Evidence map›Paper›PMID 33410471›Full record

ArticleGigaScience2021

PM4NGS, a project management framework for next-generation sequencing data analysis.

Roberto Vera Alvarez, Lorinc Pongor, Leonardo Mariño-Ramírez, David Landsman

Abstract read
In one paragraph

Article in GigaScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Roberto Vera AlvarezComputational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, 8900 Rockville Pike, NIH, Bethesda, MD 20894, USA.
Lorinc PongorDevelopmental Therapeutics Branch and Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, 8900 Rockville Pike, NIH, Bethesda, MD 20894, USA.
Leonardo Mariño-RamírezDivision of Intramural Research, National Institute on Minority Health and Health Disparities, 8900 Rockville Pike, NIH, Bethesda, MD 20894, USA.
David LandsmanComputational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, 8900 Rockville Pike, NIH, Bethesda, MD 20894, USA.

Funding

Genome Assemblies, Analyses, and ComparisonsZIALM082713 · NLM · NATIONAL LIBRARY OF MEDICINE · PI LANDSMAN, DAVID · 2013 to 2025
$3.5M
Genomics and Biobank Research for Health EquityZIAMD000018 · NIMHD · NATIONAL INSTITUTE ON MINORITY HEALTH AND HEALTH DISPARITIES · PI MARIÑO-RAMÍREZ, LEONARDO · 2020 to 2025
$2.7M
Epidemiology and Genomics of Health DisparitiesZIAMD000016 · NIMHD · NATIONAL INSTITUTE ON MINORITY HEALTH AND HEALTH DISPARITIES · PI MARINO-RAMIREZ, LEONARDO · 2019 to 2021
$1.6M
6 · The paper itself

Abstract

backgroundFAIR (Findability, Accessibility, Interoperability, and Reusability) next-generation sequencing (NGS) data analysis relies on complex computational biology workflows and pipelines to guarantee reproducibility, portability, and scalability. Moreover, workflow languages, managers, and container technologies have helped address the problem of data analysis pipeline execution across multiple platforms in scalable ways.

findingsHere, we present a project management framework for NGS data analysis called PM4NGS. This framework is composed of an automatic creation of a standard organizational structure of directories and files, bioinformatics tool management using Docker or Bioconda, and data analysis pipelines in CWL format. Pre-configured Jupyter notebooks with minimum Python code are included in PM4NGS to produce a project report and publication-ready figures. We present 3 pipelines for demonstration purposes including the analysis of RNA-Seq, ChIP-Seq, and ChIP-exo datasets.

conclusionsPM4NGS is an open source framework that creates a standard organizational structure for NGS data analysis projects. PM4NGS is easy to install, configure, and use by non-bioinformaticians on personal computers and laptops. It permits execution of the NGS data analysis on Windows 10 with the Windows Subsystem for Linux feature activated. The framework aims to reduce the gap between researcher in experimental laboratories producing NGS data and workflows for data analysis. PM4NGS documentation can be accessed at https://pm4ngs.readthedocs.io/.

Indexed as

Data AnalysisSoftwareComputational BiologyHigh-Throughput Nucleotide SequencingReproducibility of ResultsChIP-exoChIP-SeqFAIR, RNA-SeqNGS pipelinesNGS sequence analysisopen source frameworks

Identifiers

PMID33410471
PMCPMC7788391

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.