BRGenomics is designed to help users avoid code repetition by providing efficient and tested functions to accomplish common, discrete tasks in the analysis of high-throughput sequencing data. The included functions are geared toward analyzing basepair-resolution sequencing data, the properties of which are exploited to increase performance and user-friendliness. We leverage standard Bioconductor methods and classes to maximize compatibility with its rich ecoystem of bioinformatics tools, and we aim to make BRGenomics sufficient for most post-alignment data processing. Common data processing and analytical steps are turned into fast-running one-liners that can be simultaneously applied across numerous datasets. BRGenomics is fully-documented, and we aim it to be beginner-friendly.
This package is designed to:
hitslibor the kent source utilities from the UCSC genome browser
DESeq2to calculate differential expression in a manner that is robust to global changes1 Avoid the default behavior of calculating genewise dispersion across all samples present, which is invalid if any experimental condition causes broad changes
DESeq2analysis, e.g. to exclude of specific sites/peaks from the analysis (not usually supported by DESeq2)
GRanges” object), which is already supported by a rich, user-friendly suite of tools that greatly simplify working with datasets and annotations
Signal counting and analysis: