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Forked from BICF / Astrocyte / chipseq_analysis
110 commits behind the upstream repository.
index.md 12.34 KiB

BICF ChIP-seq Analysis Workflow

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.

Report issues to the Bioinformatic Core Facility BICF

Pipeline Steps

  • There are 11 steps to the pipeline
    1. Check input files
    2. Trim adaptors TrimGalore!
    3. Aligned trimmed reads with bwa, and sorts/converts to bam with samtools
    4. Mark duplicates with Sambamba, and filter reads with samtools
    5. Quality metrics with deep tools
    6. Calculate cross-correlation using PhantomPeakQualTools
    7. Call peaks with MACS
    8. Calculate consensus peaks
    9. Annotate all peaks using ChipSeeker
    10. Calculate Differential Binding Activity with DiffBind (If more than 1 rep in more than 1 experiment)
    11. Use MEME-ChIP to find motifs in original peaks

Workflow Parameters

1. One or more input FASTQ files from a ChIP-seq expereiment and a design file with the link bewetwen the same file name and sample id (required) - Choose all ChIP-seq fastq files for analysis.
2. In single-end sequencing, the sequencer reads a fragment from only one end to the other, generating the sequence of base pairs. In paired-end reading it starts at one read, finishes this direction at the specified read length, and then starts another round of reading from the opposite end of the fragment. (Paired-end: True, Single-end: False) (required)
3. A design file listing sample id, fastq files, corresponding control id and additional information about the sample.
genome - Choose a genomic reference (genome).
4. Reference species and genome used for alignment and subsequent analysis. (required)
5. Run differential peak analysis (required). Must have at least 2 replicates per experiment and at least 2 experiments.
6. Run motif calling (required). Top 600 peaks sorted by p-value.
7. Ensure configuration for astrocyte. (required; always true)

Design file

  • The Design file is a tab-delimited file with 8 columns for Single-End and 9 columns for Paired-End. Letter, numbers, and underlines can be used in the names. However, the names can only begin with a letter. Columns must be as follows:

    1. sample_id          a short, unique, and concise name used to label output files; will be used as a control_id if it is the control sample
    2. experiment_id    biosample_treatment_factor; same name given for all replicates of treatment. Will be used for the consensus header.
    3. biosample          symbol for tissue type or cell line
    4. factor                 symbol for antibody target
    5. treatment           symbol of treatment applied
    6. replicate             a number, usually from 1-3 (i.e. 1)
    7. control_id          sample_id name that is the control for this sample
    8. fastq_read1        name of fastq file 1 for SE or PC data
    9. fastq_read2        name of fastq file 2 for PE data

  • See HERE for an example design file, paired-end

  • See HERE for an example design file, single-end

Output Files

Folder File Description
design N/A Inputs used for analysis; can ignore
trimReads *_trimming_report.txt report detailing how many reads were trimmed
trimReads *_trimmed.fq.gz trimmed fastq files used for analysis
alignReads *.srt.bam.flagstat.qc QC metrics from the mapping process
alignReads *.srt.bam sorted bam file
filterReads *.dup.qc QC metrics of find duplicate reads (sambamba)
filterReads *.filt.nodup.bam filtered bam file with duplicate reads removed
filterReads *.filt.nodup.bam.bai indexed filtered bam file
filterReads *.filt.nodup.flagstat.qc QC metrics of filtered bam file (mapping stats, samtools)
filterReads *.filt.nodup.pbc.qc QC metrics of library complexity
convertReads *.filt.nodup.bedse.gz bed alignment in BEDPE format
convertReads *.filt.nodup.tagAlign.gz bed alignent in BEDPE format, same as bedse unless samples are paired-end
multiqcReport multiqc_report.html Quality control report of NRF, PBC1, PBC2, NSC, and RSC. Also contains software versions and references to cite.
experimentQC coverage.pdf plot to assess the sequencing depth of a given sample
experimentQC *_fingerprint.pdf plot to determine if the antibody-treatment enriched sufficiently
experimentQC heatmeap_SpearmanCorr.pdf plot of Spearman correlation between samples
experimentQC heatmeap_PearsonCorr.pdf plot of Pearson correlation between samples
experimentQC sample_mbs.npz array of multiple BAM summaries
crossReads *.cc.plot.pdf Plot of cross-correlation to assess signal-to-noise ratios
crossReads *.cc.qc cross-correlation metrics. File HEADER
callPeaksMACS pooled/*pooled.fc_signal.bw bigwig data file; raw fold enrichment of sample/control
callPeaksMACS pooled/*pooled_peaks.xls Excel file of peaks
callPeaksMACS pooled/*.pvalue_signal.bw bigwig data file; sample/control signal adjusted for pvalue significance
callPeaksMACS pooled/*_pooled.narrowPeak peaks file; see HERE for ENCODE narrowPeak header format
consensusPeaks *.rejected.narrowPeak peaks not supported by multiple testing (replicates and pseudo-replicates)
consensusPeaks *.replicated.narrowPeak peaks supported by multiple testing (replicates and pseudo-replicates)
peakAnnotation *.chipseeker_annotation.tsv annotated narrowPeaks file
peakAnnotation *.chipseeker_pie.pdf pie graph of where narrow annotated peaks occur
peakAnnotation *.chipseeker_upsetplot.pdf upsetplot showing the count of overlaps of the genes with different annotated location
motifSearch *_memechip/index.html interactive HTML link of MEME output
motifSearch sorted-*.replicated.narrowPeak Top 600 peaks sorted by p-value; input for motifSearch
motifSearch *_memechip/combined.meme MEME identified motifs
diffPeaks heatmap.pdf Use only for replicated samples; heatmap of relationship of peak location and peak intensity
diffPeaks normcount_peaksets.txt Use only for replicated samples; peak set values of each sample
diffPeaks pca.pdf Use only for replicated samples; PCA of peak location and peak intensity
diffPeaks *_diffbind.bed Use only for replicated samples; bed file of peak locations between replicates
diffPeaks *_diffbind.csv Use only for replicated samples; CSV file of peaks between replicates
plotProfile plotProfile.png Plot profile of the TSS region
plotProfile computeMatrix.gz Compute Matrix from deeptools to create custom plots other than plotProfile

Common Quality Control Metrics

  • These are the list of files that should be reviewed before continuing on with the CHIPseq experiment. If your experiment fails any of these metrics, you should pause and re-evaluate whether the data should remain in the study.
    1. multiqcReport/multiqc_report.html: follow the ChiP-seq standards HERE;
    2. experimentQC/*_fingerprint.pdf: make sure the plots information is correct for your antibody/input. See HERE for more details.
    3. crossReads/*cc.plot.pdf: make sure your sample data has the correct signal intensity and location. See HERE for more details.
    4. crossReads/*.cc.qc: Column 9 (NSC) should be > 1.1 for experiment and < 1.1 for input. Column 10 (RSC) should be > 0.8 for experiment and < 0.8 for input. See HERE for more details.
    5. experimentQC/coverage.pdf, experimentQC/heatmeap_SpearmanCorr.pdf, experimentQC/heatmeap_PearsonCorr.pdf: See HERE for more details.

Credits

This example worklow is derived from original scripts kindly contributed by the Bioinformatic Core Facility (BICF), in the Department of Bioinformatics.

Please cite in publications: Pipeline was developed by BICF from funding provided by Cancer Prevention and Research Institute of Texas (RP150596).

References