Evidence map›Paper›PMID 23412978›Full record

ArticleProteomics2013

A two-step database search method improves sensitivity in peptide sequence matches for metaproteomics and proteogenomics studies.

Pratik Jagtap, Jill Goslinga, Joel A Kooren, Thomas McGowan, Matthew S Wroblewski, Sean L Seymour, Timothy J Griffin

Abstract read
In one paragraph

Article in Proteomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
98citing papers in PubMed, 1 pooled it
–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

98 citing papers in PubMed, 1 synthesis or guideline pooled it.

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Pratik JagtapMinnesota Supercomputing Institute, Minneapolis, MN, USA. pratik@msi.umn.edu
Jill Goslinga
Joel A Kooren
Thomas McGowan
Matthew S Wroblewski
Sean L Seymour
Timothy J Griffin

Funding

TRAINING FOR FUTURE BIOTECHNOLOGY DEVELOPMENTT32GM008347 · NIGMS · UNIVERSITY OF MINNESOTA TWIN CITIES · PI SCHMIDT-DANNERT, CLAUDIA · 1990 to 2021
$11.0M
Characterizing Oral Cancer Progression via Saliva ProteomicsR01DE017734 · NIDCR · UNIVERSITY OF MINNESOTA · PI GRIFFIN, TIMOTHY J. · 2007 to 2010
$1.4M
NIDCR NIH HHS 1R01 DE17734NIDCR NIH HHS R01 DE017734NIGMS NIH HHS T32 GM008347
6 · The paper itself

Abstract

Large databases (>10(6) sequences) used in metaproteomic and proteogenomic studies present challenges in matching peptide sequences to MS/MS data using database-search programs. Most notably, strict filtering to avoid false-positive matches leads to more false negatives, thus constraining the number of peptide matches. To address this challenge, we developed a two-step method wherein matches derived from a primary search against a large database were used to create a smaller subset database. The second search was performed against a target-decoy version of this subset database merged with a host database. High confidence peptide sequence matches were then used to infer protein identities. Applying our two-step method for both metaproteomic and proteogenomic analysis resulted in twice the number of high confidence peptide sequence matches in each case, as compared to the conventional one-step method. The two-step method captured almost all of the same peptides matched by the one-step method, with a majority of the additional matches being false negatives from the one-step method. Furthermore, the two-step method improved results regardless of the database search program used. Our results show that our two-step method maximizes the peptide matching sensitivity for applications requiring large databases, especially valuable for proteogenomics and metaproteomics studies.

Indexed as

Amino Acid SequenceDatabases, ProteinSearch EngineAlgorithmsExpressed Sequence TagsGenomicsHumansMetagenomeMouth MucosaPeptidesProteomicsSalivaSensitivity and SpecificitySoftwareTandem Mass SpectrometryPeptides

Identifiers

PMID23412978
PMCPMC3633484

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.