4.927e-01 | 1.930 | 5.847e-02 | 3.030e-02 | 2.568e-03 | 2.015e-06 | 1.633 | 0.0004 | 1.567 | 0.0687 | 2.0250 | 0.0125 | 23.75 | 27.41 | 1.073e+00 | 1.844e+00 | 3.662 | -3.860 | 2.058e-02 | 2.896e-01 | 1.414e+08 | 0.4090 | 3.993 | 0.0001 | 0.4298 | 1.2181 | 0.4301 | 9.572e+07 | 0.7659 | 2.341e-01 | 0.7659 | 7.062 | 6.528 | 0.0106 | 8.1950 | -5.9370 | 0.9284 | 0.0003 | 1.253e-02 | 7.210e-04 | 6.868e-02 | 2.897e-01 | 10.520 | 2.380e+02 | 2.263e+01 | 3.646e-03 | 3.649e-05 |
30 | Rv0175 | Mtb_R24 | 206814 | 207455 | 642 | + | artemis | gene | undefined | undefined | Rv0175 | Rv0175 | Rv0175 | MCE-associated membrane protein | Unknown | 2.447 | 0.0073 | 2.414 | 0.0066 | 2.051 | 0.0908 | 2.620 | 4.655 | 5.162e-01 | 2.629e+00 | 2.0350 | -2.040 | 1.421e-01 | 4.928e-01 | 22.64 | 0.7257 | 3.372 | 0.0007 | 0.1855 | 2.430 | 0.2024 | 27.34 | 0.3154 | 6.846e-01 | 0.3154 | 4.606 | 12.160 | 0.0005 | 3.914 | -2.869 | -3.1890 | 0.0152 | 9.079e-02 | 7.508e-03 | 6.622e-03 | 4.927e-01 | 2.373 | 9.919e-03 | 4.180e-03 | 5.479e-03 | 7.089e-05 | 2.138 | 0.0000 | 1.966 | 0.6547 | -0.2713 | 0.9267 | 19.76 | 22.97 | 1.003e-01 | 4.670e+00 | 3.202 | -3.318 | 7.563e-02 | 4.542e-01 | 6.079e+06 | 0.4753 | 4.500 | 0.0000 | 0.3651 | 1.4537 | 0.3705 | 4.822e+06 | 0.5149 | 4.851e-01 | 0.5149 | 2.449 | 1.052 | 0.3050 | 2.4640 | 0.1894 | -5.4990 | 0.8542 | 9.267e-01 | 8.496e-05 | 6.548e-01 | 4.543e-01 | 2.156 | 3.966e-02 | 1.840e-02 | 3.864e-01 | 1.874e-01 |
31 | Rv0178 | Mtb_R24 | 208938 | 209672 | 735 | + | artemis | gene | undefined | undefined | Rv0178 | Rv0178 | Rv0178 | MCE-associated membrane protein | Unknown | 3.164 | 0.0001 | 3.153 | 0.0002 | 2.826 | 0.0432 | 3.314 | 6.634 | 5.785e-01 | 3.423e+00 | 3.3200 | -2.404 | 1.067e-01 | 4.424e-01 | 41.88 | 0.6953 | 4.550 | 0.0000 | 0.1134 | 3.141 | 0.1257 | 38.58 | 0.0042 | 9.958e-01 | 0.0042 | 5.453 | 20.650 | 0.0000 | 4.701 | -3.683 | -1.7950 | 0.0036 | 4.322e-02 | 1.366e-04 | 1.824e-04 | 4.423e-01 | 3.067 | 2.530e-02 | 8.250e-03 | 1.197e-03 | 4.257e-06 | 2.574 | 0.0000 | 2.439 | 0.1437 | 2.1930 | 0.1299 | 20.49 | 24.97 | 1.197e+00 | 3.489e+00 | 4.482 | -3.834 | 2.745e-02 | 3.181e-01 | 2.086e+07 | 0.4699 | 5.477 | 0.0000 | 0.2479 | 2.0120 | 0.2499 | 1.485e+07 | 0.5556 | 4.444e-01 | 0.5556 | 4.262 | 4.723 | 0.0298 | 5.2900 | -3.3080 | -2.3910 | 0.0096 | 1.299e-01 | 6.210e-07 | 1.437e-01 | 3.181e-01 | 11.170 | 2.243e+02 | 2.009e+01 | 1.311e-02 | 2.308e-04 |
41 | Rv0216 | Mtb_R24 | 258913 | 259926 | 1014 | + | artemis | gene | undefined | undefined | Rv0216 | Rv0216 | Rv0216 | conserved hypothetical protein | Unknown | 1.663 | 0.0012 | 1.665 | 0.0079 | 1.601 | 0.0262 | 4.291 | 6.347 | 2.796e-02 | 4.818e-01 | 2.0560 | -3.889 | 5.034e-02 | 3.374e-01 | 39.12 | 0.4224 | 3.936 | 0.0001 | 0.3094 | 1.692 | 0.3196 | 42.72 | 0.0000 | 1.000e+00 | 0.0000 | 5.352 | 11.680 | 0.0006 | 5.092 | -4.203 | -0.9701 | 0.0015 | 2.620e-02 | 1.276e-03 | 7.901e-03 | 3.374e-01 | 1.658 | 2.376e-04 | 1.433e-04 | 7.255e-04 | 4.822e-07 | 2.317 | 0.0014 | 2.218 | 0.3099 | 1.1830 | 0.5137 | 20.54 | 24.61 | 2.507e+00 | 2.529e+00 | 4.070 | -3.640 | 2.197e-02 | 2.948e-01 | 1.522e+07 | 0.6335 | 3.658 | 0.0003 | 0.2775 | 1.8493 | 0.2801 | 1.084e+07 | 0.6073 | 3.927e-01 | 0.6073 | 3.832 | 2.842 | 0.0918 | 3.9240 | -1.1240 | -5.1900 | 0.2910 | 5.137e-01 | 2.562e-03 | 3.099e-01 | 2.947e-01 | 10.280 | 1.921e+02 | 1.868e+01 | 1.277e-01 | 2.210e-02 |
53 | Rv0270 | Mtb_R24 | 324567 | 326249 | 1683 | + | artemis | gene | undefined | undefined | Rv0270 | Rv0270 | fadD2 | fatty-acid-CoA ligase | Function unknown, but involved in lipid degradation. | 1.723 | 0.0000 | 1.734 | 0.0012 | 1.560 | 0.0157 | 5.446 | 7.434 | 1.244e-01 | 1.190e-01 | 1.9880 | -5.974 | 3.951e-03 | 2.873e-01 | 111.00 | 0.3492 | 4.933 | 0.0000 | 0.2959 | 1.757 | 0.3001 | 105.35 | 0.0000 | 1.000e+00 | 0.0000 | 6.816 | 16.470 | 0.0000 | 6.631 | -4.752 | -0.1286 | 0.0006 | 1.570e-02 | 2.329e-05 | 1.172e-03 | 2.873e-01 | 1.685 | 5.885e-03 | 3.492e-03 | 2.132e-04 | 1.066e-07 | 2.139 | 1.0000 | 2.163 | 0.0518 | 1.9630 | 0.2710 | 23.74 | 25.40 | 4.988e-01 | 1.256e+01 | 1.658 | -1.856 | 1.953e-01 | 5.188e-01 | 7.688e+07 | 0.6985 | 3.062 | 1.0000 | 0.4005 | 1.3202 | 0.4009 | 5.835e+07 | 0.5208 | 4.792e-01 | 0.5208 | 6.221 | 7.154 | 0.0075 | 6.5870 | -1.8680 | -4.8400 | 0.0959 | 2.710e-01 | 1.000e+00 | 5.180e-02 | 5.188e-01 | 10.870 | 2.282e+02 | 2.101e+01 | 3.678e-01 | 3.017e-01 |
69 | Rv0357c | Mtb_R24 | 435471 | 436769 | 1299 | - | artemis | gene | undefined | undefined | Rv0357c | Rv0357c | purA | adenylosuccinate synthetase | Involved in AMP biosynthesis (first committed step). Plays an important role in the de novo pathway of purine nucleotide biosynthesis [catalytic activity: GTP imp L-aspartate = GDP phosphate adenylosuccinate]. | 2.743 | 0.0000 | 2.742 | 0.0000 | 2.619 | 0.0023 | 3.519 | 6.367 | 3.606e-01 | 3.074e-01 | 2.8480 | -5.728 | 4.687e-03 | 2.873e-01 | 54.15 | 0.4420 | 6.206 | 0.0000 | 0.1509 | 2.728 | 0.1608 | 47.71 | 0.0000 | 1.000e+00 | 0.0000 | 5.807 | 27.810 | 0.0000 | 5.376 | -6.913 | 3.0280 | 0.0000 | 2.346e-03 | 2.773e-08 | 7.381e-06 | 2.873e-01 | 2.739 | 1.408e-05 | 5.142e-06 | 8.301e-06 | 2.034e-10 | 2.769 | 0.0000 | 2.640 | 0.0988 | 2.2990 | 0.1095 | 20.47 | 25.01 | 7.060e-01 | 3.442e+00 | 4.540 | -4.179 | 2.880e-02 | 3.211e-01 | 2.138e+07 | 0.3844 | 7.203 | 0.0000 | 0.2167 | 2.2063 | 0.2186 | 1.511e+07 | 0.5098 | 4.902e-01 | 0.5098 | 4.296 | 5.619 | 0.0178 | 5.3150 | -3.5390 | -2.0700 | 0.0067 | 1.095e-01 | 9.634e-12 | 9.883e-02 | 3.212e-01 | 11.310 | 2.215e+02 | 1.958e+01 | 8.153e-03 | 8.044e-05 |
70 | Rv0360c | Mtb_R24 | 438302 | 438739 | 438 | - | artemis | gene | undefined | undefined | Rv0360c | Rv0360c | Rv0360c | conserved hypothetical protein | Function unknown | 1.678 | 0.0182 | 1.688 | 0.0260 | 1.765 | 0.0572 | 3.705 | 5.643 | 9.667e-01 | 8.947e-02 | 1.9380 | -3.044 | 7.549e-02 | 3.997e-01 | 41.18 | 0.5501 | 3.050 | 0.0023 | 0.2946 | 1.763 | 0.3086 | 31.25 | 0.0030 | 9.970e-01 | 0.0030 | 5.431 | 8.820 | 0.0030 | 5.066 | -3.332 | -2.4290 | 0.0066 | 5.722e-02 | 1.864e-02 | 2.600e-02 | 3.996e-01 | 1.707 | 1.752e-03 | 1.026e-03 | 3.971e-03 | 5.484e-06 | 2.534 | 0.3561 | 2.378 | 0.4824 | 5.6180 | 0.1833 | 21.22 | 25.15 | 1.620e+02 | 3.628e+00 | 3.938 | -1.523 | 2.620e-01 | 5.188e-01 | 2.504e+07 | 1.9320 | 1.312 | 0.1897 | 0.2558 | 1.9667 | 0.2575 | 1.713e+07 | 0.5844 | 4.156e-01 | 0.5844 | 4.525 | 1.752 | 0.1857 | 4.4620 | -2.5070 | -3.4070 | 0.0344 | 1.833e-01 | 6.577e-01 | 4.823e-01 | 5.188e-01 | 11.740 | 2.578e+02 | 2.196e+01 | 1.366e-01 | 7.838e-03 |
71 | Rv0361 | Mtb_R24 | 438822 | 439649 | 828 | + | artemis | gene | undefined | undefined | Rv0361 | Rv0361 | Rv0361 | conserved membrane protein | Unknown | 2.208 | 0.0162 | 2.207 | 0.0143 | 1.655 | 0.2201 | 4.076 | 6.696 | 4.724e-01 | 3.939e+00 | 2.6200 | -1.456 | 2.596e-01 | 5.555e-01 | 62.57 | 0.7083 | 3.117 | 0.0018 | 0.2139 | 2.225 | 0.2238 | 46.61 | 0.0771 | 9.229e-01 | 0.0771 | 6.016 | 10.330 | 0.0013 | 5.423 | -2.014 | -4.6690 | 0.0690 | 2.201e-01 | 1.657e-02 | 1.429e-02 | 5.556e-01 | 2.033 | 9.170e-02 | 4.511e-02 | 2.406e-02 | 1.518e-03 | 1.889 | 0.0088 | 1.839 | 0.4372 | -2.0820 | 0.6276 | 20.66 | 24.30 | 1.764e+00 | 1.582e+00 | 3.643 | -3.959 | 1.678e-02 | 2.718e-01 | 1.474e+07 | 0.6096 | 3.099 | 0.0019 | 0.3551 | 1.4935 | 0.3578 | 1.006e+07 | 0.6334 | 3.666e-01 | 0.6334 | 3.803 | 2.003 | 0.1570 | 3.5910 | 0.8942 | -5.1380 | 0.3953 | 6.275e-01 | 1.622e-02 | 4.372e-01 | 2.718e-01 | 1.369 | 7.603e-01 | 5.552e-01 | 1.847e-01 | 3.926e-02 |
141 | Rv0709 | Mtb_R24 | 805526 | 805759 | 234 | + | artemis | gene | undefined | undefined | Rv0709 | Rv0709 | rpmC | 50S ribosomal protein L29 | Involved in translation mechanisms. | 1.773 | 0.0002 | 1.787 | 0.0009 | 1.932 | 0.0059 | 8.188 | 10.240 | 5.338e-01 | 1.647e-01 | 2.0540 | -3.784 | 3.009e-02 | 3.118e-01 | 924.60 | 0.3945 | 4.493 | 0.0000 | 0.2850 | 1.811 | 0.2855 | 802.22 | 0.0000 | 1.000e+00 | 0.0000 | 9.852 | 17.120 | 0.0000 | 9.657 | -5.707 | 1.2680 | 0.0001 | 5.913e-03 | 1.673e-04 | 8.607e-04 | 3.118e-01 | 1.821 | 6.543e-03 | 3.592e-03 | 5.869e-05 | 4.450e-09 | 1.286 | 0.0084 | 1.277 | 0.1282 | 1.8160 | 0.0145 | 26.03 | 29.05 | 3.525e-01 | 6.870e-01 | 3.027 | -5.502 | 7.059e-03 | 2.064e-01 | 3.981e+08 | 0.4129 | 3.114 | 0.0018 | 0.5118 | 0.9662 | 0.5119 | 3.098e+08 | 0.7708 | 2.292e-01 | 0.7708 | 8.574 | 4.974 | 0.0257 | 9.7340 | -5.7850 | 0.5963 | 0.0003 | 1.451e-02 | 1.553e-02 | 1.282e-01 | 2.064e-01 | 10.270 | 2.420e+02 | 2.355e+01 | 9.293e-03 | 2.032e-04 |
155 | Rv0800 | Mtb_R24 | 893318 | 894619 | 1302 | + | artemis | gene | undefined | undefined | Rv0800 | Rv0800 | pepC | aminopeptidase | Function unknown; possibly hydrolyzes peptides and/or proteins. | 1.416 | 0.0052 | 1.416 | 0.0137 | 1.323 | 0.0649 | 7.170 | 8.143 | 3.191e-01 | 4.669e-01 | 0.9732 | -2.678 | 5.739e-02 | 3.625e-01 | 251.60 | 0.4027 | 3.516 | 0.0004 | 0.3711 | 1.430 | 0.3729 | 236.40 | 0.0041 | 9.959e-01 | 0.0041 | 7.979 | 10.480 | 0.0012 | 7.817 | -3.193 | -2.8500 | 0.0085 | 6.488e-02 | 5.290e-03 | 1.373e-02 | 3.625e-01 | 1.420 | 4.069e-05 | 2.866e-05 | 3.387e-03 | 1.987e-05 | 1.041 | 0.0350 | 1.029 | 0.3523 | 1.1310 | 0.2648 | 24.38 | 27.16 | 1.798e-01 | 8.370e-01 | 2.773 | -5.163 | 1.637e-02 | 2.718e-01 | 1.088e+08 | 0.4038 | 2.577 | 0.0100 | 0.6131 | 0.7058 | 0.6133 | 8.367e+07 | 0.6714 | 3.286e-01 | 0.6714 | 6.699 | 2.524 | 0.1122 | 7.8540 | -1.9830 | -4.7050 | 0.0798 | 2.648e-01 | 6.460e-02 | 3.524e-01 | 2.718e-01 | 9.328 | 2.067e+02 | 2.216e+01 | 6.734e-02 | 2.730e-03 |
191 | Rv0991c | Mtb_R24 | 1108172 | 1108504 | 333 | - | artemis | gene | undefined | undefined | Rv0991c | Rv0991c | Rv0991c | conserved serine rich protein | Function unknown | 2.209 | 0.0005 | 2.208 | 0.0014 | 2.121 | 0.0238 | 3.408 | 5.896 | 4.595e-01 | 5.285e-01 | 2.4880 | -3.855 | 1.838e-02 | 3.118e-01 | 41.84 | 0.5232 | 4.222 | 0.0000 | 0.2097 | 2.254 | 0.2210 | 40.60 | 0.0000 | 1.000e+00 | 0.0000 | 5.447 | 16.060 | 0.0001 | 5.048 | -4.276 | -0.8326 | 0.0013 | 2.381e-02 | 4.856e-04 | 1.360e-03 | 3.118e-01 | 2.274 | 1.294e-02 | 5.688e-03 | 4.596e-04 | 5.213e-07 | 2.208 | 0.0012 | 2.178 | 0.3166 | 1.1340 | 0.5744 | 20.42 | 24.85 | 1.214e+00 | 1.022e+00 | 4.431 | -5.020 | 7.530e-03 | 2.086e-01 | 1.516e+07 | 0.5953 | 3.709 | 0.0002 | 0.2741 | 1.8670 | 0.2762 | 1.389e+07 | 0.6381 | 3.619e-01 | 0.6381 | 3.851 | 2.783 | 0.0952 | 4.6700 | -1.0060 | -5.3360 | 0.3415 | 5.743e-01 | 2.143e-03 | 3.166e-01 | 2.086e-01 | 10.110 | 1.883e+02 | 1.862e+01 | 1.457e-01 | 3.103e-02 |
221 | Rv1187 | Mtb_R24 | 1329390 | 1331021 | 1632 | + | artemis | gene | undefined | undefined | Rv1187 | Rv1187 | rocA | pyrroline-5-carboxylate dehydrogenase | Involved in the arginase pathway [catalytic activity: 1-pyrroline-5-carboxylate NAD( ) H(2)O = L-glutamate NADH] | 1.708 | 0.0169 | 1.703 | 0.0200 | 1.905 | 0.0352 | 3.117 | 4.563 | 4.884e-01 | 4.563e-01 | 1.4460 | -3.097 | 3.638e-02 | 3.226e-01 | 27.25 | 0.5516 | 3.097 | 0.0020 | 0.2889 | 1.791 | 0.3100 | 20.60 | 0.0066 | 9.934e-01 | 0.0066 | 4.870 | 9.508 | 0.0020 | 4.443 | -3.865 | -1.4770 | 0.0026 | 3.525e-02 | 1.730e-02 | 2.005e-02 | 3.226e-01 | 1.748 | 5.547e-03 | 3.172e-03 | 2.203e-03 | 1.234e-07 | 2.353 | 1.0000 | 2.262 | 0.6680 | 1.2290 | 0.9290 | 17.29 | 23.02 | 1.248e+02 | 2.171e+00 | 5.733 | -1.657 | 2.352e-01 | 5.188e-01 | 7.297e+06 | 2.0350 | 1.156 | 1.0000 | 0.2627 | 1.9285 | 0.2708 | 3.456e+06 | 0.5666 | 4.334e-01 | 0.5666 | 2.787 | 1.002 | 0.3169 | -0.7276 | -0.1804 | -4.9950 | 0.8610 | 9.290e-01 | 1.000e+00 | 6.680e-01 | 5.188e-01 | 10.480 | 1.994e+02 | 1.903e+01 | 7.260e-01 | 1.303e-01 |
246 | Rv1323 | Mtb_R24 | 1485862 | 1487031 | 1170 | + | artemis | gene | undefined | undefined | Rv1323 | Rv1323 | fadA4 | acetyl-CoA acetyltransferase | Function unknown, but supposed involvement in lipid degradation [catalytic activity: 2 acetyl-CoA = CoA acetoacetyl-CoA]. | 1.747 | 0.0306 | 1.762 | 0.0271 | 1.793 | 0.0908 | 7.421 | 9.440 | 1.727e+00 | 1.584e+00 | 2.0180 | -1.705 | 1.636e-01 | 4.936e-01 | 445.90 | 0.6184 | 2.825 | 0.0047 | 0.2947 | 1.763 | 0.2959 | 385.26 | 0.2159 | 7.841e-01 | 0.2159 | 8.806 | 8.698 | 0.0032 | 8.471 | -2.871 | -3.4380 | 0.0151 | 9.079e-02 | 3.137e-02 | 2.708e-02 | 4.936e-01 | 1.762 | 2.991e-04 | 1.698e-04 | 7.686e-03 | 4.227e-05 | 1.092 | 0.2490 | 1.061 | 0.3894 | 1.9950 | 0.0827 | 24.67 | 28.99 | 3.225e+00 | 8.507e-01 | 4.316 | -3.054 | 5.557e-02 | 4.248e-01 | 3.496e+08 | 0.6975 | 1.566 | 0.1174 | 0.5837 | 0.7767 | 0.5838 | 2.649e+08 | 0.7038 | 2.962e-01 | 0.7038 | 8.388 | 2.292 | 0.1300 | 9.3870 | -3.8810 | -1.9960 | 0.0040 | 8.271e-02 | 4.598e-01 | 3.893e-01 | 4.248e-01 | 10.160 | 2.473e+02 | 2.435e+01 | 8.380e-02 | 4.816e-03 |
255 | Rv1380 | Mtb_R24 | 1553232 | 1554191 | 960 | + | artemis | gene | undefined | undefined | Rv1380 | Rv1380 | pyrB | aspartate carbamoyltransferase | Involved in pyrimidine biosynthesis (second step) [catalytic activity: carbamoyl phosphate L-aspartate = phosphate N-carbamoyl-L-aspartate] | 2.263 | 0.0012 | 2.284 | 0.0015 | 2.414 | 0.0168 | 4.406 | 6.799 | 2.046e+00 | 4.353e-02 | 2.3930 | -3.097 | 8.576e-02 | 4.212e-01 | 87.64 | 0.5714 | 3.961 | 0.0001 | 0.2001 | 2.321 | 0.2063 | 75.39 | 0.0000 | 1.000e+00 | 0.0000 | 6.484 | 15.750 | 0.0001 | 6.072 | -4.653 | -0.2470 | 0.0007 | 1.676e-02 | 1.235e-03 | 1.464e-03 | 4.212e-01 | 2.352 | 1.920e-02 | 8.165e-03 | 2.794e-04 | 1.273e-07 | 1.402 | 0.2406 | 1.372 | 0.4519 | 0.8510 | 0.7456 | 23.06 | 25.80 | 7.955e+00 | 1.230e+00 | 2.740 | -2.525 | 9.857e-02 | 4.812e-01 | 4.522e+07 | 0.8792 | 1.595 | 0.1108 | 0.4875 | 1.0365 | 0.4882 | 3.275e+07 | 0.6809 | 3.191e-01 | 0.6809 | 5.426 | 1.895 | 0.1687 | 5.8680 | -0.6295 | -5.8780 | 0.5453 | 7.456e-01 | 4.446e-01 | 4.520e-01 | 4.812e-01 | 8.271 | 1.416e+02 | 1.712e+01 | 2.749e-01 | 5.566e-02 |
284 | Rv1536 | Mtb_R24 | 1736519 | 1739644 | 3126 | + | artemis | gene | undefined | undefined | Rv1536 | Rv1536 | ileS | isoleucyl-tRNA synthetase | Charging ILE tRNA [catalytic activity: ATP L-isoleucine tRNA(ILE) = AMP diphosphate L-isoleucyl-tRNA(ILE)]. | 1.731 | 0.0298 | 1.758 | 0.0218 | 2.017 | 0.0498 | 5.362 | 7.262 | 2.933e+00 | 8.755e-02 | 1.9010 | -2.188 | 1.530e-01 | 4.928e-01 | 143.40 | 0.6097 | 2.838 | 0.0045 | 0.2875 | 1.798 | 0.2914 | 113.46 | 0.0017 | 9.983e-01 | 0.0017 | 7.184 | 9.237 | 0.0024 | 6.806 | -3.463 | -2.3030 | 0.0053 | 4.975e-02 | 3.051e-02 | 2.183e-02 | 4.927e-01 | 1.898 | 7.189e-02 | 3.787e-02 | 4.058e-03 | 2.270e-06 | 1.490 | 0.0080 | 1.445 | 0.1262 | 1.8250 | 0.0482 | 23.97 | 27.68 | 1.294e+00 | 1.427e+00 | 3.711 | -3.863 | 1.819e-02 | 2.792e-01 | 1.310e+08 | 0.4757 | 3.133 | 0.0017 | 0.4623 | 1.1131 | 0.4625 | 1.042e+08 | 0.7568 | 2.432e-01 | 0.7568 | 6.958 | 5.008 | 0.0252 | 8.1170 | -4.4510 | -1.0010 | 0.0017 | 4.820e-02 | 1.479e-02 | 1.262e-01 | 2.791e-01 | 10.410 | 2.392e+02 | 2.299e+01 | 9.569e-03 | 1.840e-04 |
298 | Rv1612 | Mtb_R24 | 1811127 | 1812359 | 1233 | + | artemis | gene | undefined | undefined | Rv1612 | Rv1612 | trpB | tryptophan synthase, beta subunit | Tryptophan biosynthesis pathway (fifth last step). The beta subunit is responsible for the synthesis of L-tryptophan from indole and L-serine. [catalytic activity: L-serine 1-(indol-3-YL)glycerol 3-phosphate = L-tryptophan glyceraldehyde 3-phosphate H(2)O] | 1.412 | 0.0251 | 1.433 | 0.0273 | 1.266 | 0.0905 | 6.310 | 7.049 | 3.744e-01 | 4.176e-01 | 0.7386 | -2.646 | 5.741e-02 | 3.625e-01 | 150.60 | 0.4839 | 2.917 | 0.0035 | 0.3679 | 1.443 | 0.3713 | 122.77 | 0.0794 | 9.206e-01 | 0.0794 | 7.254 | 8.639 | 0.0033 | 7.009 | -2.898 | -3.3140 | 0.0144 | 9.051e-02 | 2.571e-02 | 2.727e-02 | 3.625e-01 | 1.405 | 9.151e-04 | 6.514e-04 | 7.086e-03 | 4.057e-05 | 1.477 | 0.0039 | 1.322 | 0.1987 | 1.9250 | 0.0646 | 23.74 | 26.63 | 1.102e+00 | 4.079e+00 | 2.890 | -2.793 | 6.807e-02 | 4.400e-01 | 9.194e+07 | 0.4395 | 3.362 | 0.0008 | 0.5512 | 0.8594 | 0.5515 | 6.685e+07 | 0.7528 | 2.472e-01 | 0.7528 | 6.400 | 3.923 | 0.0476 | 7.6910 | -4.2010 | -1.3190 | 0.0025 | 6.460e-02 | 7.253e-03 | 1.987e-01 | 4.400e-01 | 10.360 | 2.412e+02 | 2.327e+01 | 1.697e-02 | 7.062e-04 |
328 | Rv1809 | Mtb_R24 | 2051282 | 2052688 | 1407 | + | artemis | gene | undefined | undefined | Rv1809 | Rv1809 | PPE33 | PPE family protein | Function unknown | 3.240 | 0.0001 | 3.249 | 0.0001 | 2.990 | 0.0207 | 4.417 | 7.851 | 6.100e-01 | 1.434e+00 | 3.4350 | -3.807 | 2.497e-02 | 3.118e-01 | 84.78 | 0.6968 | 4.650 | 0.0000 | 0.1060 | 3.238 | 0.1103 | 109.89 | 0.0002 | 9.998e-01 | 0.0002 | 6.429 | 21.680 | 0.0000 | 5.415 | -4.431 | -0.6185 | 0.0010 | 2.067e-02 | 9.188e-05 | 1.125e-04 | 3.118e-01 | 3.216 | 2.465e-03 | 7.666e-04 | 3.348e-04 | 3.297e-07 | 1.355 | 0.0844 | 1.384 | 0.3767 | 0.1836 | 0.9422 | 23.28 | 26.69 | 7.717e-02 | 4.310e-01 | 3.414 | -7.761 | 6.447e-03 | 2.064e-01 | 4.510e+07 | 0.6204 | 2.185 | 0.0289 | 0.4751 | 1.0736 | 0.4757 | 4.408e+07 | 0.6403 | 3.597e-01 | 0.6403 | 5.443 | 2.369 | 0.1238 | 5.5280 | -0.1476 | -6.1290 | 0.8860 | 9.422e-01 | 1.558e-01 | 3.767e-01 | 2.064e-01 | 2.190 | 1.956e+00 | 8.932e-01 | 3.462e-01 | 2.208e-01 |
331 | Rv1827 | Mtb_R24 | 2072596 | 2073084 | 489 | + | artemis | gene | undefined | undefined | Rv1827 | Rv1827 | cfp17 | hypothetical protein | CDS | 1.201 | 0.0292 | 1.220 | 0.0357 | 1.300 | 0.0511 | 9.564 | 10.740 | 2.231e-01 | 1.522e-01 | 1.1710 | -3.280 | 3.211e-02 | 3.118e-01 | 1519.00 | 0.4211 | 2.853 | 0.0043 | 0.4250 | 1.234 | 0.4253 | 1471.05 | 0.0071 | 9.929e-01 | 0.0071 | 10.570 | 7.976 | 0.0047 | 10.470 | -3.425 | -2.5400 | 0.0056 | 5.114e-02 | 2.992e-02 | 3.568e-02 | 3.118e-01 | 1.269 | 1.015e-02 | 8.001e-03 | 4.902e-03 | 4.406e-07 | 1.008 | 0.2109 | 1.086 | 0.3202 | 1.7720 | 0.0157 | 27.42 | 30.56 | 8.455e-01 | 6.902e-01 | 3.141 | -4.344 | 1.249e-02 | 2.420e-01 | 9.521e+08 | 0.6012 | 1.677 | 0.0936 | 0.5806 | 0.7844 | 0.5806 | 8.325e+08 | 0.7828 | 2.172e-01 | 0.7828 | 9.868 | 2.755 | 0.0970 | 10.3200 | -5.6500 | 0.1798 | 0.0004 | 1.572e-02 | 3.895e-01 | 3.202e-01 | 2.421e-01 | 10.100 | 2.456e+02 | 2.433e+01 | 6.365e-02 | 3.007e-03 |
340 | Rv1872c | Mtb_R24 | 2121907 | 2123151 | 1245 | - | artemis | gene | undefined | undefined | Rv1872c | Rv1872c | lldD2 | L-lactate dehydrogenase | Involved in respiration; catalyzes conversion of lactate into pyruvate [catalytic activity: (S)-lactate 2 ferricytochrome C = pyruvate 2 ferrocytochrome C]. | 1.928 | 0.0020 | 1.915 | 0.0043 | 1.724 | 0.0498 | 4.900 | 6.275 | 2.001e-01 | 9.669e-01 | 1.3750 | -2.871 | 6.968e-02 | 3.997e-01 | 79.00 | 0.5073 | 3.800 | 0.0001 | 0.2614 | 1.935 | 0.2672 | 77.40 | 0.0825 | 9.175e-01 | 0.0825 | 6.329 | 13.150 | 0.0003 | 5.997 | -3.478 | -2.2470 | 0.0051 | 4.975e-02 | 2.001e-03 | 4.340e-03 | 3.996e-01 | 1.858 | 1.132e-02 | 6.091e-03 | 1.854e-03 | 8.053e-06 | 2.154 | 1.0000 | 2.666 | 0.0296 | 1.2080 | 0.6186 | 23.42 | 24.88 | 5.901e-02 | 1.746e+01 | 1.469 | -1.575 | 2.551e-01 | 5.188e-01 | 6.222e+07 | 0.7866 | 2.738 | 1.0000 | 0.3103 | 1.6882 | 0.3107 | 6.475e+07 | 0.4012 | 5.988e-01 | 0.4012 | 6.245 | 8.478 | 0.0036 | 6.6950 | -0.9210 | -5.9780 | 0.3819 | 6.186e-01 | 1.000e+00 | 2.956e-02 | 5.188e-01 | 10.490 | 1.946e+02 | 1.855e+01 | 4.618e-01 | 2.530e-01 |
377 | Rv2185c | Mtb_R24 | 2447066 | 2447500 | 435 | - | artemis | gene | undefined | undefined | Rv2185c | Rv2185c | TB16.3 | conserved hypothetical protein | Unknown | 3.805 | 0.0000 | 3.831 | 0.0000 | 3.634 | 0.0048 | 6.444 | 9.617 | 9.787e-01 | 1.211e+00 | 3.1730 | -4.281 | 1.315e-02 | 3.118e-01 | 714.40 | 0.5990 | 6.351 | 0.0000 | 0.0702 | 3.833 | 0.0709 | 704.71 | 0.0255 | 9.745e-01 | 0.0255 | 9.489 | 36.870 | 0.0000 | 8.731 | -6.001 | 1.7390 | 0.0001 | 4.819e-03 | 1.537e-08 | 1.673e-07 | 3.118e-01 | 3.782 | 3.816e-03 | 1.009e-03 | 2.908e-05 | 2.536e-09 | 1.349 | 0.0035 | 1.383 | 0.0817 | 1.9350 | 0.0157 | 26.66 | 29.63 | 1.184e-01 | 1.228e+00 | 2.973 | -5.115 | 2.480e-02 | 3.093e-01 | 5.838e+08 | 0.3970 | 3.397 | 0.0007 | 0.4863 | 1.0400 | 0.4864 | 4.233e+08 | 0.8200 | 1.800e-01 | 0.8200 | 9.140 | 6.115 | 0.0134 | 9.5300 | -5.6620 | 0.3662 | 0.0004 | 1.572e-02 | 6.443e-03 | 8.170e-02 | 3.093e-01 | 10.350 | 2.416e+02 | 2.333e+01 | 4.814e-03 | 5.544e-05 |
380 | Rv2194 | Mtb_R24 | 2457553 | 2458395 | 843 | + | artemis | gene | undefined | undefined | Rv2194 | Rv2194 | qcrC | ubiquinol-cytochrome C reductase qcrC cytochrome C subunit | Respiration | 1.524 | 0.0033 | 1.537 | 0.0072 | 1.529 | 0.0335 | 6.249 | 8.150 | 7.393e-01 | 1.923e-01 | 1.9010 | -2.898 | 6.324e-02 | 3.777e-01 | 231.30 | 0.4184 | 3.643 | 0.0003 | 0.3389 | 1.561 | 0.3411 | 195.77 | 0.0000 | 1.000e+00 | 0.0000 | 7.862 | 11.930 | 0.0006 | 7.675 | -3.947 | -1.5140 | 0.0023 | 3.352e-02 | 3.431e-03 | 7.180e-03 | 3.777e-01 | 1.547 | 8.066e-04 | 5.213e-04 | 1.028e-03 | 1.162e-06 | 1.071 | 0.0958 | 1.036 | 0.4025 | 0.9077 | 0.3800 | 23.49 | 26.99 | 1.234e+00 | 1.227e+00 | 3.498 | -3.542 | 2.398e-02 | 3.065e-01 | 9.836e+07 | 0.5046 | 2.122 | 0.0338 | 0.6084 | 0.7168 | 0.6087 | 6.658e+07 | 0.6670 | 3.330e-01 | 0.6670 | 6.553 | 2.211 | 0.1370 | 6.8330 | -1.4700 | -5.3410 | 0.1767 | 3.800e-01 | 1.769e-01 | 4.024e-01 | 3.065e-01 | 8.231 | 1.545e+02 | 1.878e+01 | 1.158e-01 | 5.441e-03 |
393 | Rv2240c | Mtb_R24 | 2511690 | 2512487 | 798 | - | artemis | gene | undefined | undefined | Rv2240c | Rv2240c | Rv2240c | hypothetical protein | Unknown | 1.565 | 0.0002 | 1.566 | 0.0043 | 1.571 | 0.0106 | 8.140 | 9.504 | 5.546e-02 | 1.857e-01 | 1.3640 | -5.380 | 1.159e-02 | 3.118e-01 | 526.40 | 0.3484 | 4.492 | 0.0000 | 0.3339 | 1.583 | 0.3346 | 595.73 | 0.0000 | 1.000e+00 | 0.0000 | 9.035 | 13.210 | 0.0003 | 8.848 | -5.103 | 0.3389 | 0.0003 | 1.064e-02 | 1.673e-04 | 4.302e-03 | 3.118e-01 | 1.580 | 6.601e-04 | 4.177e-04 | 2.077e-04 | 3.101e-08 | 2.050 | 0.0077 | 2.083 | 0.0363 | 1.3060 | 0.4289 | 23.98 | 27.96 | 7.248e-01 | 9.279e-03 | 3.979 | -7.610 | 1.567e-02 | 2.712e-01 | 1.401e+08 | 0.6506 | 3.151 | 0.0016 | 0.2846 | 1.8131 | 0.2848 | 1.174e+08 | 0.7299 | 2.701e-01 | 0.7299 | 7.086 | 8.022 | 0.0046 | 7.0810 | -1.3160 | -5.5810 | 0.2218 | 4.289e-01 | 1.413e-02 | 3.630e-02 | 2.712e-01 | 10.430 | 2.099e+02 | 2.013e+01 | 7.602e-02 | 1.594e-02 |
405 | Rv2301 | Mtb_R24 | 2573015 | 2573707 | 693 | + | artemis | gene | undefined | undefined | Rv2301 | Rv2301 | cut2 | cutinase | CDS | 1.499 | 0.0237 | 1.517 | 0.0258 | 1.486 | 0.0624 | 7.569 | 9.726 | 8.359e-01 | 3.124e-01 | 2.1570 | -2.443 | 8.420e-02 | 4.197e-01 | 481.40 | 0.5101 | 2.939 | 0.0033 | 0.3389 | 1.561 | 0.3398 | 529.44 | 0.3472 | 6.528e-01 | 0.3472 | 8.908 | 8.858 | 0.0029 | 8.671 | -3.226 | -2.8450 | 0.0080 | 6.235e-02 | 2.430e-02 | 2.580e-02 | 4.197e-01 | 1.516 | 2.831e-04 | 1.868e-04 | 4.747e-03 | 8.098e-06 | 1.321 | 0.1437 | 1.364 | 0.2279 | 1.3530 | 0.2613 | 26.93 | 29.89 | 7.308e-01 | 4.516e-02 | 2.965 | -5.746 | 2.206e-02 | 2.948e-01 | 5.651e+08 | 0.6918 | 1.909 | 0.0563 | 0.4672 | 1.0978 | 0.4673 | 5.719e+08 | 0.6821 | 3.179e-01 | 0.6821 | 9.103 | 3.585 | 0.0583 | 10.0500 | -2.0300 | -5.0910 | 0.0741 | 2.613e-01 | 2.654e-01 | 2.279e-01 | 2.947e-01 | 10.010 | 2.247e+02 | 2.244e+01 | 6.289e-02 | 9.528e-05 |
414 | Rv2376c | Mtb_R24 | 2655609 | 2656115 | 507 | - | artemis | gene | undefined | undefined | Rv2376c | Rv2376c | cfp2 | low molecular weight protein antigen | CDS | 3.079 | 0.0052 | 3.063 | 0.0340 | 3.062 | 0.0707 | 12.280 | 16.310 | 2.084e+00 | 6.481e+00 | 4.0300 | -1.611 | 2.007e-01 | 5.043e-01 | 43070.00 | 0.8779 | 3.508 | 0.0005 | 0.1211 | 3.046 | 0.1211 | 32472.56 | 0.3348 | 6.652e-01 | 0.3348 | 15.390 | 8.087 | 0.0045 | 14.300 | -3.095 | -3.0230 | 0.0101 | 7.070e-02 | 5.347e-03 | 3.397e-02 | 5.043e-01 | 3.129 | 1.011e-02 | 3.232e-03 | 5.013e-03 | 2.365e-05 | -1.630 | 0.0325 | 2.534 | 0.0998 | 3.0240 | 0.0003 | 31.30 | 36.08 | 8.686e-01 | 7.910e-02 | 4.783 | -7.694 | 1.007e-02 | 2.297e-01 | 2.750e+09 | 0.6248 | -2.608 | 0.0091 | 0.2082 | 2.2638 | 0.2082 | 3.033e+10 | 0.9352 | 6.479e-02 | 0.9352 | 15.380 | 5.592 | 0.0180 | 15.5600 | -11.0100 | 4.6310 | 0.0000 | 2.575e-04 | 6.001e-02 | 9.981e-02 | 2.298e-01 | 10.030 | 2.751e+02 | 2.744e+01 | 9.050e-03 | 8.143e-05 |
436 | Rv2477c | Mtb_R24 | 2782366 | 2784042 | 1677 | - | artemis | gene | undefined | undefined | Rv2477c | Rv2477c | Rv2477c | macrolide-transport ATP-binding protein ABC transporter | Thought to be involved in active transport of macrolide across the membrane (export): macrolide antibiotics resistance by an export mechanism. Responsible for energy coupling to the transport system. | 2.412 | 0.0005 | 2.403 | 0.0008 | 2.225 | 0.0275 | 3.665 | 5.933 | 7.501e-01 | 1.290e+00 | 2.2690 | -2.816 | 5.191e-02 | 3.374e-01 | 64.12 | 0.5693 | 4.236 | 0.0000 | 0.1835 | 2.446 | 0.1926 | 51.42 | 0.0625 | 9.375e-01 | 0.0625 | 6.042 | 17.270 | 0.0000 | 5.522 | -4.129 | -1.0830 | 0.0017 | 2.753e-02 | 4.718e-04 | 8.453e-04 | 3.374e-01 | 2.408 | 5.333e-06 | 2.215e-06 | 5.711e-04 | 8.861e-07 | 3.526 | 1.0000 | 3.151 | 0.0131 | 3.2750 | 0.1808 | 20.96 | 25.04 | 2.362e+00 | 1.253e+01 | 4.077 | -2.331 | 1.107e-01 | 4.999e-01 | 6.384e+07 | 0.8900 | 3.962 | 1.0000 | 0.1987 | 2.3313 | 0.1995 | 3.557e+07 | 0.3153 | 6.847e-01 | 0.3153 | 5.721 | 10.300 | 0.0013 | 6.5610 | -2.5290 | -3.6550 | 0.0332 | 1.808e-01 | 1.000e+00 | 1.309e-02 | 4.998e-01 | 11.930 | 2.212e+02 | 1.855e+01 | 3.448e-01 | 3.222e-01 |
514 | Rv3001c | Mtb_R24 | 3359585 | 3360586 | 1002 | - | artemis | gene | undefined | undefined | Rv3001c | Rv3001c | ilvC | ketol-acid reductoisomerase | Involved in valine and isoleucine biosynthesis (at the second step) [catalytic activity: (R)-2,3-dihydroxy-3-methylbutanoate NADP( ) = (S)-2-hydroxy-2-methyl-3-oxobutanoate NADPH]. | 1.806 | 0.0522 | 1.791 | 0.0496 | 1.204 | 0.2682 | 4.058 | 5.035 | 3.796e-01 | 3.029e+00 | 0.9770 | -1.188 | 3.355e-01 | 6.208e-01 | 48.75 | 0.6974 | 2.590 | 0.0096 | 0.2836 | 1.818 | 0.2929 | 47.71 | 0.6138 | 3.862e-01 | 0.6138 | 5.653 | 7.118 | 0.0076 | 5.181 | -1.791 | -5.0170 | 0.1007 | 2.681e-01 | 5.354e-02 | 4.961e-02 | 6.207e-01 | 1.610 | 1.029e-01 | 6.392e-02 | 3.931e-02 | 2.827e-03 | 3.424 | 1.0000 | 2.994 | 0.0416 | 2.7020 | 0.2648 | 21.23 | 24.17 | 1.830e+00 | 1.597e+01 | 2.946 | -1.873 | 1.780e-01 | 5.188e-01 | 5.078e+07 | 0.9886 | 3.463 | 1.0000 | 0.2369 | 2.0775 | 0.2379 | 3.046e+07 | 0.3278 | 6.722e-01 | 0.3278 | 5.314 | 7.711 | 0.0055 | 6.0770 | -1.9760 | -4.4530 | 0.0808 | 2.648e-01 | 1.000e+00 | 4.163e-02 | 5.188e-01 | 11.740 | 2.187e+02 | 1.863e+01 | 3.621e-01 | 3.066e-01 |
541 | Rv3194c | Mtb_R24 | 3563264 | 3564286 | 1023 | - | artemis | gene | undefined | undefined | Rv3194c | Rv3194c | Rv3194c | conserved secreted protein | Function unknown | 2.891 | 0.0000 | 2.875 | 0.0000 | 2.913 | 0.0059 | 2.602 | 5.332 | 6.047e-01 | 6.239e-01 | 2.7300 | -4.494 | 1.087e-02 | 3.118e-01 | 29.77 | 0.5771 | 5.009 | 0.0000 | 0.1303 | 2.940 | 0.1453 | 31.39 | 0.0002 | 9.998e-01 | 0.0002 | 4.974 | 24.570 | 0.0000 | 4.383 | -5.711 | 1.4130 | 0.0001 | 5.913e-03 | 1.728e-05 | 2.796e-05 | 3.118e-01 | 2.947 | 1.229e-02 | 4.170e-03 | 4.485e-05 | 5.867e-09 | 8.481 | 0.0038 | 8.450 | 0.0001 | 12.5500 | 0.1299 | 0.00 | 23.79 | 7.890e+01 | 2.365e+00 | 23.790 | -3.752 | 5.870e-02 | 4.280e-01 | 6.902e+06 | 2.5180 | 3.368 | 0.0008 | 0.0039 | 7.9871 | 0.0091 | 5.852e+06 | 0.0000 | 0.000e+00 | 0.0000 | 2.672 | 20.960 | 0.0000 | -1.8180 | -2.9850 | -3.1970 | 0.0160 | 1.299e-01 | 7.106e-03 | 1.224e-04 | 4.280e-01 | 16.500 | 1.932e+02 | 1.171e+01 | 5.570e-03 | 8.095e-05 |
549 | Rv3237c | Mtb_R24 | 3613121 | 3613603 | 483 | - | artemis | gene | undefined | undefined | Rv3237c | Rv3237c | Rv3237c | conserved hypothetical protein | Function unknown | 1.829 | 0.0012 | 1.826 | 0.0055 | 1.690 | 0.0346 | 4.287 | 5.878 | 2.225e-01 | 3.996e-01 | 1.5910 | -3.937 | 1.975e-02 | 3.118e-01 | 50.84 | 0.4646 | 3.936 | 0.0001 | 0.2762 | 1.856 | 0.2865 | 42.81 | 0.0000 | 1.000e+00 | 0.0000 | 5.719 | 12.570 | 0.0004 | 5.424 | -3.900 | -1.4790 | 0.0025 | 3.460e-02 | 1.276e-03 | 5.537e-03 | 3.118e-01 | 1.794 | 3.497e-03 | 1.949e-03 | 9.761e-04 | 1.660e-06 | 3.641 | 0.3759 | 3.131 | 0.6001 | 13.2900 | 0.1299 | 0.00 | 20.36 | 1.452e+02 | 2.011e+01 | 20.360 | -2.147 | 1.371e-01 | 5.188e-01 | 8.668e+06 | 2.8810 | 1.264 | 0.2063 | 0.2203 | 2.1823 | 0.2287 | 3.428e+06 | 0.2294 | 7.706e-01 | 0.2294 | 2.825 | 1.234 | 0.2667 | -1.7850 | -3.0440 | -3.1810 | 0.0145 | 1.299e-01 | 6.943e-01 | 6.002e-01 | 5.188e-01 | 13.150 | 2.856e+02 | 2.172e+01 | 1.625e-01 | 1.734e-02 |
582 | Rv3459c | Mtb_R24 | 3879273 | 3879692 | 420 | - | artemis | gene | undefined | undefined | Rv3459c | Rv3459c | rpsK | 30S ribosomal protein S11 | S11 plays an essential role for the selection of the correct tRNA in protein biosynthesis. It is located on the large lobe of the small subunit. | 1.503 | 0.0032 | 1.502 | 0.0179 | 1.459 | 0.0435 | 4.608 | 6.265 | 5.838e-02 | 3.609e-01 | 1.6570 | -3.903 | 3.772e-02 | 3.248e-01 | 38.71 | 0.4107 | 3.661 | 0.0003 | 0.3535 | 1.500 | 0.3628 | 45.05 | 0.0000 | 1.000e+00 | 0.0000 | 5.334 | 9.788 | 0.0018 | 5.046 | -3.668 | -1.8850 | 0.0037 | 4.349e-02 | 3.269e-03 | 1.791e-02 | 3.248e-01 | 1.509 | 1.470e-04 | 9.738e-05 | 1.894e-03 | 2.941e-06 | 1.369 | 0.1024 | 1.056 | 0.6680 | 0.9426 | 0.4246 | 22.24 | 23.71 | 8.699e-02 | 8.847e+00 | 1.467 | -1.774 | 2.157e-01 | 5.188e-01 | 1.857e+07 | 0.6565 | 2.086 | 0.0370 | 0.7889 | 0.3421 | 0.7896 | 1.571e+07 | 0.6504 | 3.496e-01 | 0.6504 | 3.984 | 0.780 | 0.3771 | 5.3160 | -1.3270 | -5.2200 | 0.2183 | 4.247e-01 | 1.892e-01 | 6.680e-01 | 5.188e-01 | 8.675 | 1.673e+02 | 1.928e+01 | 2.108e-01 | 2.896e-02 |
586 | Rv3484 | Mtb_R24 | 3903078 | 3904616 | 1539 | + | artemis | gene | undefined | undefined | Rv3484 | Rv3484 | cpsA | hypothetical protein | Unknown | 1.914 | 0.0000 | 1.915 | 0.0004 | 1.773 | 0.0157 | 6.068 | 7.806 | 3.225e-01 | 4.045e-01 | 1.7380 | -3.856 | 1.865e-02 | 3.118e-01 | 131.20 | 0.3873 | 4.941 | 0.0000 | 0.2627 | 1.929 | 0.2660 | 137.13 | 0.0000 | 1.000e+00 | 0.0000 | 7.049 | 18.870 | 0.0000 | 6.834 | -4.775 | -0.1039 | 0.0006 | 1.570e-02 | 2.329e-05 | 3.876e-04 | 3.118e-01 | 1.864 | 8.351e-03 | 4.481e-03 | 1.941e-04 | 1.047e-07 | 2.220 | 0.0001 | 2.231 | 0.0436 | 1.6910 | 0.2643 | 23.06 | 26.78 | 1.178e-01 | 3.880e-01 | 3.724 | -9.939 | 1.852e-03 | 1.185e-01 | 6.512e+07 | 0.5103 | 4.351 | 0.0000 | 0.2623 | 1.9305 | 0.2629 | 5.031e+07 | 0.7036 | 2.964e-01 | 0.7036 | 5.967 | 7.603 | 0.0058 | 6.8770 | -1.9900 | -4.5090 | 0.0790 | 2.643e-01 | 1.657e-04 | 4.356e-02 | 1.186e-01 | 10.830 | 2.222e+02 | 2.051e+01 | 2.829e-02 | 1.939e-03 |
591 | Rv3520c | Mtb_R24 | 3956325 | 3957368 | 1044 | - | artemis | gene | undefined | undefined | Rv3520c | Rv3520c | Rv3520c | coenzyme F420-dependent oxidoreductase | Function unknown; probably involved in cellular metabolism. | 2.621 | 0.0000 | 2.631 | 0.0001 | 2.702 | 0.0059 | 3.274 | 6.975 | 1.304e+00 | 3.021e-01 | 3.7010 | -3.895 | 3.231e-02 | 3.118e-01 | 70.97 | 0.5085 | 5.155 | 0.0000 | 0.1561 | 2.680 | 0.1636 | 62.45 | 0.0000 | 1.000e+00 | 0.0000 | 6.186 | 23.290 | 0.0000 | 5.684 | -5.761 | 1.4650 | 0.0001 | 5.913e-03 | 9.544e-06 | 5.120e-05 | 3.118e-01 | 2.668 | 5.376e-03 | 2.015e-03 | 4.185e-05 | 5.050e-09 | 1.572 | 0.0443 | 1.263 | 0.4518 | 1.3430 | 0.2846 | 22.56 | 24.80 | 4.084e-01 | 8.661e+00 | 2.240 | -1.904 | 1.862e-01 | 5.188e-01 | 3.533e+07 | 0.6335 | 2.482 | 0.0130 | 0.6743 | 0.5684 | 0.6750 | 2.585e+07 | 0.6578 | 3.422e-01 | 0.6578 | 4.932 | 1.901 | 0.1680 | 6.2660 | -1.8040 | -4.7430 | 0.1060 | 2.847e-01 | 8.178e-02 | 4.517e-01 | 5.188e-01 | 10.040 | 2.232e+02 | 2.223e+01 | 9.568e-02 | 6.082e-03 |
597 | Rv3583c | Mtb_R24 | 4025056 | 4025544 | 489 | - | artemis | gene | undefined | undefined | Rv3583c | Rv3583c | Rv3583c | transcriptional regulator | Involved in transcriptional mechanism. | 2.731 | 0.0000 | 2.743 | 0.0000 | 2.688 | 0.0025 | 4.007 | 7.510 | 7.557e-01 | 9.109e-02 | 3.5030 | -5.351 | 2.050e-02 | 3.118e-01 | 114.00 | 0.4275 | 6.387 | 0.0000 | 0.1457 | 2.779 | 0.1507 | 94.98 | 0.0000 | 1.000e+00 | 0.0000 | 6.856 | 32.560 | 0.0000 | 6.401 | -6.676 | 2.7180 | 0.0000 | 2.503e-03 | 1.404e-08 | 1.098e-06 | 3.118e-01 | 2.741 | 1.408e-05 | 5.138e-06 | 1.133e-05 | 3.847e-10 | 1.750 | 0.0000 | 1.643 | 0.0809 | 0.9757 | 0.2710 | 23.22 | 26.64 | 4.765e-01 | 2.956e+00 | 3.416 | -3.619 | 4.495e-02 | 3.891e-01 | 8.411e+07 | 0.2555 | 6.848 | 0.0000 | 0.4272 | 1.2269 | 0.4277 | 5.581e+07 | 0.7396 | 2.604e-01 | 0.7396 | 6.293 | 6.144 | 0.0132 | 7.1740 | -1.8770 | -4.7980 | 0.0945 | 2.710e-01 | 1.180e-10 | 8.086e-02 | 3.892e-01 | 9.367 | 1.767e+02 | 1.886e+01 | 3.589e-02 | 2.619e-03 |
606 | Rv3627c | Mtb_R24 | 4065900 | 4067285 | 1386 | - | artemis | gene | undefined | undefined | Rv3627c | Rv3627c | Rv3627c | conserved hypothetical protein | Function unknown (possibly involved in cell wall biosynthesis). | 2.859 | 0.0000 | 2.852 | 0.0000 | 2.726 | 0.0045 | 4.226 | 6.634 | 2.400e-01 | 3.649e-01 | 2.4080 | -6.299 | 3.731e-03 | 2.873e-01 | 67.65 | 0.4602 | 6.213 | 0.0000 | 0.1355 | 2.884 | 0.1425 | 67.64 | 0.0000 | 1.000e+00 | 0.0000 | 6.114 | 30.260 | 0.0000 | 5.621 | -6.169 | 2.0400 | 0.0001 | 4.490e-03 | 2.773e-08 | 2.788e-06 | 2.873e-01 | 2.832 | 1.704e-03 | 6.018e-04 | 2.289e-05 | 1.570e-09 | 1.654 | 0.0021 | 1.553 | 0.5303 | 0.5826 | 0.7456 | 21.16 | 24.30 | 6.880e-01 | 2.829e+00 | 3.149 | -3.518 | 4.070e-02 | 3.758e-01 | 1.502e+07 | 0.4679 | 3.536 | 0.0004 | 0.4523 | 1.1447 | 0.4543 | 1.218e+07 | 0.6602 | 3.398e-01 | 0.6602 | 3.802 | 1.506 | 0.2198 | 4.1020 | -0.6315 | -5.6570 | 0.5440 | 7.456e-01 | 3.951e-03 | 5.303e-01 | 3.759e-01 | 3.498 | 1.066e+01 | 3.049e+00 | 2.547e-01 | 7.479e-02 |
642 | Rv3879c | Mtb_R24 | 4357593 | 4359782 | 2190 | - | artemis | gene | undefined | undefined | Rv3879c | Rv3879c | Rv3879c | hypothetical alanine and proline rich protein | Unknown | 1.255 | 0.0225 | 1.279 | 0.0382 | 1.249 | 0.0619 | 7.523 | 8.620 | 5.198e-01 | 1.848e-01 | 1.0970 | -2.571 | 7.580e-02 | 3.997e-01 | 361.50 | 0.4242 | 2.958 | 0.0031 | 0.4064 | 1.299 | 0.4077 | 303.58 | 0.0882 | 9.118e-01 | 0.0882 | 8.506 | 7.773 | 0.0053 | 8.349 | -3.245 | -2.7770 | 0.0078 | 6.191e-02 | 2.309e-02 | 3.822e-02 | 3.996e-01 | 1.282 | 7.053e-04 | 5.500e-04 | 5.384e-03 | 5.413e-06 | 2.032 | 0.0023 | 2.050 | 0.0185 | 2.3110 | 0.0663 | 25.29 | 29.36 | 7.199e-01 | 9.995e-02 | 4.062 | -7.336 | 8.937e-03 | 2.259e-01 | 3.757e+08 | 0.5784 | 3.513 | 0.0004 | 0.2917 | 1.7775 | 0.2918 | 3.135e+08 | 0.7899 | 2.101e-01 | 0.7899 | 8.505 | 9.506 | 0.0020 | 9.4660 | -4.1480 | -1.6120 | 0.0027 | 6.629e-02 | 4.274e-03 | 1.846e-02 | 2.259e-01 | 10.860 | 2.333e+02 | 2.148e+01 | 1.729e-03 | 1.344e-06 |
favorite_idx <- merged_table[["edger_logfc.x"]] <= -1 &
merged_table[["edger_logfc.y"]] <= -1 &
merged_table[["edger_adjp.x"]] <= 0.05
favorites <- merged_table[favorite_idx, ]
write.csv(x=favorites, file="conservative_decreased_delta_filtrate.csv")
knitr::kable(favorites)
Row.names | seqnames | start | end | width | strand | source | type | score | phase | id | locustag | gene | description | function. | deseq_logfc.x | deseq_adjp.x | edger_logfc.x | edger_adjp.x | limma_logfc.x | limma_adjp.x | basic_nummed.x | basic_denmed.x | basic_numvar.x | basic_denvar.x | basic_logfc.x | basic_t.x | basic_p.x | basic_adjp.x | deseq_basemean.x | deseq_lfcse.x | deseq_stat.x | deseq_p.x | ebseq_fc.x | ebseq_logfc.x | ebseq_postfc.x | ebseq_mean.x | ebseq_ppee.x | ebseq_ppde.x | ebseq_adjp.x | edger_logcpm.x | edger_lr.x | edger_p.x | limma_ave.x | limma_t.x | limma_b.x | limma_p.x | limma_adjp_fdr.x | deseq_adjp_fdr.x | edger_adjp_fdr.x | basic_adjp_fdr.x | lfc_meta.x | lfc_var.x | lfc_varbymed.x | p_meta.x | p_var.x | deseq_logfc.y | deseq_adjp.y | edger_logfc.y | edger_adjp.y | limma_logfc.y | limma_adjp.y | basic_nummed.y | basic_denmed.y | basic_numvar.y | basic_denvar.y | basic_logfc.y | basic_t.y | basic_p.y | basic_adjp.y | deseq_basemean.y | deseq_lfcse.y | deseq_stat.y | deseq_p.y | ebseq_fc.y | ebseq_logfc.y | ebseq_postfc.y | ebseq_mean.y | ebseq_ppee.y | ebseq_ppde.y | ebseq_adjp.y | edger_logcpm.y | edger_lr.y | edger_p.y | limma_ave.y | limma_t.y | limma_b.y | limma_p.y | limma_adjp_fdr.y | deseq_adjp_fdr.y | edger_adjp_fdr.y | basic_adjp_fdr.y | lfc_meta.y | lfc_var.y | lfc_varbymed.y | p_meta.y | p_var.y | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
37 | Rv0203 | Mtb_R24 | 241514 | 241924 | 411 | + | artemis | gene | undefined | undefined | Rv0203 | Rv0203 | Rv0203 | hypothetical exported protein | Unknown | -1.740 | 0.0000 | -1.734 | 0.0004 | -1.370 | 0.0103 | 12.310 | 10.300 | 2.518e-02 | 1.683e-01 | -2.0120 | 7.058 | 9.364e-03 | 3.118e-01 | 2493.00 | 0.2745 | -6.339 | 0.0000 | 3.285 | -1.716 | 3.284 | 3229.43 | 0.0000 | 1.000e+00 | 0.0000 | 11.270 | 19.140 | 0.0000 | 10.830 | 5.157 | 0.4089 | 0.0003 | 1.026e-02 | 1.537e-08 | 3.659e-04 | 3.118e-01 | -1.579 | 7.505e-02 | -4.754e-02 | 1.072e-04 | 3.071e-08 | -2.9840 | 0.0002 | -2.926 | 0.0018 | -3.8080 | 0.1356 | 28.38 | 26.81 | 1.050e-01 | 1.177e-01 | -1.5720 | 5.2890 | 6.188e-03 | 2.064e-01 | 3.442e+08 | 0.7139 | -4.1790 | 0.0000 | 9.265 | -3.212 | 9.260 | 5.155e+08 | 0.0000 | 1.000e+00 | 0.0000 | 8.363 | 14.8400 | 0.0001 | 8.374 | 2.8890 | -3.2640 | 0.0186 | 1.356e-01 | 3.403e-04 | 1.804e-03 | 2.064e-01 | -2.0620 | 2.611e+00 | -1.266e+00 | 6.242e-03 | 1.142e-04 |
58 | Rv0288 | Mtb_R24 | 351848 | 352138 | 291 | + | artemis | gene | undefined | undefined | Rv0288 | Rv0288 | esxH | low molecular weight protein antigen 7 | CDS | -4.142 | 0.0000 | -4.131 | 0.0000 | -3.695 | 0.0008 | 13.270 | 9.015 | 1.115e-01 | 1.201e-01 | -4.2500 | 15.190 | 1.106e-04 | 7.336e-02 | 3470.00 | 0.4798 | -8.632 | 0.0000 | 17.253 | -4.109 | 17.224 | 5056.95 | 0.0000 | 1.000e+00 | 0.0000 | 11.750 | 54.020 | 0.0000 | 9.602 | 8.198 | 4.5740 | 0.0000 | 8.289e-04 | 9.970e-16 | 6.564e-11 | 7.333e-02 | -4.102 | 3.605e-03 | -8.790e-04 | 1.667e-06 | 8.337e-12 | -6.0110 | 0.0000 | -5.964 | 0.0000 | -11.9300 | 0.2601 | 27.31 | 23.20 | 4.284e-01 | 1.691e-01 | -4.1080 | 9.2890 | 1.632e-03 | 1.160e-01 | 1.357e+08 | 0.8283 | -7.2570 | 0.0000 | 77.034 | -6.267 | 76.252 | 2.286e+08 | 0.0000 | 1.000e+00 | 0.0000 | 7.008 | 35.9900 | 0.0000 | 3.256 | 2.1300 | -3.8650 | 0.0631 | 2.601e-01 | 6.494e-12 | 1.088e-07 | 1.160e-01 | -4.8100 | 4.161e+00 | -8.650e-01 | 2.105e-02 | 1.329e-03 |
76 | Rv0397A | undefined | undefined | undefined | undefined | undefined | undefined | undefined | undefined | undefined | undefined | undefined | undefined | undefined | undefined | -4.053 | 1.0000 | -4.012 | 0.0022 | -2.149 | 0.2556 | 6.778 | 5.850 | 9.813e+00 | 2.857e-02 | -0.9271 | 1.207 | 3.501e-01 | 6.301e-01 | 365.40 | 1.3170 | -3.078 | 1.0000 | 15.720 | -3.974 | 15.486 | 503.93 | 0.0000 | 0.000e+00 | 0.0000 | 8.480 | 14.810 | 0.0001 | 6.188 | 1.849 | -5.0610 | 0.0914 | 2.556e-01 | 1.000e+00 | 2.188e-03 | 6.301e-01 | -3.447 | 1.030e+00 | -2.987e-01 | 3.638e-01 | 3.056e-01 | -1.8420 | 0.0350 | -1.988 | 0.1135 | -1.5290 | 0.2648 | 31.22 | 30.68 | 1.786e-01 | 4.490e-03 | -0.5449 | 1.5440 | 2.567e-01 | 5.188e-01 | 2.342e+09 | 0.7146 | -2.5780 | 0.0099 | 4.831 | -2.272 | 4.831 | 3.562e+09 | 0.0000 | 1.000e+00 | 0.0000 | 11.260 | 5.2840 | 0.0215 | 11.850 | 1.9680 | -5.5690 | 0.0818 | 2.648e-01 | 6.460e-02 | 1.135e-01 | 5.188e-01 | -1.0470 | 2.258e+00 | -2.156e+00 | 3.776e-02 | 1.490e-03 |
218 | Rv1174c | Mtb_R24 | 1305669 | 1306001 | 333 | - | artemis | gene | undefined | undefined | Rv1174c | Rv1174c | TB8.4 | low molecular weight T-cell antigen | Unknown function (secreted protein) | -4.715 | 0.0000 | -4.700 | 0.0000 | -4.965 | 0.0002 | 16.800 | 11.840 | 5.686e-02 | 2.252e-01 | -4.9580 | 15.830 | 6.024e-04 | 1.997e-01 | 40910.00 | 0.4377 | -10.770 | 0.0000 | 25.527 | -4.674 | 25.522 | 58062.68 | 0.0000 | 1.000e+00 | 0.0000 | 15.300 | 29.260 | 0.0000 | 13.770 | 10.070 | 6.5010 | 0.0000 | 2.179e-04 | 3.085e-24 | 4.203e-06 | 1.997e-01 | -4.708 | 0.000e+00 | 0.000e+00 | 2.402e-07 | 1.315e-13 | -2.8120 | 0.0001 | -4.834 | 0.0001 | -5.6870 | 0.0006 | 32.96 | 29.76 | 4.472e-02 | 2.252e-02 | -3.2010 | 21.9600 | 5.678e-05 | 4.981e-02 | 2.184e+09 | 0.6574 | -4.2770 | 0.0000 | 34.803 | -5.121 | 34.800 | 1.242e+10 | 0.0000 | 1.000e+00 | 0.0000 | 12.820 | 20.8300 | 0.0000 | 11.730 | 9.6350 | 4.4350 | 0.0000 | 5.943e-04 | 2.266e-04 | 1.295e-04 | 4.981e-02 | -2.7360 | 3.787e+00 | -1.384e+00 | 1.009e-05 | 5.913e-11 |
245 | Rv1311 | Mtb_R24 | 1467315 | 1467680 | 366 | + | artemis | gene | undefined | undefined | Rv1311 | Rv1311 | atpC | ATP synthase epsilon chain | Produces ATP from ADP in the presence of a proton gradient across the membrane [catalytic activity: ATP H(2)O H( )(in) = ADP phosphate H( )(out)] | -1.829 | 0.0005 | -1.810 | 0.0030 | -1.892 | 0.0157 | 9.900 | 8.083 | 1.474e-02 | 4.552e-01 | -1.8170 | 5.044 | 3.259e-02 | 3.118e-01 | 501.60 | 0.4360 | -4.195 | 0.0000 | 3.471 | -1.795 | 3.462 | 584.20 | 0.0000 | 1.000e+00 | 0.0000 | 8.966 | 14.070 | 0.0002 | 8.658 | 4.725 | -0.2664 | 0.0006 | 1.570e-02 | 5.166e-04 | 2.987e-03 | 3.118e-01 | -1.776 | 5.677e-03 | -3.196e-03 | 2.729e-04 | 9.361e-08 | -1.8530 | 0.0000 | -1.900 | 0.0101 | -2.6830 | 0.0453 | 26.81 | 26.43 | 6.281e-02 | 1.759e+00 | -0.3822 | -0.2826 | 8.025e-01 | 8.647e-01 | 1.498e+08 | 0.2878 | -6.4410 | 0.0000 | 4.837 | -2.274 | 4.833 | 1.892e+08 | 0.0000 | 1.000e+00 | 0.0000 | 7.154 | 10.9600 | 0.0009 | 7.780 | 4.5130 | -0.8926 | 0.0016 | 4.534e-02 | 1.818e-09 | 1.013e-02 | 8.647e-01 | -1.2010 | 1.422e+00 | -1.185e+00 | 8.445e-04 | 6.473e-07 |
260 | Rv1390 | Mtb_R24 | 1565093 | 1565425 | 333 | + | artemis | gene | undefined | undefined | Rv1390 | Rv1390 | rpoZ | DNA-directed RNA polymerase omega chain | Promotes RNA polymerase assembly. Latches the N-and C-terminal regions of the beta’ subunit thereby faciltating its interaction with the beta and alpha subunits [catalytic activity: N nucleoside triphosphate = N diphosphate {RNA}N]. | -1.330 | 0.0073 | -1.325 | 0.0211 | -1.398 | 0.0457 | 7.948 | 6.293 | 7.131e-03 | 2.681e-01 | -1.6550 | 4.589 | 4.018e-02 | 3.253e-01 | 145.50 | 0.3928 | -3.385 | 0.0007 | 2.478 | -1.309 | 2.463 | 166.81 | 0.0000 | 1.000e+00 | 0.0000 | 7.191 | 9.352 | 0.0022 | 6.992 | 3.593 | -2.1220 | 0.0042 | 4.569e-02 | 7.489e-03 | 2.110e-02 | 3.253e-01 | -1.311 | 8.168e-04 | -6.230e-04 | 2.375e-03 | 3.032e-06 | -1.2740 | 0.0077 | -1.317 | 0.2774 | -1.5580 | 0.2710 | 25.54 | 25.62 | 4.953e-02 | 1.613e+00 | 0.0766 | -1.0730 | 3.901e-01 | 5.188e-01 | 6.637e+07 | 0.4049 | -3.1460 | 0.0017 | 3.209 | -1.682 | 3.206 | 7.964e+07 | 0.0000 | 1.000e+00 | 0.0000 | 5.979 | 3.1080 | 0.0779 | 6.131 | 1.8840 | -4.6590 | 0.0935 | 2.710e-01 | 1.425e-02 | 2.774e-01 | 5.188e-01 | -0.6444 | 1.267e+00 | -1.965e+00 | 5.767e-02 | 2.414e-03 |
265 | Rv1411c | Mtb_R24 | 1587772 | 1588482 | 711 | - | artemis | gene | undefined | undefined | Rv1411c | Rv1411c | lprG | lipoprotein | CDS | -1.901 | 0.0019 | -1.878 | 0.0038 | -1.970 | 0.0238 | 7.992 | 5.978 | 3.916e-01 | 5.469e-01 | -2.0130 | 3.628 | 2.326e-02 | 3.118e-01 | 134.80 | 0.4995 | -3.805 | 0.0001 | 3.635 | -1.862 | 3.598 | 154.99 | 0.0000 | 1.000e+00 | 0.0000 | 7.084 | 13.490 | 0.0002 | 6.742 | 4.287 | -0.9120 | 0.0013 | 2.381e-02 | 1.996e-03 | 3.795e-03 | 3.118e-01 | -1.839 | 7.752e-03 | -4.216e-03 | 5.500e-04 | 3.891e-07 | -2.1450 | 0.0000 | -2.216 | 0.0126 | -2.4250 | 0.1285 | 25.81 | 25.21 | 1.191e-01 | 2.231e+00 | -0.5950 | 0.0699 | 9.501e-01 | 9.864e-01 | 7.966e+07 | 0.2201 | -9.7470 | 0.0000 | 6.088 | -2.606 | 6.078 | 1.002e+08 | 0.0000 | 1.000e+00 | 0.0000 | 6.244 | 10.3900 | 0.0013 | 6.247 | 3.3780 | -2.3880 | 0.0086 | 1.285e-01 | 5.533e-21 | 1.260e-02 | 9.865e-01 | -1.3830 | 1.961e+00 | -1.418e+00 | 3.286e-03 | 2.153e-05 |
277 | Rv1477 | Mtb_R24 | 1666990 | 1668408 | 1419 | + | artemis | gene | undefined | undefined | Rv1477 | Rv1477 | Rv1477 | invasion-associated protein | Unknown, but supposed involvement in virulence. | -1.541 | 0.0011 | -1.531 | 0.0052 | -1.349 | 0.0287 | 10.750 | 9.190 | 3.780e-02 | 7.502e-03 | -1.5580 | 12.930 | 1.489e-03 | 2.469e-01 | 954.90 | 0.3850 | -4.002 | 0.0001 | 2.853 | -1.512 | 2.850 | 1191.84 | 0.0000 | 1.000e+00 | 0.0000 | 9.891 | 12.710 | 0.0004 | 9.555 | 4.089 | -1.3710 | 0.0018 | 2.870e-02 | 1.096e-03 | 5.241e-03 | 2.468e-01 | -1.440 | 2.736e-02 | -1.899e-02 | 7.338e-04 | 8.357e-07 | -1.1410 | 0.1693 | -1.105 | 0.3820 | -0.7287 | 0.4838 | 29.50 | 30.04 | 7.567e-02 | 1.609e-02 | 0.5475 | -2.9380 | 6.557e-02 | 4.400e-01 | 1.080e+09 | 0.6275 | -1.8190 | 0.0689 | 2.612 | -1.385 | 2.611 | 1.423e+09 | 0.0009 | 9.991e-01 | 0.0009 | 10.020 | 2.3360 | 0.1264 | 10.910 | 1.1900 | -6.4530 | 0.2656 | 4.838e-01 | 3.128e-01 | 3.820e-01 | 4.400e-01 | -0.2437 | 2.333e+00 | -9.574e+00 | 1.536e-01 | 1.023e-02 |
315 | Rv1712 | Mtb_R24 | 1939599 | 1940291 | 693 | + | artemis | gene | undefined | undefined | Rv1712 | Rv1712 | cmk | cytidylate kinase | Catalyzes the transfer of a phosphate group from ATP to either CMP or dCMP to form CDP or dCDP and ADP [catalytic activity: ATP CMP = ADP CDP]. | -1.685 | 0.0120 | -1.683 | 0.0211 | -1.832 | 0.0498 | 6.322 | 4.590 | 2.252e-01 | 1.601e+00 | -1.7320 | 2.415 | 1.096e-01 | 4.456e-01 | 41.77 | 0.5232 | -3.220 | 0.0013 | 3.320 | -1.731 | 3.216 | 44.73 | 0.0225 | 9.775e-01 | 0.0225 | 5.441 | 9.368 | 0.0022 | 5.127 | 3.485 | -2.1900 | 0.0051 | 4.975e-02 | 1.232e-02 | 2.110e-02 | 4.455e-01 | -1.674 | 2.823e-04 | -1.686e-04 | 2.852e-03 | 3.889e-06 | -1.3390 | 0.1904 | -1.614 | 0.5242 | -2.0220 | 0.3211 | 23.07 | 22.79 | 4.283e-01 | 8.370e+00 | -0.2798 | -0.3414 | 7.626e-01 | 8.364e-01 | 1.504e+07 | 0.7671 | -1.7450 | 0.0810 | 4.888 | -2.289 | 4.848 | 1.739e+07 | 0.0001 | 9.999e-01 | 0.0001 | 3.788 | 1.5300 | 0.2161 | 4.724 | 1.6640 | -4.5810 | 0.1318 | 3.212e-01 | 3.517e-01 | 5.242e-01 | 8.364e-01 | -0.8488 | 1.209e+00 | -1.425e+00 | 1.430e-01 | 4.658e-03 |
347 | Rv1910c | Mtb_R24 | 2156706 | 2157299 | 594 | - | artemis | gene | undefined | undefined | Rv1910c | Rv1910c | Rv1910c | hypothetical exported protein | Unknown | -1.282 | 0.0036 | -1.273 | 0.0215 | -0.965 | 0.0823 | 11.950 | 10.560 | 1.229e-01 | 1.873e-01 | -1.3860 | 4.062 | 1.667e-02 | 3.118e-01 | 2225.00 | 0.3544 | -3.618 | 0.0003 | 2.412 | -1.270 | 2.412 | 2906.00 | 0.0535 | 9.465e-01 | 0.0535 | 11.110 | 9.289 | 0.0023 | 10.710 | 3.005 | -3.2740 | 0.0119 | 8.225e-02 | 3.709e-03 | 2.152e-02 | 3.118e-01 | -1.146 | 5.146e-02 | -4.489e-02 | 4.837e-03 | 3.853e-05 | -1.8340 | 0.0077 | -1.802 | 0.0523 | -2.7230 | 0.0858 | 28.96 | 28.87 | 1.226e-01 | 8.045e-02 | -0.0936 | 0.3641 | 7.349e-01 | 8.152e-01 | 6.052e+08 | 0.5831 | -3.1460 | 0.0017 | 4.257 | -2.090 | 4.256 | 8.347e+08 | 0.0000 | 1.000e+00 | 0.0000 | 9.185 | 7.1270 | 0.0076 | 9.560 | 3.8370 | -2.1610 | 0.0043 | 8.584e-02 | 1.425e-02 | 5.233e-02 | 8.151e-01 | -1.1630 | 1.332e+00 | -1.146e+00 | 4.504e-03 | 8.865e-06 |
349 | Rv1926c | Mtb_R24 | 2178957 | 2179436 | 480 | - | artemis | gene | undefined | undefined | Rv1926c | Rv1926c | mpt63 | immunogenic protein | CDS | -2.740 | 0.0000 | -2.738 | 0.0004 | -2.301 | 0.0059 | 15.010 | 12.120 | 3.252e-02 | 7.358e-01 | -2.8950 | 5.641 | 2.472e-02 | 3.118e-01 | 14200.00 | 0.3648 | -7.509 | 0.0000 | 6.625 | -2.728 | 6.624 | 18077.15 | 0.0000 | 1.000e+00 | 0.0000 | 13.780 | 18.880 | 0.0000 | 13.270 | 5.665 | 1.2470 | 0.0001 | 5.913e-03 | 7.892e-12 | 3.876e-04 | 3.118e-01 | -2.739 | 0.000e+00 | 0.000e+00 | 5.222e-05 | 6.189e-09 | -1.6300 | 0.0325 | -2.501 | 0.0596 | -1.8750 | 0.3147 | 33.34 | 32.55 | 3.162e-02 | 4.996e-02 | -0.7930 | 5.2140 | 7.383e-03 | 2.086e-01 | 2.750e+09 | 0.6248 | -2.6080 | 0.0091 | 6.906 | -2.788 | 6.906 | 1.610e+10 | 0.0000 | 1.000e+00 | 0.0000 | 13.380 | 6.8390 | 0.0089 | 13.980 | 1.6900 | -6.4890 | 0.1265 | 3.146e-01 | 6.001e-02 | 5.957e-02 | 2.086e-01 | -1.1730 | 2.185e+00 | -1.863e+00 | 4.817e-02 | 4.602e-03 |
350 | Rv1932 | Mtb_R24 | 2183372 | 2183869 | 498 | + | artemis | gene | undefined | undefined | Rv1932 | Rv1932 | tpx | thiol peroxidase | CDS | -2.289 | 0.0070 | -2.261 | 0.0072 | -2.007 | 0.0908 | 10.380 | 7.725 | 1.836e+00 | 2.041e-01 | -2.6590 | 2.496 | 1.074e-01 | 4.424e-01 | 560.60 | 0.6733 | -3.400 | 0.0007 | 4.740 | -2.245 | 4.724 | 656.94 | 0.1908 | 8.092e-01 | 0.1908 | 9.117 | 11.940 | 0.0005 | 8.504 | 2.870 | -3.4700 | 0.0152 | 9.079e-02 | 7.211e-03 | 7.180e-03 | 4.423e-01 | -2.123 | 6.916e-02 | -3.257e-02 | 5.467e-03 | 7.075e-05 | -1.2140 | 0.0123 | -1.205 | 0.2042 | -0.2484 | 0.7843 | 29.25 | 29.74 | 3.504e-02 | 9.779e-01 | 0.4929 | -1.3470 | 3.026e-01 | 5.188e-01 | 1.013e+09 | 0.4068 | -2.9830 | 0.0029 | 2.908 | -1.540 | 2.907 | 1.117e+09 | 0.0006 | 9.994e-01 | 0.0006 | 9.923 | 3.8610 | 0.0494 | 11.110 | 0.5361 | -7.0430 | 0.6053 | 7.843e-01 | 2.268e-02 | 2.042e-01 | 5.188e-01 | 0.0110 | 4.429e+00 | 4.026e+02 | 2.192e-01 | 1.124e-01 |
396 | Rv2245 | Mtb_R24 | 2518115 | 2519365 | 1251 | + | artemis | gene | undefined | undefined | Rv2245 | Rv2245 | kasA | 3-oxoacyl-[acyl-carrier protein] synthase 1 | Involved in fatty acid biosynthesis (mycolic acids synthesis); involved in meromycolate extension. Catalyzes the condensation reaction of fatty acid synthesis by the addition to an acyl acceptor of two carbons from malonyl-ACP [catalytic activity: acyl-[acyl-carrier protein] malonyl-[acyl-carrier protein] = 3-oxoacyl-[acyl-carrier protein] [acyl-carrier protein] CO(2)]. | -1.503 | 0.0064 | -1.489 | 0.0137 | -1.538 | 0.0335 | 8.907 | 7.481 | 1.076e-01 | 2.628e-01 | -1.4260 | 4.366 | 1.706e-02 | 3.118e-01 | 256.80 | 0.4365 | -3.444 | 0.0006 | 2.801 | -1.486 | 2.791 | 322.92 | 0.0000 | 1.000e+00 | 0.0000 | 7.999 | 10.510 | 0.0012 | 7.598 | 3.944 | -1.5540 | 0.0023 | 3.352e-02 | 6.553e-03 | 1.373e-02 | 3.118e-01 | -1.490 | 1.291e-04 | -8.665e-05 | 1.344e-03 | 7.432e-07 | -1.1030 | 0.1919 | -1.334 | 0.1481 | -0.5823 | 0.7111 | 27.11 | 25.88 | 1.354e-01 | 9.775e+00 | -1.2250 | -0.3442 | 7.627e-01 | 8.364e-01 | 1.651e+08 | 0.6336 | -1.7410 | 0.0817 | 4.263 | -2.092 | 4.261 | 2.084e+08 | 0.0188 | 9.812e-01 | 0.0188 | 7.239 | 4.6360 | 0.0313 | 8.274 | 0.7263 | -6.4040 | 0.4868 | 7.112e-01 | 3.544e-01 | 1.481e-01 | 8.364e-01 | -0.1848 | 3.313e+00 | -1.793e+01 | 1.999e-01 | 6.235e-02 |
412 | Rv2352c | Mtb_R24 | 2632923 | 2634098 | 1176 | - | artemis | gene | undefined | undefined | Rv2352c | Rv2352c | PPE38 | PPE family protein | Function unknown | -4.263 | 0.0000 | -4.242 | 0.0000 | -4.812 | 0.0084 | 10.470 | 6.237 | 7.186e-01 | 7.897e+00 | -4.2330 | 3.111 | 7.250e-02 | 3.997e-01 | 505.80 | 0.8171 | -5.217 | 0.0000 | 18.842 | -4.236 | 18.596 | 693.53 | 0.0000 | 1.000e+00 | 0.0000 | 8.977 | 24.980 | 0.0000 | 7.343 | 5.351 | 0.8000 | 0.0002 | 8.450e-03 | 8.018e-06 | 2.397e-05 | 3.996e-01 | -4.252 | 0.000e+00 | 0.000e+00 | 7.672e-05 | 1.748e-08 | -5.2050 | 0.0000 | -5.245 | 0.0000 | -11.9600 | 0.1299 | 25.03 | 22.11 | 5.773e-01 | 1.900e+00 | -2.9170 | 3.2780 | 4.409e-02 | 3.843e-01 | 4.167e+07 | 0.5566 | -9.3510 | 0.0000 | 49.117 | -5.618 | 48.025 | 6.572e+07 | 0.0000 | 1.000e+00 | 0.0000 | 5.317 | 25.0300 | 0.0000 | 2.628 | 3.1710 | -2.9400 | 0.0119 | 1.299e-01 | 2.043e-19 | 2.037e-05 | 3.843e-01 | -4.3150 | 2.496e+00 | -5.786e-01 | 3.960e-03 | 4.704e-05 |
422 | Rv2431c | Mtb_R24 | 2727967 | 2728266 | 300 | - | artemis | gene | undefined | undefined | Rv2431c | Rv2431c | PE25 | PE family protein | Function unknown | -1.665 | 0.0182 | -1.647 | 0.0168 | -1.461 | 0.1025 | 10.890 | 9.582 | 2.257e-01 | 2.374e-01 | -1.3080 | 4.386 | 1.183e-02 | 3.118e-01 | 1240.00 | 0.5447 | -3.057 | 0.0022 | 3.100 | -1.632 | 3.097 | 1488.41 | 0.0450 | 9.550e-01 | 0.0450 | 10.270 | 9.930 | 0.0016 | 9.859 | 2.729 | -3.7650 | 0.0195 | 1.025e-01 | 1.864e-02 | 1.684e-02 | 3.118e-01 | -1.562 | 2.670e-02 | -1.709e-02 | 7.800e-03 | 1.035e-04 | -1.2910 | 0.3636 | -1.221 | 0.4688 | -4.6610 | 0.2548 | 28.68 | 27.92 | 2.247e-01 | 1.645e+00 | -0.7582 | 0.4894 | 6.637e-01 | 7.494e-01 | 5.253e+08 | 0.9980 | -1.2930 | 0.1960 | 2.788 | -1.479 | 2.788 | 6.650e+08 | 0.0000 | 1.000e+00 | 0.0000 | 8.984 | 1.8160 | 0.1778 | 8.507 | 2.1480 | -4.4020 | 0.0613 | 2.548e-01 | 6.717e-01 | 4.687e-01 | 7.494e-01 | -0.9732 | 2.338e-01 | -2.402e-01 | 1.450e-01 | 5.342e-03 |
506 | Rv2971 | Mtb_R24 | 3326101 | 3326949 | 849 | + | artemis | gene | undefined | undefined | Rv2971 | Rv2971 | Rv2971 | oxidoreductase | Function unknown; probably involved in cellular metabolism. | -1.198 | 0.0121 | -1.190 | 0.0480 | -1.211 | 0.0498 | 9.411 | 8.329 | 9.005e-02 | 1.887e-02 | -1.0820 | 6.495 | 9.095e-03 | 3.118e-01 | 562.50 | 0.3726 | -3.214 | 0.0013 | 2.248 | -1.169 | 2.244 | 545.50 | 0.0063 | 9.937e-01 | 0.0063 | 9.137 | 7.213 | 0.0072 | 8.993 | 3.456 | -2.4450 | 0.0053 | 4.975e-02 | 1.240e-02 | 4.797e-02 | 3.118e-01 | -1.163 | 3.118e-03 | -2.681e-03 | 4.626e-03 | 9.157e-06 | -1.0310 | 0.0000 | -1.156 | 0.0978 | -0.1834 | 0.8755 | 27.84 | 27.89 | 4.201e-02 | 3.650e+00 | 0.0552 | -0.9631 | 4.351e-01 | 5.292e-01 | 3.794e+08 | 0.2275 | -4.5330 | 0.0000 | 3.072 | -1.619 | 3.071 | 3.923e+08 | 0.0000 | 1.000e+00 | 0.0000 | 8.477 | 5.6610 | 0.0174 | 9.803 | 0.3454 | -6.8440 | 0.7380 | 8.756e-01 | 7.278e-05 | 9.778e-02 | 5.292e-01 | 0.1338 | 4.492e+00 | 3.357e+01 | 2.518e-01 | 1.774e-01 |
523 | Rv3044 | Mtb_R24 | 3405136 | 3406215 | 1080 | + | artemis | gene | undefined | undefined | Rv3044 | Rv3044 | fecB | Fe(III)-dicitrate-binding periplasmic lipoprotein | May be involved in active transport of FeIII-decitrate across the membrane (import). | -2.226 | 0.0006 | -2.218 | 0.0015 | -2.139 | 0.0275 | 6.844 | 4.854 | 5.535e-01 | 1.712e-01 | -1.9900 | 4.395 | 1.999e-02 | 3.118e-01 | 94.15 | 0.5382 | -4.136 | 0.0000 | 4.668 | -2.223 | 4.570 | 100.15 | 0.0764 | 9.236e-01 | 0.0764 | 6.583 | 15.750 | 0.0001 | 6.198 | 4.128 | -1.1460 | 0.0017 | 2.753e-02 | 6.320e-04 | 1.464e-03 | 3.118e-01 | -2.222 | 0.000e+00 | 0.000e+00 | 5.895e-04 | 8.614e-07 | -0.9919 | 0.0222 | -1.081 | 0.5054 | -1.0120 | 0.3765 | 24.77 | 24.90 | 1.974e-01 | 2.904e+00 | 0.1231 | -1.1240 | 3.656e-01 | 5.188e-01 | 4.092e+07 | 0.3573 | -2.7760 | 0.0055 | 2.845 | -1.508 | 2.840 | 4.478e+07 | 0.0012 | 9.988e-01 | 0.0012 | 5.266 | 1.6170 | 0.2035 | 6.419 | 1.4830 | -5.1200 | 0.1735 | 3.765e-01 | 4.093e-02 | 5.053e-01 | 5.188e-01 | -0.2868 | 1.626e+00 | -5.671e+00 | 1.275e-01 | 1.139e-02 |
545 | Rv3208A | Mtb_R24 | 3585677 | 3585949 | 273 | - | artemis | gene | undefined | undefined | Rv3208A | Rv3208A | TB9.4 | conserved hypothetical protein | Function unknown | -1.208 | 0.0178 | -1.211 | 0.0309 | -0.991 | 0.0955 | 11.260 | 9.853 | 1.493e-01 | 3.422e-01 | -1.4060 | 3.085 | 4.449e-02 | 3.352e-01 | 1712.00 | 0.3935 | -3.069 | 0.0021 | 2.288 | -1.194 | 2.287 | 1845.15 | 0.2042 | 7.958e-01 | 0.2042 | 10.740 | 8.347 | 0.0039 | 10.580 | 2.821 | -3.6110 | 0.0166 | 9.547e-02 | 1.825e-02 | 3.086e-02 | 3.352e-01 | -1.105 | 3.095e-02 | -2.800e-02 | 7.523e-03 | 6.198e-05 | -1.3170 | 0.0048 | -1.330 | 0.1258 | -0.7288 | 0.4425 | 28.64 | 28.92 | 3.066e-02 | 9.948e-01 | 0.2866 | -1.2220 | 3.399e-01 | 5.188e-01 | 7.618e+08 | 0.3993 | -3.2980 | 0.0010 | 3.184 | -1.671 | 3.184 | 7.879e+08 | 0.0001 | 9.999e-01 | 0.0001 | 9.506 | 5.0280 | 0.0249 | 9.873 | 1.2850 | -6.1950 | 0.2319 | 4.426e-01 | 8.944e-03 | 1.258e-01 | 5.188e-01 | -0.3789 | 2.696e+00 | -7.115e+00 | 8.594e-02 | 1.612e-02 |
567 | Rv3354 | Mtb_R24 | 3769111 | 3769500 | 390 | + | artemis | gene | undefined | undefined | Rv3354 | Rv3354 | Rv3354 | conserved hypothetical protein | Function unknown | -2.585 | 0.0005 | -2.560 | 0.0013 | -2.217 | 0.0447 | 13.070 | 10.120 | 4.208e-01 | 8.844e-01 | -2.9580 | 4.108 | 1.876e-02 | 3.118e-01 | 4468.00 | 0.6087 | -4.247 | 0.0000 | 5.919 | -2.565 | 5.916 | 5869.43 | 0.0208 | 9.792e-01 | 0.0208 | 12.110 | 16.140 | 0.0001 | 11.220 | 3.642 | -2.1260 | 0.0038 | 4.471e-02 | 4.639e-04 | 1.343e-03 | 3.118e-01 | -2.518 | 8.748e-03 | -3.473e-03 | 1.308e-03 | 4.823e-06 | -3.1960 | 0.0001 | -3.147 | 0.0019 | -3.6050 | 0.1390 | 29.67 | 28.12 | 1.380e-02 | 2.851e-02 | -1.5550 | 13.8600 | 3.128e-04 | 6.627e-02 | 8.283e+08 | 0.7509 | -4.2560 | 0.0000 | 10.737 | -3.425 | 10.734 | 1.277e+09 | 0.0000 | 1.000e+00 | 0.0000 | 9.633 | 14.6500 | 0.0001 | 8.752 | 2.8510 | -3.5700 | 0.0198 | 1.390e-01 | 2.451e-04 | 1.943e-03 | 6.627e-02 | -2.1570 | 2.968e+00 | -1.376e+00 | 6.633e-03 | 1.290e-04 |
623 | Rv3763 | Mtb_R24 | 4209047 | 4209526 | 480 | + | artemis | gene | undefined | undefined | Rv3763 | Rv3763 | lpqH | 19 kda lipoprotein antigen precursor | Shown to inhibit gamma interferon regulated HLA-DR protein and mRNA expression in human macrophages | -3.418 | 0.0000 | -3.403 | 0.0000 | -3.289 | 0.0002 | 11.360 | 7.669 | 6.473e-02 | 2.251e-01 | -3.6880 | 11.220 | 1.379e-03 | 2.469e-01 | 990.70 | 0.3345 | -10.220 | 0.0000 | 10.537 | -3.397 | 10.498 | 1358.02 | 0.0000 | 1.000e+00 | 0.0000 | 9.937 | 60.500 | 0.0000 | 8.837 | 10.670 | 7.0960 | 0.0000 | 2.179e-04 | 5.490e-22 | 4.870e-12 | 2.468e-01 | -3.468 | 9.804e-03 | -2.827e-03 | 1.226e-07 | 4.509e-14 | -4.3500 | 0.0000 | -4.364 | 0.0000 | -4.7820 | 0.0231 | 28.51 | 25.82 | 2.204e-01 | 8.702e-01 | -2.6890 | 3.9460 | 2.989e-02 | 3.237e-01 | 3.395e+08 | 0.4120 | -10.5600 | 0.0000 | 25.755 | -4.687 | 25.717 | 5.376e+08 | 0.0000 | 1.000e+00 | 0.0000 | 8.348 | 45.7000 | 0.0000 | 7.124 | 5.1710 | 0.0395 | 0.0007 | 2.311e-02 | 1.876e-24 | 1.099e-09 | 3.237e-01 | -3.0220 | 5.013e+00 | -1.659e+00 | 2.195e-04 | 1.445e-07 |
646 | Rv3891c | Mtb_R24 | 4374049 | 4374372 | 324 | - | artemis | gene | undefined | undefined | Rv3891c | Rv3891c | esxD | Esat-6 like protein | Function unknown | -1.434 | 0.0029 | -1.427 | 0.0137 | -1.440 | 0.0319 | 8.014 | 6.693 | 9.292e-02 | 2.417e-01 | -1.3210 | 4.368 | 1.772e-02 | 3.118e-01 | 141.90 | 0.3885 | -3.692 | 0.0002 | 2.695 | -1.430 | 2.678 | 177.53 | 0.0009 | 9.991e-01 | 0.0009 | 7.157 | 10.530 | 0.0012 | 6.813 | 3.999 | -1.4200 | 0.0021 | 3.189e-02 | 2.956e-03 | 1.373e-02 | 3.118e-01 | -1.410 | 1.220e-03 | -8.651e-04 | 1.156e-03 | 8.514e-07 | -0.8540 | 0.8953 | -1.337 | 0.9029 | -2.4620 | 0.8752 | 0.00 | 18.95 | 1.692e+02 | 1.782e+02 | 18.9500 | -0.6870 | 5.299e-01 | 6.152e-01 | 3.016e+06 | 3.7250 | -0.2293 | 0.8187 | 5.142 | -2.362 | 4.928 | 3.421e+06 | 0.5210 | 4.790e-01 | 0.5210 | 1.405 | 0.1011 | 0.7506 | -8.102 | 0.3470 | -4.9560 | 0.7368 | 8.751e-01 | 1.000e+00 | 9.029e-01 | 6.152e-01 | -0.6622 | 6.461e-01 | -9.757e-01 | 7.687e-01 | 1.923e-03 |