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PISCES: a package for rapid quantitation and quality control of large scale mRNA-seq datasets

View ORCID ProfileMatthew D. Shirley, Viveksagar K. Radhakrishna, Javad Golji, Joshua M. Korn
doi: https://doi.org/10.1101/2020.12.01.390575
Matthew D. Shirley
1Novartis Institutes for Biomedical Research
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  • For correspondence: matt_d.shirley@novartis.com joshua.korn@novartis.com
Viveksagar K. Radhakrishna
1Novartis Institutes for Biomedical Research
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Javad Golji
1Novartis Institutes for Biomedical Research
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Joshua M. Korn
1Novartis Institutes for Biomedical Research
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  • For correspondence: matt_d.shirley@novartis.com joshua.korn@novartis.com
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Abstract

PISCES eases processing of large mRNA-seq experiments by encouraging capture of metadata using simple textual file formats, processing samples on either a single machine or in parallel on a high performance computing cluster (HPC), validating sample identity using genetic fingerprinting, and summarizing all outputs in analysis-ready data matrices. PISCES consists of two modules: 1) compute cluster-aware analysis of individual mRNA-seq libraries including species detection, SNP genotyping, library geometry detection, and quantitation using salmon, and 2) gene-level transcript aggregation, transcriptional and read-based QC, TMM normalization and differential expression analysis of multiple libraries to produce data ready for visualization and further analysis.

PISCES is implemented as a python3 package and is bundled with all necessary dependencies to enable reproducible analysis and easy deployment. JSON configuration files are used to build and identify transcriptome indices, and CSV files are used to supply sample metadata and to define comparison groups for differential expression analysis using DEseq2. PISCES builds on many existing open-source tools, and releases of PISCES are available on GitHub or the python package index (PyPI).

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/Novartis/pisces

  • https://pypi.org/project/novartis-pisces

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 December 02, 2020.
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PISCES: a package for rapid quantitation and quality control of large scale mRNA-seq datasets
Matthew D. Shirley, Viveksagar K. Radhakrishna, Javad Golji, Joshua M. Korn
bioRxiv 2020.12.01.390575; doi: https://doi.org/10.1101/2020.12.01.390575
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PISCES: a package for rapid quantitation and quality control of large scale mRNA-seq datasets
Matthew D. Shirley, Viveksagar K. Radhakrishna, Javad Golji, Joshua M. Korn
bioRxiv 2020.12.01.390575; doi: https://doi.org/10.1101/2020.12.01.390575

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