customProDB: an R package to generate customized protein databases from RNA-Seq data for proteomics search
1Department of Biomedical Informatics, Vanderbilt-Ingram Cancer Center and Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Bioinformatics (Oxford, England)
|September 24, 2013
Summary
Generating custom protein databases from RNA-Seq data improves mass spectrometry-based proteomics. The customProDB R package facilitates the creation of these sample-specific databases, enhancing protein identification by integrating genomics and proteomics.
Area of Science:
- Proteomics
- Genomics
- Bioinformatics
Background:
- Mass spectrometry-based proteomics relies heavily on database searching for protein identification.
- Sample-specific protein databases derived from RNA-Seq data can more accurately represent the actual protein content of samples.
- RNA-Seq data reveals variations like single nucleotide variations, insertions, deletions, and novel junctions, leading to more comprehensive and personalized protein databases.
Purpose of the Study:
- To introduce customProDB, an R package for generating customized protein databases from RNA-Seq data.
- To simplify the process of creating sample-specific protein databases for proteomics searches.
- To bridge the gap between genomics and proteomics, enabling better cross-omics data integration.
Main Methods:
- Development of the customProDB R package.
- Utilizing RNA-Seq data to identify genetic variations and novel junctions.
- Generating customized protein databases incorporating these variations.
Main Results:
- The customProDB package enables the straightforward generation of customized protein databases.
- These databases are more complete and sample-specific due to the inclusion of RNA-Seq-derived variations.
- Improved protein identification in mass spectrometry-based proteomics studies is achieved.
Conclusions:
- customProDB facilitates the integration of genomics and proteomics data.
- The package enhances protein identification accuracy by providing tailored protein databases.
- This approach supports more robust and comprehensive proteomic analyses.
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