Astrocyte ChIPseq analysis Workflow Package
Introduction
ChIP-seq Analysis is a bioinformatics best-practice analysis pipeline used for chromatin immunoprecipitation (ChIP-seq) data analysis.
The pipeline uses Nextflow, a bioinformatics workflow tool. It pre-processes raw data from FastQ inputs, aligns the reads and performs extensive quality-control on the results.
Pipeline Steps
- Trim adaptors TrimGalore!
- Align with BWA
- Filter reads with Sambamba S
- Quality control with DeepTools
- Calculate Cross-correlation using SPP and PhantomPeakQualTools
- Signal profiling using MACS2
- Call consenus peaks
- Annotate all peaks using ChipSeeker
- Use MEME-ChIP to find motifs in original peaks
- Find differential expressed peaks using DiffBind (If more than 1 experiment)
Workflow Parameters
reads - Choose all ChIP-seq fastq files for analysis.
pairedEnd - Choose True/False if data is paired-end
design - Choose the file with the experiment design information. TSV format
genome - Choose a genomic reference (genome).Design file
The following columns are necessary, must be named as in template. An design file template can be downloaded HERE
SampleID
The id of the sample. This will be the header in output files, please make sure it is concise
Tissue
Tissue of the sample
Factor
Factor of the experiment
Condition
This is the group that will be used for pairwise differential expression analysis
Replicate
Replicate id
Peaks
The file name of the peak file for this sample
bamReads
The file name of the IP BAM for this sample
bamControl
The file name of the control BAM for this sample
ContorlID
The id of the control sample
PeakCaller
The peak caller usedCredits
This example worklow is derived from original scripts kindly contributed by the Bioinformatic Core Facility (BICF), Department of Bioinformatics