index.html sample_estimation.html

1 Differential Expression, Mus musculus: 20170703

At this point, I am reasonably sure that the data is not crazytown or replete with difficult to assay batch effects. We have (I think) a reasonable factor in the experimental design to include as batch, so I will allow my differential expression toys to use that.

2 Preliminary Differential Expression in mice

Grab the data structure from sample_estimation_mmusculus and see what happens.

## Drop low count genes
isc_filtered <- sm(normalize_expt(isc_mm, filter=TRUE))

## Do a default no-batch assessment.
isc_mm_de_default <- sm(all_pairwise(isc_filtered, model_batch=FALSE,
                                     limma_robust="robust", limma_method="robust", parallel=FALSE))
isc_mm_written_default <- sm(combine_de_tables(isc_mm_de_default,
                                               excel=paste0("tables/mm_de_nobatch_default-v", ver, ".xlsx")))
isc_mm_sig <- sm(extract_significant_genes(isc_mm_written_default,
                                           excel=paste0("tables/mm_de_nobatch_default_sig-v", ver, ".xlsx")))

2.1 Check venn plots

Lets see if I finally got these darn things to behave.

isc_mm_written_default$venns$wt_vs_mut$up_noweight

isc_mm_written_default$venns$wt_vs_mut$down_noweight

isc_mm_de_sva <- sm(all_pairwise(isc_filtered, model_batch="svaseq",
                                 limma_robust="robust", limma_method="robust", parallel=FALSE))
isc_mm_written_sva <- sm(combine_de_tables(isc_mm_de_sva,
                                           excel=paste0("tables/mm_de_nobatch_sva-v", ver, ".xlsx")))
isc_mm_sig_sva <- sm(extract_significant_genes(isc_mm_written_sva,
                                               excel=paste0("tables/mm_de_nobatch_sva_sig-v", ver, ".xlsx")))

index.html sample_estimation.html

pander::pander(sessionInfo())

R version 3.3.3 (2017-03-06)

**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: grid, parallel, stats4, stats, graphics, grDevices, utils, datasets, methods and base

other attached packages: hpgltools(v.2017.01), DESeq2(v.1.14.1), SummarizedExperiment(v.1.4.0), GenomicRanges(v.1.26.4), GenomeInfoDb(v.1.10.3), ruv(v.0.9.6), Vennerable(v.3.1.0.9000), Rgraphviz(v.2.18.0), graph(v.1.52.0), SparseM(v.1.77), topGO(v.2.26.0), GO.db(v.3.4.0), AnnotationDbi(v.1.36.2), IRanges(v.2.8.2), S4Vectors(v.0.12.2), Biobase(v.2.34.0) and BiocGenerics(v.0.20.0)

loaded via a namespace (and not attached): minqa(v.1.2.4), colorspace(v.1.3-2), colorRamps(v.2.3), rprojroot(v.1.2), qvalue(v.2.6.0), htmlTable(v.1.9), corpcor(v.1.6.9), XVector(v.0.14.1), 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.3.3.3), doParallel(v.1.0.10), robustbase(v.0.92-7), geneplotter(v.1.52.0), knitr(v.1.16), Formula(v.1.2-1), nloptr(v.1.0.4), gProfileR(v.0.6.1), Rsamtools(v.1.26.2), pbkrtest(v.0.4-7), annotate(v.1.52.1), cluster(v.2.0.6), geneLenDataBase(v.1.10.0), compiler(v.3.3.3), backports(v.1.1.0), Matrix(v.1.2-10), lazyeval(v.0.2.0), limma(v.3.30.13), acepack(v.1.4.1), htmltools(v.0.3.6), tools(v.3.3.3), gtable(v.0.2.0), reshape2(v.1.4.2), Rcpp(v.0.12.11), Biostrings(v.2.42.1), preprocessCore(v.1.36.0), gdata(v.2.18.0), nlme(v.3.1-131), rtracklayer(v.1.34.2), iterators(v.1.0.8), stringr(v.1.2.0), openxlsx(v.4.0.17), testthat(v.1.0.2), lme4(v.1.1-13), gtools(v.3.5.0), devtools(v.1.13.2), statmod(v.1.4.30), XML(v.3.98-1.9), edgeR(v.3.16.5), DEoptimR(v.1.0-8), zlibbioc(v.1.20.0), MASS(v.7.3-47), scales(v.0.4.1), RBGL(v.1.50.0), RColorBrewer(v.1.1-2), yaml(v.2.1.14), memoise(v.1.1.0), goseq(v.1.26.0), gridExtra(v.2.2.1), pander(v.0.6.0), ggplot2(v.2.2.1), biomaRt(v.2.30.0), rpart(v.4.1-11), latticeExtra(v.0.6-28), stringi(v.1.1.5), RSQLite(v.2.0), genefilter(v.1.56.0), foreach(v.1.4.3), checkmate(v.1.8.3), GenomicFeatures(v.1.26.4), caTools(v.1.17.1), BiocParallel(v.1.8.2), matrixStats(v.0.52.2), rlang(v.0.1.1), pkgconfig(v.2.0.1), commonmark(v.1.2), bitops(v.1.0-6), evaluate(v.0.10.1), lattice(v.0.20-35), GenomicAlignments(v.1.10.1), htmlwidgets(v.0.8), labeling(v.0.3), bit(v.1.1-12), plyr(v.1.8.4), magrittr(v.1.5), variancePartition(v.1.4.2), R6(v.2.2.2), gplots(v.3.0.1), Hmisc(v.4.0-3), DBI(v.0.7), foreign(v.0.8-69), withr(v.1.0.2), mgcv(v.1.8-17), survival(v.2.41-3), RCurl(v.1.95-4.8), nnet(v.7.3-12), tibble(v.1.3.3), crayon(v.1.3.2), KernSmooth(v.2.23-15), rmarkdown(v.1.6), locfit(v.1.5-9.1), sva(v.3.22.0), 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 BiasedUrn(v.1.07)

this_save <- paste0(gsub(pattern="\\.Rmd", replace="", x=rmd_file), "-v", ver, ".rda.xz")
message(paste0("Saving to ", this_save))
## Saving to 03_differential_expression_mmusculus-v20170703.rda.xz
tmp <- sm(saveme(filename=this_save))
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