Evidence map›Paper›PMID 29386051›Full record

ArticleGenome biology2018

The proBAM and proBed standard formats: enabling a seamless integration of genomics and proteomics data.

Gerben Menschaert, Xiaojing Wang, Andrew R Jones, Fawaz Ghali, David Fenyö, Volodimir Olexiouk, Bing Zhang, Eric W Deutsch, Tobias Ternent, Juan Antonio Vizcaíno

Abstract readLetter
In one paragraph

Article in Genome biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Proteomics Standards Initiative Extended FASTA Format.Journal of proteome research · 2019
    Article
  7. PDV: an integrative proteomics data viewer.Bioinformatics (Oxford, England) · 2019
    Article
  8. Article
  9. Article
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

10 authors.

Gerben MenschaertDepartment of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure links 653, 9000, Gent, Belgium. Gerben.Menschaert@ugent.be.ORCID 0000-0002-7575-2085
Xiaojing WangGreehey Children's Cancer Research Institute, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA. WANGX11@uthscsa.edu.
Andrew R JonesInstitute of Integrative Biology, University of Liverpool, Liverpool, UK.
Fawaz GhaliInstitute of Integrative Biology, University of Liverpool, Liverpool, UK.
David FenyöDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.
Volodimir OlexioukDepartment of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure links 653, 9000, Gent, Belgium.
Bing ZhangLester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, USA.
Eric W DeutschInstitute for Systems Biology, Seattle, WA, USA.
Tobias TernentEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
Juan Antonio VizcaínoEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. juan@ebi.ac.uk.

Funding

TrainingU54EB020406 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TOGA, ARTHUR W · 2014 to 2018
$12.5M
Shortening the development cycle time of Trans Proteomic Pipeline tools with high performance computingR01GM087221 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC, MORITZ, ROBERT L · 2010 to 2021
$6.0M
iPGDAC, An Integrative Proteogenomic Data Analysis Center for CPTACU24CA210954 · NCI · BAYLOR COLLEGE OF MEDICINE · PI ZHANG, BING · 2016 to 2020
$4.9M
Proteogenomic Data Analysis for Cancer Systems Biology and Clinical TranslationU24CA210972 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DING, LI, FENYO, DAVID · 2016 to 2020
$3.3M
Advancing data and metadata standards for proteomics mass spectraR24GM127667 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC · 2017 to 2019
$1.2M
Biotechnology and Biological Sciences Research Council BB/K01997X/1Biotechnology and Biological Sciences Research Council BB/L005239/1Biotechnology and Biological Sciences Research Council (GB) BB/L024225/1Fonds Wetenschappelijk Onderzoek 12A7813Nleidos biomedical research (US) 13XS068NCI NIH HHS U24 CA210954NCI NIH HHS U24CA210954NCI NIH HHS U24CA210972NIBIB NIH HHS U54 EB020406NIBIB NIH HHS U54EB020406NIGMS NIH HHS R01 GM087221NIGMS NIH HHS R01GM087221NIGMS NIH HHS R24 GM127667NIGMS NIH HHS R24GM127667
6 · The paper itself

Abstract

On behalf of The Human Proteome Organization (HUPO) Proteomics Standards Initiative, we introduce here two novel standard data formats, proBAM and proBed, that have been developed to address the current challenges of integrating mass spectrometry-based proteomics data with genomics and transcriptomics information in proteogenomics studies. proBAM and proBed are adaptations of the well-defined, widely used file formats SAM/BAM and BED, respectively, and both have been extended to meet the specific requirements entailed by proteomics data. Therefore, existing popular genomics tools such as SAMtools and Bedtools, and several widely used genome browsers, can already be used to manipulate and visualize these formats "out-of-the-box." We also highlight that a number of specific additional software tools, properly supporting the proteomics information available in these formats, are now available providing functionalities such as file generation, file conversion, and data analysis. All the related documentation, including the detailed file format specifications and example files, are accessible at http://www.psidev.info/probam and at http://www.psidev.info/probed .

Indexed as

SoftwareGene Expression ProfilingGenomicsMass SpectrometryProteomics

Identifiers

PMID29386051
PMCPMC5793360

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.