Package: ProteoMM 1.25.0
ProteoMM: Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform
ProteoMM is a statistical method to perform model-based peptide-level differential expression analysis of single or multiple datasets. For multiple datasets ProteoMM produces a single fold change and p-value for each protein across multiple datasets. ProteoMM provides functionality for normalization, missing value imputation and differential expression. Model-based peptide-level imputation and differential expression analysis component of package follows the analysis described in “A statistical framework for protein quantitation in bottom-up MS based proteomics" (Karpievitch et al. Bioinformatics 2009). EigenMS normalisation is implemented as described in "Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition." (Karpievitch et al. Bioinformatics 2009).
Authors:
ProteoMM_1.25.0.tar.gz
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ProteoMM.pdf |ProteoMM.html✨
ProteoMM/json (API)
NEWS
# Install 'ProteoMM' in R: |
install.packages('ProteoMM', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- hs_peptides - Hs_peptides - peptide-level intensities for human
- mm_peptides - Mm_peptides - peptide-level intensities for mouse
On BioConductor:ProteoMM-1.25.0(bioc 3.21)ProteoMM-1.24.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
immunooncologymassspectrometryproteomicsnormalizationdifferentialexpression
Last updated 23 days agofrom:19b533b01c. Checks:OK: 1 NOTE: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 19 2024 |
R-4.5-win | NOTE | Nov 19 2024 |
R-4.5-linux | NOTE | Nov 19 2024 |
R-4.4-win | NOTE | Nov 19 2024 |
R-4.4-mac | NOTE | Nov 19 2024 |
R-4.3-win | NOTE | Nov 19 2024 |
R-4.3-mac | NOTE | Nov 19 2024 |
Exports:convert_log2eig_norm1eig_norm2eigen_pig.testget_presAbs_protsmake_intencitiesmake_metamakeLMFormulaMBimputepeptideLevel_DEpeptideLevel_PresAbsDEplot_3_pep_trends_NOfileplot_volcanoplot_volcano_wLabprot_level_multi_partprot_level_multiMat_PresAbssubset_proteins
Dependencies:AnnotationDbiaskpassBiobaseBiocFileCacheBiocGenericsbiomaRtBiostringsbitbit64blobcachemclicolorspacecpp11crayoncurlDBIdbplyrdigestdplyrfansifarverfastmapfilelockgdatagenericsGenomeInfoDbGenomeInfoDbDataggplot2ggrepelgluegtablegtoolshmshttrhttr2IRangesisobandjsonliteKEGGRESTlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplogrpngprettyunitsprogresspurrrR6rappdirsRColorBrewerRcpprlangRSQLiteS4VectorsscalesstringistringrsystibbletidyrtidyselectUCSC.utilsutf8vctrsviridisLitewithrxml2XVectorzlibbioc