BRGenomics

BRGenomics provides post-alignment processing and analysis of high-resolution genomics data in R/Bioconductor for quantification, normalization, and metagene analyses.


Key Features:

  • Bioconductor integration: Leverages Bioconductor infrastructure and GenomicRanges for genomic range operations and compatibility with ecosystem data structures.
  • Data importation and processing: Supports efficient import and processing of post-alignment sequencing data with optimization for parallel processing.
  • Read counting and aggregation: Implements robust methods for read counting and aggregation to enable accurate quantification across experiments.
  • Normalization techniques: Provides spike-in and batch normalization strategies to mitigate technical variability between samples.
  • Resampling methods: Includes re-sampling approaches for robust metagene analyses and exploration of aggregate signal profiles.
  • Data cleaning and modification: Offers functions to clean and modify sequencing and annotation data for high-quality downstream analysis.
  • Efficient storage and quantification: Supports multiple quantification and storage strategies including whole reads, quantitative single-base data, and run-length encoded coverage information.

Scientific Applications:

  • ATAC-seq: Analysis of chromatin accessibility datasets such as ATAC-seq for region-level and single-base quantification.
  • ChIP-seq/ChIP-exo: Analysis of protein–DNA interaction datasets including ChIP-seq and ChIP-exo for binding and footprinting studies.
  • PRO-seq/PRO-cap: Analysis of nascent transcription datasets such as PRO-seq and PRO-cap for transcriptional initiation and elongation profiling.
  • RNA-seq: Analysis of gene expression datasets from RNA-seq for quantification and comparative studies.

Methodology:

Implements Bioconductor-based genomic range operations via GenomicRanges, parallelized data import and processing, read counting and aggregation algorithms, spike-in and batch normalization methods, re-sampling for metagene analyses, and support for run-length encoded coverage representations.

Topics

Details

License:
Artistic-2.0
Cost:
Free of charge
Tool Type:
library
Operating Systems:
Mac, Linux, Windows
Programming Languages:
R
Added:
1/2/2024
Last Updated:
11/24/2024

Operations

Publications

DeBerardine M. BRGenomics for analyzing high-resolution genomics data in R. Bioinformatics. 2023;39(6). doi:10.1093/bioinformatics/btad331. PMID:37208173. PMCID:PMC10278936.

PMID: 37208173
Funding: - National Institutes of Health: GM025232, GM139738

Links