wrProteo: Proteomics Data Analysis Functions
Data analysis of proteomics experiments by mass spectrometry is supported by this collection of functions mostly dedicated to the analysis of (bottom-up) quantitative (XIC) data.
Fasta-formatted proteomes (eg from UniProt Consortium <doi:10.1093/nar/gky1049>) can be read with automatic parsing and multiple annotation types (like species origin, abbreviated gene names, etc) extracted.
Initial results from multiple software for protein (and peptide) quantitation can be imported (to a common format):
Fragpipe(da Veiga et al 2020, <doi:10.1038/s41592-020-0912-y>), MaxQuant (Tyanova et al 2016 <doi:10.1038/nprot.2016.136>), MassChroq (Valot et al 2011] <doi:10.1002/pmic.201100120>), ProteomeDiscoverer,
OpenMS (<doi:10.1038/nmeth.3959>) and Proline (Bouyssie et al 2020 <doi:10.1093/bioinformatics/btaa118>). Meta-data provided in sdrf format can be integrated to the analysis.
Quantitative proteomics measurements frequently contain multiple NA values, due to physical absence of given peptides in some samples, limitations in sensitivity or other reasons.
The functions provided here help to inspect graphically the data to investigate the nature of NA-values via their respective replicate measurements
and to help/confirm the choice of NA-replacement by low random values.
Dedicated filtering and statistical testing using the framework of package 'limma' <doi:10.18129/B9.bioc.limma> can be run, enhanced by multiple rounds of NA-replacements to provide robustness towards rare stochastic events.
Multi-species samples, as frequently used in benchmark-tests (eg Navarro et al 2016 <doi:10.1038/nbt.3685>, Ramus et al 2016 <doi:10.1016/j.jprot.2015.11.011>), can be run with special options separating
the data into sub-groups during normalization and testing. Subsequently, ROC curves (Hand and Till 2001 <doi:10.1023/A:1010920819831>) can be constructed to compare multiple analysis approaches.
As detailed example the data-set from Ramus et al 2016 <doi:10.1016/j.jprot.2015.11.011>) quantified by MaxQuant, ProteomeDiscoverer,
and Proline is provided with a detailed analysis of heterologous spike-in proteins.
| Version: |
1.7.0.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
grDevices, graphics, knitr, limma, stats, utils, wrMisc (≥
1.10.0) |
| Suggests: |
data.table, fdrtool, kableExtra, MASS, RColorBrewer, readxl, ROTS, rmarkdown, R.utils, sm, wrGraph (≥ 1.3.0) |
| Published: |
2022-11-24 |
| Author: |
Wolfgang Raffelsberger [aut, cre] |
| Maintainer: |
Wolfgang Raffelsberger <w.raffelsberger at gmail.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| In views: |
MissingData |
| CRAN checks: |
wrProteo results |
Documentation:
Downloads:
Reverse dependencies:
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