README.md

In StoreyLab/biobroom: Turn Bioconductor objects into tidy data frames

biobroom: Tidying up computational biology ====================

This package contains methods for converting standard objects constructed by bioinformatics packages, especially those in Bioconductor, and converting them to tidy data. It thus serves as a complement to the broom package, and follows the same the tidy/augment/glance division of tidying methods. Tidying data makes it easy to recombine, reshape and visualize bioinformatics analyses.

biobroom implements tidying methods for both S3 and S4 classes. Objects that can be tidied include

• ExpressionSet objects
• RangedSummarizedExperiment objects
• MSnSet objects
• per-gene differential expression tests from limma, edgeR, and DESeq2
• qvalue multiple hypothesis testing objects

Installation

The package can be installed with (requires devtools):

devtools::install_github("StoreyLab/biobroom")

Find out more about the provided methods with:

library(biobroom)
?edgeR_tidiers
?DESeq2_tidiers
?limma_tidiers
?ExpressionSet_tidiers
?MSnSet_tidiers
?GRangesList
?GRanges
?SummarizedExperiment_tidiers

Note on returned values

All biobroom tidy and augment methods, since they tend to be large data frames, return a tbl_df by default (this prevents them from printing many rows at once, while still acting like a traditional data.frame). To change this to a data.frame or data.table, you can set the biobroom.return option:

options(biobroom.return = "data.frame")
options(biobroom.return = "data.table")

StoreyLab/biobroom documentation built on May 9, 2019, 3:09 p.m.