Evidence map›Paper›PMID 22103967›Full record

ArticleJournal of proteome research2012

Protein identification using customized protein sequence databases derived from RNA-Seq data.

Xiaojing Wang, Robbert J C Slebos, Dong Wang, Patrick J Halvey, David L Tabb, Daniel C Liebler, Bing Zhang

Erratum issuedAbstract read
In one paragraph

Article in Journal of proteome research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 96 papers.

0numbers the graph read from it
0cells of the map it votes in
96citing 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

96 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Identification of non-canonical peptides with moPepGen.bioRxiv : the preprint server for biology · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. A practical introduction to holo-omics.Cell reports methods · 2024
    Review
  10. Article
  11. Article
  12. Multi-omic stratification of the missense variant cysteinome.bioRxiv : the preprint server for biology · 2023
    Article
  13. Review
  14. Integrative Proteogenomics Using ProteomeGenerator2.Journal of proteome research · 2023
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

36 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

7 authors.

Xiaojing WangDepartment of Biomedical Informatics,Vanderbilt University School of Medicine , Nashville, Tennessee 37232, United States.
Robbert J C Slebos
Dong Wang
Patrick J Halvey
David L Tabb
Daniel C Liebler
Bing Zhang

Funding

Clinical Proteomic Technology Assessment for CancerU24CA126479 · NCI · VANDERBILT UNIVERSITY · PI LIEBLER, DANIEL C · 2006 to 2010
$7.9M
New Proteomic Algorithms to Identify Mutant or Modified ProteinsR01CA126218 · NCI · VANDERBILT UNIVERSITY · PI TABB, DAVID L · 2006 to 2010
$1.8M
Systems Approach to the Biological Basis of Colon Cancer MetastasesR01GM088822 · NIGMS · VANDERBILT UNIVERSITY · PI BEAUCHAMP, ROBERT DANIEL, ZHANG, BING · 2009 to 2012
$1.5M
NCI NIH HHS R01 CA126218NCI NIH HHS R01CA126218NCI NIH HHS U24 CA126479NIGMS NIH HHS R01 GM088822
6 · The paper itself

Abstract

The standard shotgun proteomics data analysis strategy relies on searching MS/MS spectra against a context-independent protein sequence database derived from the complete genome sequence of an organism. Because transcriptome sequence analysis (RNA-Seq) promises an unbiased and comprehensive picture of the transcriptome, we reason that a sample-specific protein database derived from RNA-Seq data can better approximate the real protein pool in the sample and thus improve protein identification. In this study, we have developed a two-step strategy for building sample-specific protein databases from RNA-Seq data. First, the database size is reduced by eliminating unexpressed or lowly expressed genes according to transcript quantification. Second, high-quality nonsynonymous coding single nucleotide variations (SNVs) are identified based on RNA-Seq data, and corresponding protein variants are added to the database. Using RNA-Seq and shotgun proteomics data from two colorectal cancer cell lines SW480 and RKO, we demonstrated that customized protein sequence databases could significantly increase the sensitivity of peptide identification, reduce ambiguity in protein assembly, and enable the detection of known and novel peptide variants. Thus, sample-specific databases from RNA-Seq data can enable more sensitive and comprehensive protein discovery in shotgun proteomics studies.

Indexed as

Databases, ProteinAmino Acid SequenceBase SequenceCell Line, TumorComputational BiologyGene Expression ProfilingHumansMolecular Sequence DataPeptide MappingPeptidesProteinsRNASequence Analysis, RNATranscriptomePeptidesProteinsRNA

Identifiers

PMID22103967
PMCPMC3727138

What OpenQuestion holds

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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.