index.html preprocessing.html sample_estimation.html
1 Differential expression: 20170703
first_try <- all_pairwise(parasite_expt, model_batch=FALSE)## There is just one batch in this data.## Assuming no batch in model for testing pca.## There is just one batch in this data.## Finished running DE analyses, collecting outputs.## Comparing analyses 1/1: wt_vs_odd3keepers <- list(
"odd_over_wt" = c("odd3", "wt"))
write_try <- combine_de_tables(first_try, keepers=keepers,
excel=paste0("excel/lmajor_de-v", ver, ".xlsx"))## Deleting the file excel/lmajor_de-v20170703.xlsx before writing the tables.## Writing a legend of columns.## Printing a pca plot before/after surrogates/batch estimation.## Working on 1/1: odd_over_wt## Found inverse table with wt_vs_odd3## Adding venn plots for odd3_vs_wt.
## Limma expression coefficients for odd3_vs_wt; R^2: 0.999; equation: y = 0.999x + 0.0114## Edger expression coefficients for odd3_vs_wt; R^2: 0.999; equation: y = 1x - 0.0117## DESeq2 expression coefficients for odd3_vs_wt; R^2: 0.995; equation: y = 1.01x - 0.115## Writing summary information.## Attempting to add the comparison plot to pairwise_summary at row: 19 and column: 1## Performing save of the workbook.
sig_try <- extract_significant_genes(write_try, excel=paste0("excel/lmajor_sig-v", ver, ".xlsx"))## Writing a legend of columns.## Writing excel data sheet 0/1: odd3_vs_wt## Assuming the fold changes are on the log scale and so taking >< 0## After (adj)p filter, the up genes table has 197 genes.## After (adj)p filter, the down genes table has 178 genes.## Assuming the fold changes are on the log scale and so taking -1.0 * fc## After fold change filter, the up genes table has 5 genes.## After fold change filter, the down genes table has 23 genes.## Printing significant genes to the file: excel/lmajor_sig-v20170703.xlsx## 1/1: Writing excel data sheet up_1limma_odd3_vs_wt## 1/1: Writing excel data sheet down_1limma_odd3_vs_wt## Writing excel data sheet 1/1: odd3_vs_wt## Assuming the fold changes are on the log scale and so taking >< 0## After (adj)p filter, the up genes table has 389 genes.## After (adj)p filter, the down genes table has 430 genes.## Assuming the fold changes are on the log scale and so taking -1.0 * fc## After fold change filter, the up genes table has 6 genes.## After fold change filter, the down genes table has 34 genes.## Printing significant genes to the file: excel/lmajor_sig-v20170703.xlsx## 1/1: Writing excel data sheet up_1edger_odd3_vs_wt## 1/1: Writing excel data sheet down_1edger_odd3_vs_wt## Writing excel data sheet 2/1: odd3_vs_wt## Assuming the fold changes are on the log scale and so taking >< 0## After (adj)p filter, the up genes table has 528 genes.## After (adj)p filter, the down genes table has 503 genes.## Assuming the fold changes are on the log scale and so taking -1.0 * fc## After fold change filter, the up genes table has 4 genes.## After fold change filter, the down genes table has 27 genes.## Printing significant genes to the file: excel/lmajor_sig-v20170703.xlsx## 1/1: Writing excel data sheet up_1deseq_odd3_vs_wt## 1/1: Writing excel data sheet down_1deseq_odd3_vs_wt## Writing excel data sheet 3/1: odd3_vs_wt## Assuming the fold changes are on the log scale and so taking >< 0## After (adj)p filter, the up genes table has 0 genes.## After (adj)p filter, the down genes table has 3 genes.## Assuming the fold changes are on the log scale and so taking -1.0 * fc## After fold change filter, the up genes table has 0 genes.## After fold change filter, the down genes table has 1 genes.## Printing significant genes to the file: excel/lmajor_sig-v20170703.xlsx## 1/1: Writing excel data sheet up_1basic_odd3_vs_wt## 1/1: Writing excel data sheet down_1basic_odd3_vs_wt## Warning in if (according_to == "all") {: the condition has length > 1 and only the first
## element will be used## Adding significance bar plots.pander::pander(sessionInfo())R version 3.4.1 (2017-06-30)
**Platform:** x86_64-pc-linux-gnu (64-bit)
locale: LC_CTYPE=en_US.utf8, LC_NUMERIC=C, LC_TIME=en_US.utf8, LC_COLLATE=en_US.utf8, LC_MONETARY=en_US.utf8, LC_MESSAGES=en_US.utf8, LC_PAPER=en_US.utf8, LC_NAME=C, LC_ADDRESS=C, LC_TELEPHONE=C, LC_MEASUREMENT=en_US.utf8 and LC_IDENTIFICATION=C
attached base packages: parallel, stats4, stats, graphics, grDevices, utils, datasets, methods and base
other attached packages: hpgltools(v.2017.01), Vennerable(v.3.1.0.9000), TxDb.Lmajor.friedlin.TriTrypDB28(v.28.0), org.Lmajor.friedlin.eg.db(v.28.0), Leishmania.major.Friedlin(v.28.0), GO.db(v.3.4.1), OrganismDbi(v.1.18.0), GenomicFeatures(v.1.28.4), GenomicRanges(v.1.28.4), GenomeInfoDb(v.1.12.2), AnnotationDbi(v.1.38.2), IRanges(v.2.10.3), S4Vectors(v.0.14.3), Biobase(v.2.36.2) and BiocGenerics(v.0.22.0)
loaded via a namespace (and not attached): Rtsne(v.0.13), colorspace(v.1.3-2), rprojroot(v.1.2), htmlTable(v.1.9), corpcor(v.1.6.9), XVector(v.0.16.0), base64enc(v.0.1-3), roxygen2(v.6.0.1), ggrepel(v.0.6.5), bit64(v.0.9-7), xml2(v.1.1.1), codetools(v.0.2-15), splines(v.3.4.1), doParallel(v.1.0.10), robustbase(v.0.92-7), geneplotter(v.1.54.0), knitr(v.1.17), Formula(v.1.2-2), Rsamtools(v.1.28.0), annotate(v.1.54.0), cluster(v.2.0.6), graph(v.1.54.0), compiler(v.3.4.1), backports(v.1.1.0), assertthat(v.0.2.0), Matrix(v.1.2-11), lazyeval(v.0.2.0), limma(v.3.32.5), acepack(v.1.4.1), htmltools(v.0.3.6), tools(v.3.4.1), bindrcpp(v.0.2), gtable(v.0.2.0), glue(v.1.1.1), GenomeInfoDbData(v.0.99.0), reshape2(v.1.4.2), dplyr(v.0.7.2), Rcpp(v.0.12.12), Biostrings(v.2.44.2), preprocessCore(v.1.38.1), rtracklayer(v.1.36.4), iterators(v.1.0.8), stringr(v.1.2.0), openxlsx(v.4.0.17), testthat(v.1.0.2), gtools(v.3.5.0), devtools(v.1.13.3), XML(v.3.98-1.9), DEoptimR(v.1.0-8), edgeR(v.3.18.1), directlabels(v.2017.03.31), zlibbioc(v.1.22.0), scales(v.0.5.0), BiocInstaller(v.1.26.1), SummarizedExperiment(v.1.6.3), RBGL(v.1.52.0), RColorBrewer(v.1.1-2), yaml(v.2.1.14), gridExtra(v.2.2.1), memoise(v.1.1.0), ggplot2(v.2.2.1), pander(v.0.6.1), rpart(v.4.1-11), biomaRt(v.2.32.1), latticeExtra(v.0.6-28), stringi(v.1.1.5), RSQLite(v.2.0), genefilter(v.1.58.1), highr(v.0.6), foreach(v.1.4.3), checkmate(v.1.8.3), BiocParallel(v.1.10.1), rlang(v.0.1.2), pkgconfig(v.2.0.1), commonmark(v.1.4), matrixStats(v.0.52.2), bitops(v.1.0-6), evaluate(v.0.10.1), lattice(v.0.20-35), bindr(v.0.1), htmlwidgets(v.0.9), GenomicAlignments(v.1.12.2), labeling(v.0.3), bit(v.1.1-12), plyr(v.1.8.4), magrittr(v.1.5), DESeq2(v.1.16.1), R6(v.2.2.2), Hmisc(v.4.0-3), DelayedArray(v.0.2.7), DBI(v.0.7), foreign(v.0.8-69), withr(v.2.0.0), nnet(v.7.3-12), survival(v.2.41-3), RCurl(v.1.95-4.8), tibble(v.1.3.4), crayon(v.1.3.2), KernSmooth(v.2.23-15), rmarkdown(v.1.6), locfit(v.1.5-9.1), grid(v.3.4.1), data.table(v.1.10.4), blob(v.1.1.0), digest(v.0.6.12), xtable(v.1.8-2), munsell(v.0.4.3) and quadprog(v.1.5-5)
message(paste0("This is hpgltools commit: ", get_git_commit()))## If you wish to reproduce this exact build of hpgltools, invoke the following:## > git clone http://github.com/abelew/hpgltools.git## > git reset 7ed429e18249ffb93173bf0d788c8c71928d5f89## R> packrat::restore()## This is hpgltools commit: Wed Sep 6 16:57:49 2017 -0400: 7ed429e18249ffb93173bf0d788c8c71928d5f89this_save <- paste0(gsub(pattern="\\.Rmd", replace="", x=rmd_file), "-v", ver, ".rda.xz")
message(paste0("Saving to: ", this_save))## Saving to: 03_differential_expression-v20170703.rda.xztmp <- sm(saveme(filename=this_save))