ArticleNature communications2022
SMAP is a pipeline for sample matching in proteogenomics.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 7 citations in OpenAlex.
- High-resolution multi-omics enhances prediction and detection of smORF-encoded proteins in the human gut microbiome.Nature communications · 2026Article
- Genetic modulation of protein expression in rat brain.iScience · 2025Article
- Genetic regulation of human brain proteome reveals proteins implicated in psychiatric disorders.Molecular psychiatry · 2024Article
- Multi-omic atlas of the parahippocampal gyrus in Alzheimer's disease.Scientific data · 2023Article
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Authors and funding
13 authors at 6 institutions in 2 countries.
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Abstract
The integration of genomics and proteomics data (proteogenomics) holds the promise of furthering the in-depth understanding of human disease. However, sample mix-up is a pervasive problem in proteogenomics because of the complexity of sample processing. Here, we present a pipeline for Sample Matching in Proteogenomics (SMAP) to verify sample identity and ensure data integrity. SMAP infers sample-dependent protein-coding variants from quantitative mass spectrometry (MS), and aligns the MS-based proteomic samples with genomic samples by two discriminant scores. Theoretical analysis with simulated data indicates that SMAP is capable of uniquely matching proteomic and genomic samples when ≥20% genotypes of individual samples are available. When SMAP was applied to a large-scale dataset generated by the PsychENCODE BrainGVEX project, 54 samples (19%) were corrected. The correction was further confirmed by ribosome profiling and chromatin sequencing (ATAC-seq) data from the same set of samples. Our results demonstrate that SMAP is an effective tool for sample verification in a large-scale MS-based proteogenomics study. SMAP is publicly available at https://github.com/UND-Wanglab/SMAP , and a web-based version can be accessed at https://smap.shinyapps.io/smap/ .
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