DPLabR

The goal of DPLabR is to collect custom functions written in different .R files in different projects in the same place. The need came up when I realized how hard it would be to keep track of different versions of the same custom functions scattered around different .R files. So i decided to grop them here.

The DPLabR’s functions cover different omics technologies, namely Bulk RNAseq, ChIPseq, scRNAseq and Proteomics. It’s probably not straight forward to remember which function belong to which tech, so i’ll try to be as exaustive as possible when writing the documentation.

Installation

Get the latest stable R release from CRAN. Note that you need to have R >= 4.3. You can get devel version of DPLabR from GitHub with:

# install.packages("devtools")
devtools::install_github("AndreaMariani-AM/DPLabR")

Example (undre dev)

This is a basic example which shows you how to solve a common problem for each tech.

Combinatorial Indexing

If you have run our pipeline based on Alevin-fry pipeline then an intuitive to lead your experiment is to leverage DPLabR::load_split_seq, which internally uses fishpond::loadFry function and does some additional things like standardizing gene names and creating an object based on the specie you specify.
Then, there’s an optional function to add a sample info on the experiment if this is provided. Read the docs for more

# Load expr
sce <- load_split_seq(fryDir, outputFormat, expType)
# Add sample info
sce <- add_sample_info(sce, fryDir, bc_filter)

ChIPseq

Some routine analysis you might want to do, is quantify your ChIPseq experiments for some features. We use get_coverage_custom function to compute average scores from a list of bigwig files across a list of genomic regions in BED format.