PBLMM: Peptide-based linear mixed models for differential expression analysis of shotgun proteomics data
- Here, we present a peptide-based linear mixed models tool—PBLMM, a standalone desktop application for differential expression analysis of proteomics data. We also provide a Python package that allows streamlined data analysis workflows implementing the PBLMM algorithm. PBLMM is easy to use without scripting experience and calculates differential expression by peptide-based linear mixed regression models. We show that peptide-based models outperform classical methods of statistical inference of differentially expressed proteins. In addition, PBLMM exhibits superior statistical power in situations of low effect size and/or low sample size. Taken together our tool provides an easy-to-use, high-statistical-power method to infer differentially expressed proteins from proteomics data.
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| Author: | Kevin KlannORCiDGND, Christian MünchORCiD |
|---|---|
| URN: | urn:nbn:de:hebis:30:3-754982 |
| DOI: | https://doi.org/10.1002/jcb.30225 |
| ISSN: | 1097-4644 |
| ISSN: | 1547-9366 |
| ISSN: | 1547-1748 |
| Parent Title (English): | Journal of cellular biochemistry |
| Publisher: | Wiley-Liss |
| Place of publication: | New York, NY |
| Document Type: | Article |
| Language: | English |
| Date of Publication (online): | 2022/02/07 |
| Date of first Publication: | 2022/02/07 |
| Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
| Release Date: | 2023/09/15 |
| Tag: | bioinformatics; data analysis; differential expression; proteomics; statistics |
| Volume: | 123 |
| Issue: | 3 |
| Page Number: | 7 |
| First Page: | 691 |
| Last Page: | 696 |
| Note: | The source code and implementations are made freely accessible via Github under https://github.com/klannk/ mssuite and https://github.com/klannk/Peptide_based_LMM. All proteomics data is will be shared upon request. |
| HeBIS-PPN: | 512980403 |
| Institutes: | Medizin |
| Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
| 6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit | |
| Sammlungen: | Universitätspublikationen |
| Licence (German): |  Creative Commons - CC BY - Namensnennung 4.0 International |
