PPIP: Automated Software for Identification of Bioactive Endogenous Peptides.
Ming-Qiang RongBao-Jin ZhouRuo ZhouQiong LiaoYong ZengShaohang XuZhonghua LiuPublished in: Journal of proteome research (2018)
Endogenous peptides play an important role in multiple biological processes in many species. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is an important technique for detecting these peptides on a large scale. We present PPIP, which is a dedicated peptidogenomics software for identifying endogenous peptides based on peptidomics and RNA-Seq data. This software automates the de novo transcript assembly based on RNA-Seq data, construction of a protein reference database based on the de novo assembled transcripts, peptide identification, function analysis, and HTML-based report generation. Different function components are integrated using Docker technology. The Docker image of PPIP is available at https://hub.docker.com/r/shawndp/ppip , and the source code under GPL-3 license is available at https://github.com/Shawn-Xu/PPIP . A user manual of PPIP is available at https://shawn-xu.github.io/PPIP .
Keyphrases
- rna seq
- single cell
- tandem mass spectrometry
- liquid chromatography
- ultra high performance liquid chromatography
- amino acid
- data analysis
- simultaneous determination
- high performance liquid chromatography
- mass spectrometry
- high throughput
- high resolution mass spectrometry
- deep learning
- electronic health record
- bioinformatics analysis
- big data
- high resolution
- emergency department
- ms ms
- binding protein
- network analysis