README.Rmd

Peptide correlation analysis
============================

## The `PeCorA` package


`PeCorA` is a package that contains a number of functions to detect discordant peptide quantities in shotgun proteomics sata by Peptide Correlation Analysis. The package also contains a number of published proteomics datasets processed with different processing tools. 


### Install
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:

```{r}
library(devtools)
install_github("jessegmeyerlab/PeCorA")
```

Or you can install`PeCorA` from CRAN by typing in R: install.packages("PeCorA")

Once installed, load the package by writing in the console

```{r}
library(PeCorA)
```

### Available datasets

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|

### Loading data

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](https://pubmed.ncbi.nlm.nih.gov/27990823/):

```{r}
data("input.dda.iprg.pg")
```

To get more information about a dataset, see its manual page.

```{r}
?input.dda.iprg.pg
```

### How to use
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`.

### Functions
The main function of the package is called `PeCorA`, which fits a linear model with interaction between peptides and biological treatment groups.


### Vignette 
See [Vignette](https://github.com/demar01/PeCorA/blob/master/vignettes/PeCorA_vignette.pdf) for complete workflow.


### Contact
If you have any questions or suggestions please contact us:

Maria Dermit : maria.dermit at qmul.ac.uk 

Jesse Meyer: jesmeyer at mcw.edu