A ChIP-Seq Data Analysis Pipeline Based on Bioconductor Packages
Genomics & Informatics
;
: 11-18, 2017.
Article
in English
| WPRIM
| ID: wpr-69983
ABSTRACT
Nowadays, huge volumes of chromatin immunoprecipitation-sequencing (ChIP-Seq) data are generated to increase the knowledge on DNA-protein interactions in the cell, and accordingly, many tools have been developed for ChIP-Seq analysis. Here, we provide an example of a streamlined workflow for ChIP-Seq data analysis composed of only four packages in Bioconductor dada2, QuasR, mosaics, and ChIPseeker. ‘dada2’ performs trimming of the high-throughput sequencing data. ‘QuasR’ and ‘mosaics’ perform quality control and mapping of the input reads to the reference genome and peak calling, respectively. Finally, ‘ChIPseeker’ performs annotation and visualization of the called peaks. This workflow runs well independently of operating systems (e.g., Windows, Mac, or Linux) and processes the input fastq files into various results in one run. R code is available at github https//github.com/ddhb/Workflow_of_Chipseq.git.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Quality Control
/
Chromatin
/
Statistics as Topic
/
Genome
/
Chromatin Immunoprecipitation
Language:
English
Journal:
Genomics & Informatics
Year:
2017
Type:
Article
Similar
MEDLINE
...
LILACS
LIS