As many of our ongoing projects involve next-generation sequencing data, our lab is equipped with bioinformatics experts who specialize in whole genome analysis. We use both existing R packages and novel scripts to delve into these large scale data sets, including:
- Reads mapping —- bowtie, bowtie2, STAR, Subread, Tophat
- Counting reads to genomic features —- featureCounts, Cufflinks
- Reads deduplication —- samtools, Rsamtools
- Peak calling —- MACS2, SPP, BayesPeak
- Differential binding analysis of ChIP-Seq peak data —- DiffBind, chipseq
- Annotation imports, interface to online genome browsers —- rtracklayer
- RNA-Seq analysis —- DESeq, edgeR, Cuffdiff
- Motif calling —- MEME
- Visualization —- ggplot2
Bioinformatics allows us to objectively integrate the various regulatory layers in order to further our understanding of how epigenetic modifications, independently or in conjunction with one another, contribute to biological and pathological processes. Through this vital tool, we have been able to:
- Create base-pair resolution maps of the various DNA modifications and identify differentially modified regions
- Decipher the role of histone and DNA modifications in gene regulation
- Integrate DNA modification maps with histones modification profiles and transcriptomic data
- Identify genome-wide DNA binding sites for histone modifications, transcription factors and other proteins