Software for Computing and Annotating Genomic Ranges

TLDR

The paper presents a Bioconductor infrastructure for representing and computing annotated genomic ranges, integrating genomic data with R's statistical computing features. The infrastructure comprises three core packages—IRanges, GenomicRanges, and GenomicFeatures—that provide scalable data structures and efficient algorithms for overlap, nearest‑neighbor detection, coverage calculation, and other range operations. The infrastructure underpins over 80 Bioconductor packages, such as those for sequence analysis, differential expression analysis, and visualization.

Abstract

We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.