Skip to content

dolphinnext/chipseq

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

67 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Travis-ci tests: DOI:10.1186/s12864-020-6714-x

ChIP-seq Pipeline maps reads with Bowtie2, removes duplicates with Picard or Samtools, calls ChIP peaks with MACS2 and finally creates count table for analysis. Additionally these peaks analyzed by Motif Finder module (HOMER).

Steps:

  1. For Quality Control, we use FastQC to create qc outputs. There are optional read quality filtering (trimmomatic), read quality trimming (trimmomatic), adapter removal (cutadapt) processes available.
  2. In the sequential mapping step, Bowtie2 is used to count or filter out common reads (eg. ercc, rmsk).
  3. Bowtie2 is used to align reads to a selected genome, and duplicates removed with Picard or Samtools,
  4. When processing several samples together, pipeline provide consensus peak calls by merging all peaks individually called in each samples using Bedtools (Quinlan and Hall 2010). The number of reads in each peak location are then quantified using Bedtools (Quinlan and Hall 2010) coverage function.
  5. Optionally, genome-wide Bam analysis is done by RseQC.
  6. Optionally, you can create Integrative Genomics Viewer (IGV) and Genome Browser Files (TDF and Bigwig, respectively)
  7. Optionally, these peaks analyzed by Motif Finder module (HOMER).
  8. As a result, pipeline generates a matrix that has the count values for each peak region and samples. This matrix can be uploaded directly to the embedded version of DEBrowser (Kucukural et al. 2019) to perform differential analysis or downloaded to perform other analysis.

Inputs:

  • Reads

  • ChIP-prep section: To enable peak calling, please click settings of run_ChIP_MACS2 and enter your samples by clicking Add button in the Sample Definitions section as described below:

    There are three fields need to be entered for each sample: output-prefix, sample-prefix, and input-prefix.

    Output-Prefix Sample-Prefix Input-Prefix (optional)
    exper-rep1 exper-rep1
    control-rep1 control-rep1
    • Output-Prefix: Output prefix of the sample. Final reports will be created by using this sample name.
    • Sample-Prefix: Sample name which is entered in the reads section.
    • Input-Prefix (optional): If your experiment has background sample (input), you can specify its prefix in this section.

Citation:

If you use DolphinNext in your research, please cite: Yukselen, O., Turkyilmaz, O., Ozturk, A.R. et al. DolphinNext: a distributed data processing platform for high throughput genomics. BMC Genomics 21, 310 (2020). https://doi.org/10.1186/s12864-020-6714-x

Program Versions:

  • Macs2 v2.1.2
  • Bowtie2 v2.3.5
  • Bowtie v1.2.2
  • FastQC v0.11.8
  • Star v2.6.1
  • Picard v2.18.27
  • Rseqc v2.6.2
  • Samtools v1.3
  • Multiqc v1.7
  • Trimmomatic v0.39
  • Igvtools v2.5.3
  • Bedtools v2.29.2
  • Fastx_toolkit v0.0.14
  • Ucsc-wigToBigWig v366
  • Pdfbox-App v2.0.0
  • Scripture v0.1
  • HOMER v4.10

Run through DolphinNext User Interface:

To start using the dolphinnext/chipseq pipeline please go to DolphinNext Web page and click run button.

Run through Command Line:

To install and start using the dolphinnext/chipseq pipeline by using command line, please follow these steps: Installation.