ArticleSTAR protocols2021
RHybridFinder: An R package to process immunopeptidomic data for putative hybrid peptide discovery.
Article in STAR protocols, 2021. 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
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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.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines.Nature communications · 2024Article
- Unlocking the potential of microfluidics in mass spectrometry-based immunopeptidomics for tumor antigen discovery.Cell reports methods · 2023Review
- Using mass spectrometry to identify neoantigens in autoimmune diseases: The type 1 diabetes example.Seminars in immunology · 2023Review
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
Abstract
Identification of proteasomal spliced peptides (PSPs) by mass spectrometry (MS) is not possible with traditional search engines. Here, we provide a protocol for running RHybridFinder (RHF), an R package for the computational inference of putative PSPs detected by MS. RHF extracts high confidence scored de novo sequenced peptides identified by PEAKS software. Those peptides are then matched to protein databases to infer cis- or trans-spliced major histocompatibility complex (MHC)-associated peptides. RHF is relatively fast and straightforward. PSPs have to be validated experimentally. For complete details on the use and execution of the original protocol, please refer to Faridi et al. (2018).
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Registered trials
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