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Assessing the increase in power from increasing read depth in a given RNA-Seq study

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superSeq: Determining sufficient read depth in RNA-Seq experiments

The superSeq package models the relationship between statistical power and read depth in an RNA sequencing study. Our algorithm can help predict how many additional reads, if any, should be sequenced to achieve desired statistical power.

See also superSeq: Determining sufficient sequencing depth in RNA-Seq differential expression studies.

Installation

First install the Bioconductor dependencies:

source("http://bioconductor.org/biocLite.R")
biocLite(c("qvalue", "limma", "edgeR", "DESeq2", "DEXSeq", "pasilla"))

Then install the devtools package, and use it to install the subSeq and superSeq packages.

install.packages("devtools")
library(devtools)
install_github("StoreyLab/subSeq")
install_github("StoreyLab/superSeq", build_opts = c("--no-resave-data", "--no-manual"), build_vignettes = TRUE)

Vignette

Once you've installed the package, you can access the vignette with

library(superSeq)
vignette("superSeq")

If you run into a problem or have a question about the software's usage, please open a GitHub issue.

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Assessing the increase in power from increasing read depth in a given RNA-Seq study

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