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CHIPS: A Snakemake pipeline for quality control and reproducible processing of chromatin profiling data

Len Taing, Clara Cousins, Gali Bai, Paloma Cejas, Xintao Qiu, Myles Brown, Clifford A. Meyer, View ORCID ProfileX. Shirley Liu, View ORCID ProfileHenry W. Long, Ming Tang
doi: https://doi.org/10.1101/2021.03.09.434676
Len Taing
1Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
3Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215
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Clara Cousins
1Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
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Gali Bai
1Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
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Paloma Cejas
3Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215
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Xintao Qiu
3Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215
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Myles Brown
3Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215
4Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215
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Clifford A. Meyer
1Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
2Department of Biostatistics, Harvard T.H. Chan School of Public Health
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X. Shirley Liu
1Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
2Department of Biostatistics, Harvard T.H. Chan School of Public Health
3Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215
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  • ORCID record for X. Shirley Liu
Henry W. Long
3Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215
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  • ORCID record for Henry W. Long
  • For correspondence: tangming2005@gmail.com
Ming Tang
1Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
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  • For correspondence: tangming2005@gmail.com
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Abstract

Motivation The chromatin profile measured by ATAC-seq, ChlP-seq, or DNase-seq experiments can identify genomic regions critical in regulating gene expression and provide insights on biological processes such as diseases and development. However, quality control and processing chromatin profiling data involve many steps, and different bioinformatics tools are used at each step. It can be challenging to manage the analysis.

Results We developed a Snakemake pipeline called CHIPS (CHromatin enrichment Processor) to streamline the processing of ChIP-seq, ATAC-seq, and DNase-seq data. The pipeline supports single- and paired-end data and is flexible to start with FASTQ or BAM files. It includes basic steps such as read trimming, mapping, and peak calling. In addition, it calculates quality control metrics such as contamination profiles, PCR bottleneck coefficient, the fraction of reads in peaks, percentage of peaks overlapping with the union of public DNaseI hypersensitivity sites, and conservation profile of the peaks. For downstream analysis, it carries out peak annotations, motif finding, and regulatory potential calculation for all genes. The pipeline ensures that the processing is robust and reproducible.

Availability CHIPS is available at https://bitbucket.org/plumbers/cidc_chips/src/master/

Contact mtang{at}ds.dfci.harvard.edu: henry_long{at}dfci.harvard.edu

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • http://cistrome.org/~lentaing/chips/report/report.html

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted March 10, 2021.
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CHIPS: A Snakemake pipeline for quality control and reproducible processing of chromatin profiling data
Len Taing, Clara Cousins, Gali Bai, Paloma Cejas, Xintao Qiu, Myles Brown, Clifford A. Meyer, X. Shirley Liu, Henry W. Long, Ming Tang
bioRxiv 2021.03.09.434676; doi: https://doi.org/10.1101/2021.03.09.434676
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CHIPS: A Snakemake pipeline for quality control and reproducible processing of chromatin profiling data
Len Taing, Clara Cousins, Gali Bai, Paloma Cejas, Xintao Qiu, Myles Brown, Clifford A. Meyer, X. Shirley Liu, Henry W. Long, Ming Tang
bioRxiv 2021.03.09.434676; doi: https://doi.org/10.1101/2021.03.09.434676

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