- recipe bioconductor-proteomm
Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform
- Homepage:
https://bioconductor.org/packages/3.16/bioc/html/ProteoMM.html
- License:
MIT
- Recipe:
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).
- package bioconductor-proteomm¶
-
- Versions:
1.16.0-0
,1.12.0-0
,1.10.0-0
,1.8.0-1
,1.8.0-0
,1.6.0-0
,1.4.0-0
,1.2.0-1
,1.0.0-0
- Depends:
bioconductor-biomart
>=2.54.0,<2.55.0
r-base
>=4.2,<4.3.0a0
- Required By:
Installation
With an activated Bioconda channel (see set-up-channels), install with:
conda install bioconductor-proteomm
and update with:
conda update bioconductor-proteomm
or use the docker container:
docker pull quay.io/biocontainers/bioconductor-proteomm:<tag>
(see bioconductor-proteomm/tags for valid values for
<tag>
)
Download stats¶
Link to this page¶
Render an badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-proteomm/README.html)