protr
Comprehensive toolkit for generating various numerical features of protein sequences described in Xiao et al. (2015) <DOI:10.1093/bioinformatics/btv042> (PDF).
Paper Citation
Formatted citation:
Nan Xiao, Dong-Sheng Cao, Min-Feng Zhu, and Qing-Song Xu. (2015). protr/ProtrWeb: R package and web server for generating various numerical representation schemes of protein sequences. Bioinformatics 31 (11), 1857-1859.
BibTeX entry:
@article{Xiao2015,
author = {Xiao, Nan and Cao, Dong-Sheng and Zhu, Min-Feng and Xu, Qing-Song.},
title = {{protr/ProtrWeb: R package and web server for generating various numerical representation schemes of protein sequences}},
journal = {Bioinformatics},
year = {2015},
volume = {31},
number = {11},
pages = {1857--1859},
doi = {10.1093/bioinformatics/btv042},
issn = {1367-4803},
url = {http://bioinformatics.oxfordjournals.org/content/31/11/1857}
}Installation
To install protr from CRAN:
install.packages("protr")Or try the latest version on GitHub:
# install.packages("devtools")
devtools::install_github("road2stat/protr")Browse the package vignette for a quick-start.
Shiny Web Application
ProtrWeb, the Shiny web application built on protr, can be accessed from http://protr.org.
ProtrWeb is a user-friendly web application for computing the protein sequence descriptors (features) presented in the protr package.
Descriptors List
Commonly used descriptors
Amino acid composition
- Amino acid composition
- Dipeptide composition
- Tripeptide composition
Autocorrelation
- Normalized Moreau-Broto autocorrelation
- Moran autocorrelation
- Geary autocorrelation
CTD
- Composition
- Transition
- Distribution
Conjoint Triad
Quasi-sequence-order descriptors
- Sequence-order-coupling number
- Quasi-sequence-order descriptors
Pseudo amino acid composition
- Pseudo amino acid composition
- Amphiphilic pseudo amino acid composition
Profile-based descriptors
- Profile-based descriptors derived by PSSM (Position-Specific Scoring Matrix)
Proteochemometric (PCM) modeling descriptors
- Scales-based descriptors derived by principal components analysis
- Scales-based descriptors derived by amino acid properties (AAindex)
- Scales-based descriptors derived by 20+ classes of 2D and 3D molecular descriptors (Topological, WHIM, VHSE, etc.)
- Scales-based descriptors derived by factor analysis
- Scales-based descriptors derived by multidimensional scaling
- BLOSUM and PAM matrix-derived descriptors
Similarity Computation
Local and global pairwise sequence alignment for protein sequences:
- Between two protein sequences
- Parallelized pairwise similarity calculation with a list of protein sequences
GO semantic similarity measures:
- Between two groups of GO terms / two Entrez Gene IDs
- Parallelized pairwise similarity calculation with a list of GO terms / Entrez Gene IDs
Miscellaneous tools and datasets
- Retrieve protein sequences from UniProt
- Read protein sequences in FASTA format
- Read protein sequences in PDB format
- Sanity check of the amino acid types appeared in the protein sequences
- Protein sequence segmentation
- Auto cross covariance (ACC) for generating scales-based descriptors of the same length
- 20+ pre-computed 2D and 3D descriptor sets for the 20 amino acids to use with the scales-based descriptors
- BLOSUM and PAM matrices for the 20 amino acids
- Meta information of the 20 amino acids