Peptide Library Analysis Methods
This package provides a variety of methods for dealing with analysis of peptide library data, including clustering, motif finding, and QSAR model fitting. It is for the R programming language and is described in a recent paper.
Installing From Source (preferred)
To install the latest version from the source here, use:
wget https://github.com/whitead/peplib/archive/master.zip unzip master.zip && rm master.zip R CMD build peplib-master sudo R CMD INSTALL peplib_*.tar.gz
Installing From CRAN
To install from CRAN, type the following command from an R session
Check out the
tutorial.pdf file. It contains
many more details than the brief information below and detailed
The easiest way to load sequences is to use the
seq <- read.sequences("seqfile.txt")
seqfile.txt looks like:
FDDSDF FDSA GGHIT
For most of the methods, it's recommended to have the same length for all sequences.
Calculating Peptide Descriptors
To calculate descriptors on your sequences, use:
seq.desc <- simpleDescriptors(seq)
That will calculate about 10 descriptors. To calculate a few hundred, type
seq.desc <- descriptors(seq)
These descriptors are all relative to glycine. So, for example, molecular weight is not the actual molecular weight but the difference between a given amino acid and glycine.
One nice feature of peplib is the ability to plot sequences with a combination of a finding the substitution distance between sequences and then projecting that distance matrix to 2 dimensions. This may be done like so:
This method also clusters your sequences assuming that there are 3 clusters. That may be changed by adding one argument:
plot(seq, 1) plot(seq, 5)