Evidence map›Paper›PMID 25301683›Full record

ArticleJournal of proteome research2014

Flexible and accessible workflows for improved proteogenomic analysis using the Galaxy framework.

Pratik D Jagtap, James E Johnson, Getiria Onsongo, Fredrik W Sadler, Kevin Murray, Yuanbo Wang, Gloria M Shenykman, Sricharan Bandhakavi, Lloyd M Smith, Timothy J Griffin

Abstract read
In one paragraph

Article in Journal of proteome research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Bioinformatic Workflows for Metaproteomics.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Spritz: A Proteogenomic Database Engine.Journal of proteome research · 2021
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
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  20. 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.

Pratik D JagtapCenter for Mass Spectrometry and Proteomics, University of Minnesota , 43 Gortner Laboratory, 1479 Gortner Avenue, St. Paul, Minnesota 55108, United States.
James E Johnson
Getiria Onsongo
Fredrik W Sadler
Kevin Murray
Yuanbo Wang
Gloria M Shenykman
Sricharan Bandhakavi
Lloyd M Smith
Timothy J Griffin

Funding

Institutional Training in the Genomic SciencesT32HG002760 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI Qiongshi Lu · 2003 to 2026
$17.7M
Wisconsin Center of Excellence in Genomics ScienceP50HG004952 · NHGRI · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI OLIVIER, MICHAEL · 2009 to 2013
$13.0M
NHGRI NIH HHS 1P50HG004952NHGRI NIH HHS 5T32HG002760
6 · The paper itself

Abstract

Proteogenomics combines large-scale genomic and transcriptomic data with mass-spectrometry-based proteomic data to discover novel protein sequence variants and improve genome annotation. In contrast with conventional proteomic applications, proteogenomic analysis requires a number of additional data processing steps. Ideally, these required steps would be integrated and automated via a single software platform offering accessibility for wet-bench researchers as well as flexibility for user-specific customization and integration of new software tools as they emerge. Toward this end, we have extended the Galaxy bioinformatics framework to facilitate proteogenomic analysis. Using analysis of whole human saliva as an example, we demonstrate Galaxy's flexibility through the creation of a modular workflow incorporating both established and customized software tools that improve depth and quality of proteogenomic results. Our customized Galaxy-based software includes automated, batch-mode BLASTP searching and a Peptide Sequence Match Evaluator tool, both useful for evaluating the veracity of putative novel peptide identifications. Our complex workflow (approximately 140 steps) can be easily shared using built-in Galaxy functions, enabling their use and customization by others. Our results provide a blueprint for the establishment of the Galaxy framework as an ideal solution for the emerging field of proteogenomics.

Indexed as

DNA, ComplementaryGene LibraryHumansProteomeProteomicsReading FramesSalivaSoftwareDNA, ComplementaryProteomecustomized database generationpeptide corresponding to a novel proteoformpeptide-spectral match evaluationproteogenomicssalivary proteinsworkflows

Identifiers

PMID25301683
PMCPMC4261978

What OpenQuestion holds

Textmetadata
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.