# An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms

## Documentation for package ‘metaseqR2’ version 1.6.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

buildAnnotationDatabase | Build a local annotation database for metaseqR2
buildCustomAnnotation | Import custom annotation to the metaseqR2 annotation database from GTF file
combineBonferroni | Combine p-values with Bonferroni's method
combineHarmonic | Combine p-values using weights
combineMaxp | Combine p-values using the maximum p-value
combineMinp | Combine p-values using the minimum p-value
combineSimes | Combine p-values with Simes' method
combineWeight | Combine p-values using weights
createSignalTracks | Create bigWig signal tracks
diagplotAvgFtd | Create average False (or True) Discovery curves
diagplotBoxplot | Boxplots wrapper for the metaseqR2 package
diagplotCor | Summarized correlation plots
diagplotDeHeatmap | Diagnostic heatmap of differentially expressed genes
diagplotEdaseq | Diagnostic plots based on the EDASeq package
diagplotFiltered | Diagnostic plot for filtered genes
diagplotFtd | Create False (or True) Positive (or Negative) curves
diagplotMds | Multi-Dimensinal Scale plots or RNA-Seq samples
diagplotNoiseq | Diagnostic plots based on the NOISeq package
diagplotPairs | Massive X-Y, M-D correlation plots
diagplotRoc | Create basic ROC curves
diagplotVenn | Venn diagrams when performing meta-analysis
diagplotVolcano | (Interactive) volcano plots of differentially expressed genes
downsampleCounts | Downsample read counts
estimateAufcWeights | Estimate AUFC weights
estimateSimParams | Estimate negative binomial parameters from real data
getAnnotation | Annotation downloader
getDefaults | Default parameters for several metaseqr functions
getInstalledAnnotations | Load a metaseqR2 annotation element
getWeights | Get precalculated statistical test weights
hg19pvalues | p-values from human RNA-Seq data with two conditions, four samples
importCustomAnnotation | Import a metaseqR2 custom annotation element
libsizeListMm9 | Mouse RNA-Seq data with two conditions, four samples
loadAnnotation | Load a metaseqR2 annotation element
makeSimDataSd | Create simulated counts using the Soneson-Delorenzi method
makeSimDataTcc | Create simulated counts using TCC package
metaseqr2 | The main metaseqr2 pipeline
metaseqrPlot | Diagnostic plots for the metaseqR2 package
metaTest | Meta-analysis using several RNA-Seq statistics
mm9GeneCounts | Mouse RNA-Seq data with two conditions, four samples
normalizeAbsseq | Normalization based on the ABSSeq package
normalizeDeseq | Normalization based on the DESeq package
normalizeDeseq2 | Normalization based on the DESeq2 package
normalizeDss | Normalization based on the DSS package
normalizeEdaseq | Normalization based on the EDASeq package
normalizeEdger | Normalization based on the edgeR package
normalizeNbpseq | Normalization based on the NBPSeq package
normalizeNoiseq | Normalization based on the NOISeq package
read2count | SAM/BAM/BED file reader helper for the metaseqr2 pipeline
readTargets | Creates sample list and BAM/BED file list from file
sampleListMm9 | Mouse RNA-Seq data with two conditions, four samples
statAbsseq | Statistical testing with ABSSeq
statBayseq | Statistical testing with baySeq
statDeseq | Statistical testing with DESeq
statDeseq2 | Statistical testing with DESeq2
statDss | Statistical testing with DSS
statEdger | Statistical testing with edgeR
statLimma | Statistical testing with limma
statNbpseq | Statistical testing with NBPSeq
statNoiseq | Statistical testing with NOISeq