ArticleProteomes2024
Assessment of Data-Independent Acquisition Mass Spectrometry (DIA-MS) for the Identification of Single Amino Acid Variants.
Article in Proteomes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Advances in Mass Spectrometry Instrumentation and Methodology for Analysis of Alternative Protein Isoforms.Journal of mass spectrometry : JMS · 2026Review
- Optimization of protein extraction and digestion workflows for proteomic analysis of saliva, salivary stones and kidney stones.Frontiers in molecular biosciences · 2026Article
- Unraveling ADAR-Mediated Protein Recoding: A Proteogenomic Exploration in Model Organisms and Human Pathology.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Proteogenomics integrates genomic and proteomic data to elucidate cellular processes by identifying variant peptides, including single amino acid variants (SAAVs). In this study, we assessed the capability of data-independent acquisition mass spectrometry (DIA-MS) to identify SAAV peptides in HeLa cells using various search engine pipelines. We developed a customised sequence database (DB) incorporating SAAV sequences from the HeLa genome and conducted searches using DIA-NN, Spectronaut, and Fragpipe-MSFragger. Our evaluation focused on identifying true positive SAAV peptides and false positives through entrapment DBs. This study revealed that DIA-MS provides reproducible and comprehensive coverage of the proteome, identifying a substantial proportion of SAAV peptides. Notably, the DIA-MS searches maintained consistent identification of SAAV peptides despite varying sizes of the entrapment DB. A comparative analysis showed that Fragpipe-MSFragger (FP-DIA) demonstrated the most conservative and effective performance, exhibiting the lowest false discovery match ratio (FDMR). Additionally, integrating DIA and data-dependent acquisition (DDA) MS data search outputs enhanced SAAV peptide identification, with a lower false discovery rate (FDR) observed in DDA searches. The validation using stable isotope dilution and parallel reaction monitoring (SID-PRM) confirmed the SAAV peptides identified by DIA-MS and DDA-MS searches, highlighting the reliability of our approach. Our findings underscore the effectiveness of DIA-MS in proteogenomic workflows for identifying SAAV peptides, offering insights into optimising search engine pipelines and DB construction for accurate proteomics analysis. These methodologies advance the understanding of proteome variability, contributing to cancer research and the identification of novel proteoform therapeutic targets.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.