Evidence map›Paper›PMID 38106106›Full record

ArticlebioRxiv : the preprint server for biology2023

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Datasets Built on FragPipe.

Edgar Manriquez-Sandoval, Joy Brewer, Gabriela Lule, Samanta Lopez, Stephen D Fried

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Edgar Manriquez-SandovalDepartment of Chemistry, Johns Hopkins University, Baltimore, MD 21218, USA.ORCID 0000-0001-7284-1237
Joy BrewerDepartment of Chemistry and Biochemistry, Old Dominion University, Norfolk, VA, 23529, USA.ORCID 0000-0003-2758-351X
Gabriela LuleDepartment of Chemistry, Johns Hopkins University, Baltimore, MD 21218, USA.ORCID 0009-0002-9419-9526
Samanta LopezDepartment of Chemistry, Johns Hopkins University, Baltimore, MD 21218, USA.ORCID 0009-0001-6768-8802
Stephen D FriedDepartment of Chemistry, Johns Hopkins University, Baltimore, MD 21218, USA.ORCID 0000-0003-2494-2193

Funding

Program of Molecular BiophysicsT32GM135131 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Karen G. Fleming · 2020 to 2026
$5.4M
Watching Proteins Fold (or Misfold) in vivo with Mass SpectrometryDP2GM140926 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI FRIED, STEPHEN DAVID · 2020 to 2020
$2.3M
NIGMS NIH HHS DP2 GM140926NIGMS NIH HHS T32 GM135131
6 · The paper itself

Abstract

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage the fast, sensitive, and accurate search and label-free quantification algorithms in FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a new data merging scheme (from ions to cut-sites) and a protein-centric multiple hypothesis correction scheme, collectively enabling processed LiP-MS datasets to be more robust and less redundant. These improvements substantially strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. As a final feature, FLiPPR facilitates the collection of structural metadata to identify correlations between experiments and structural features. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

Identifiers

PMID38106106
PMCPMC10723326

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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.