PEPPRO: quality control and processing of nascent RNA profiling data

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Abstract

Nascent RNA profiling is growing in popularity; however, there is no standard analysis pipeline to uniformly process the data and assess quality. Here, we introduce PEPPRO, a comprehensive, scalable workflow for GRO-seq, PRO-seq, and ChRO-seq data. PEPPRO produces uniformly processed output files for downstream analysis and assesses adapter abundance, RNA integrity, library complexity, nascent RNA purity, and run-on efficiency. PEPPRO is restartable and fault-tolerant, records copious logs, and provides a web-based project report. PEPPRO can be run locally or using a cluster, providing a portable first step for genomic nascent RNA analysis.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13059-021-02349-4).

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael Love, Wolfgang Huber, Simon Anders (2014)

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.

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The Sequence Alignment/Map format and SAMtools

Heng Li, Bob Handsaker, Alec Wysoker … (2009)

Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk

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Fast gapped-read alignment with Bowtie 2.

Ben Langmead, Steven L Salzberg (2012)

As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.

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Author and article information

Contributors

Michael J. Guertin: guertin@uchc.edu

Nathan C. Sheffield:

ORCID: http://orcid.org/0000-0001-5643-4068

nsheffield@virginia.edu

Journal

Journal ID (nlm-ta): Genome Biol

Journal ID (iso-abbrev): Genome Biol

Title: Genome Biology

Publisher: BioMed Central (London )

ISSN (Print): 1474-7596

ISSN (Electronic): 1474-760X

Publication date (Electronic): 15 May 2021

Publication date PMC-release: 15 May 2021

Publication date Collection: 2021

Volume: 22

Electronic Location Identifier: 155

Affiliations

[1 ]GRID grid.27755.32, ISNI 0000 0000 9136 933X, Center for Public Health Genomics, University of Virginia, ; Charlottesville, USA

[2 ]GRID grid.27755.32, ISNI 0000 0000 9136 933X, Department of Biochemistry and Molecular Genetics, University of Virginia, ; Charlottesville, USA

[3 ]GRID grid.27755.32, ISNI 0000 0000 9136 933X, Department of Public Health Sciences, University of Virginia, ; Charlottesville, USA

[4 ]GRID grid.27755.32, ISNI 0000 0000 9136 933X, Department of Biomedical Engineering, University of Virginia, ; Charlottesville, USA

Author information

Nathan C. Sheffield http://orcid.org/0000-0001-5643-4068

Article

Publisher ID: 2349

DOI: 10.1186/s13059-021-02349-4

PMC ID: 8126160

PubMed ID: 33992117

SO-VID: e3292fa9-fd5a-4453-bb63-53d509094aa2

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 28 February 2020

Date accepted : 12 April 2021

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;

Award ID: GM128635

Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;

Award ID: GM128636

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ScienceOpen disciplines: Genetics

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ScienceOpen disciplines: Genetics

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PEPPRO: quality control and processing of nascent RNA profiling data

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Most cited references 28

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

The Sequence Alignment/Map format and SAMtools

Fast gapped-read alignment with Bowtie 2.

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