PeCorA
is short for "Peptide Correlation Analysis", which is an R package that enables detection of discordant peptide quantities in shotgun proteomics data. The package also contains a number of published proteomics datasets processed with different processing tools to demonstrate the workflow.
Please find the relevant preprint here: https://doi.org/10.1101/2020.08.21.261818
You can install PeCorA
from github downloading the package by cloning
the repository.
$ git clone https://github.com/jessegmeyerlab/PeCorA.git
$ R CMD INSTALL PeCorA-master
Alternatively you can install PeCorA
directly from R using devtools:
library(devtools)
install_github("jessegmeyerlab/PeCorA")
Or you can installPeCorA
from CRAN by typing in R:
install.packages(“PeCorA”)
Once installed, load the package by writing in the console
library(PeCorA)
Currently, there are three datasets available in PeCorA
.
Data | Description |
---|---|
PeCorA_noZ | Primary mouse microglia dataset (PXD014466) |
input.dda.iprg.pg | BRF Proteome Informatics Research Group (iPRG) 2015 Study: Detection of Differentially Abundant Proteins in Label-Free Quantitative LC-MS/MS Experiments |
Covid_peptides | Large-scale proteomic Analysis of COVID-19 Severity |
Data available in the package is loaded into the R
session using the
load
function; for instance, to get the DDA iPRG data from Choi et
al 2017:
data("input.dda.iprg.pg")
To get more information about a dataset, see its manual page.
?input.dda.iprg.pg
PeCorA requires a filename.csv file containing table in long format of peptides, their quantities, and the proteins they belong to. This file must at least contain the following columns (check spelling and letter case):
“Condition” - group labels of the conditions. Can be more than 2 but must be at least 2. “Peptide.Modified.Sequence” - peptide sequence including any modifications “BioReplicate” - numbering for biological replicates “Protein” - protein membership for each peptide
You may need to transform your data into PeCorA-ready format. For
example ransform peptides.txt output of MaxQuant into t use function
import_preprocessed_for_PeCorA
.
The main function of the package is called PeCorA
, which fits a linear
model with interaction between peptides and biological treatment groups.
See Vignette for complete workflow.
If you have any questions or suggestions please contact us:
Maria Dermit : maria.dermit at qmul.ac.uk
Jesse Meyer: jesmeyer at mcw.edu