bigbio / pIR

Estimation of isoelectric point of peptides and proteins using Support vector machines
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pIR

An R package to analyze the isoelectric point of peptides and proteins based on experimental values and predicted using different functions. The package provides an statistical framework to analyze the correlation between predicted and expeted values, and it can be use in other contexts.

Installation

First, we need to install devtools:

install.packages("devtools")
library(devtools)

Then we just call

install_github("ypriverol/pIR")
library(pIR)

Examples

=================


# Other different pKSets that can be selected: rodwell, emboss, lehninger, grimsley, patrickios, DtaSelect

library(pIR)
seq <- "GLPRKILCAIAKKKGKCKGPLKLVCKC"
pI <- pIIterative(sequence = seq, pkSetMethod = "solomon")
print(pI)

#The result will be 10.526

#Computing all pI values using Iterative method.

> sequence <- "AADCEVEQWDSDEPIPAK"
> pIvalues <- computeAllIterativeValues(seq = sequence)

#The result will be...

> pIvalues
           method values
1         solomon 3.4161
2         rodwell 3.3749
3          emboss 3.5322
4       lehninger 3.3711
5        grimsley 3.3012
6      patrickios 3.4220
7       DtaSelect 3.7848
8        toseland 3.3571
9       thurlkill 3.4784
10 nozaki_tanford 3.6445

How to cite

Audain, E., Ramos, Y., Hermjakob, H., Flower, D. R., & Perez-Riverol, Y. (2015). Accurate estimation of isoelectric point of protein and peptide based on amino acid sequences. Bioinformatics, btv674. article

Perez-Riverol, Y., Audain, E., Millan, A., Ramos, Y., Sanchez, A., Vizcaíno, J. A., ... & González, L. J. (2012). Isoelectric point optimization using peptide descriptors and support vector machines. Journal of proteomics, 75(7), 2269-2274. article

This library has been used in: