Package: ERSSA 1.31.0

Zixuan Shao

ERSSA: Empirical RNA-seq Sample Size Analysis

The ERSSA package takes user supplied RNA-seq differential expression dataset and calculates the number of differentially expressed genes at varying biological replicate levels. This allows the user to determine, without relying on any a priori assumptions, whether sufficient differential detection has been acheived with their RNA-seq dataset.

Authors:Zixuan Shao [aut, cre]

ERSSA_1.31.0.tar.gz
ERSSA_1.31.0.zip(r-4.7)ERSSA_1.31.0.zip(r-4.6)ERSSA_1.31.0.zip(r-4.5)
ERSSA_1.31.0.tgz(r-4.6-any)ERSSA_1.31.0.tgz(r-4.5-any)
ERSSA_1.31.0.tar.gz(r-4.7-any)ERSSA_1.31.0.tar.gz(r-4.6-any)
ERSSA_1.31.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ERSSA/json (API)

# Install 'ERSSA' in R:

install.packages('ERSSA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/zshao1/erssa/issues

Datasets:

combinations.partial - Example list of combinations generated by comb_gen function.
condition_table.full - Example table of sample names and conditions
condition_table.partial - Example table of sample names and conditions
count_table.filtered.partial - Example count table of GTEx RNA-seq experiment, fitered by count_filter function
count_table.full - Example count table of GTEx RNA-seq experiment
count_table.partial - Example count table of GTEx RNA-seq experiment
deg.partial - Example list of DE genes generated by edgeR

On BioConductor:ERSSA-1.31.0(bioc 3.24)ERSSA-1.30.0(bioc 3.23)

immunooncology geneexpression transcription differentialexpression rnaseq multiplecomparison qualitycontrol

4.48 score 1 stars 3 scripts 375 downloads 11 exports 60 dependencies

Last updated from:40734a208c. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	199
linux-devel-x86_64	NOTE	380
source / vignettes	OK	248
linux-release-x86_64	NOTE	437
macos-release-arm64	NOTE	184
macos-oldrel-arm64	NOTE	157
windows-devel	NOTE	283
windows-release	NOTE	248
windows-oldrel	NOTE	293
wasm-release	OK	140

Exports:comb_gen count_filter erssa erssa_deseq2 erssa_deseq2_parallel erssa_edger erssa_edger_parallel ggplot2_dotplot ggplot2_intersectPlot ggplot2_marginPlot ggplot2_TPR_FPRPlot

Dependencies:abind apeglm bbmle bdsmatrix BH Biobase BiocGenerics BiocParallel cli coda codetools cpp11 DelayedArray DESeq2 edgeR emdbook farver formatR futile.logger futile.options generics GenomicRanges ggplot2 glue gtable IRanges isoband labeling lambda.r lattice lifecycle limma locfit MASS Matrix MatrixGenerics matrixStats mvtnorm numDeriv plyr R6 RColorBrewer Rcpp RcppArmadillo RcppEigen RcppNumerical rlang S4Arrays S4Vectors S7 scales Seqinfo snow SparseArray statmod SummarizedExperiment vctrs viridisLite withr XVector

ERSSA Package Introduction

Rendered fromERSSA.Rmdusingknitr::rmarkdown

Last update: 2020-01-22
Started: 2018-04-11

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Calculate unique combinations of samples at varying replicate number	comb_gen
Example list of combinations generated by comb_gen function.	combinations.partial
Example table of sample names and conditions	condition_table.full
Example table of sample names and conditions	condition_table.partial
Filter RNA-seq expression table	count_filter
Example count table of GTEx RNA-seq experiment, fitered by count_filter function	count_table.filtered.partial
Example count table of GTEx RNA-seq experiment	count_table.full
Example count table of GTEx RNA-seq experiment	count_table.partial
Example list of DE genes generated by edgeR	deg.partial
Empirical RNA-seq Sample Size Analysis	erssa
Run DESeq2 for computed sample combinations	erssa_deseq2
Run DESeq2 for computed sample combinations with parallel computing	erssa_deseq2_parallel
Run edgeR for computed sample combinations	erssa_edger
Run edgeR for computed sample combinations with parallel computing	erssa_edger_parallel
Plot number of DE genes	ggplot2_dotplot
Plot number of DE genes that is common across combinations	ggplot2_intersectPlot
Plot percent increase in detection of DE genes across replicate levels	ggplot2_marginPlot
Plot TPR and FPR of each combination	ggplot2_TPR_FPRPlot