DROPA is a fully customizable peak-annotation tool optimized for DRIP-seq peaks, which allows a finest gene annotation based on gene expression information. Its output can easily be integrated into pipelines to perform downstream analyses, while useful and informative summary plots and statistical enrichment tests can be produced. Although it is developed for R-loop mapping, DROPA can also be used to annotate other genomic sequencing data as in the case of Histone marks IP-seq, DNAse-seq, FAIRE-seq.
- Python:
DROPA core is written in Python 3.5 You can install Python directly from the Console with the command:
sudo apt-get install python3
sudo apt-get install python-dev
Install Pip to get the packages that DROPA needs for running.
sudo apt-get install python3-pip
Here is the list of required packages:
- numpy(v. 1.16.1)
- pandas(v. 0.24.1)
- tqdm(v. 4.31.1)
- intervaltree(v. 3.0.2)
- matplotlib(v. 3.0.3)
- upsetplot(v. 0.2.1)
- argparse(v. 1.4.0)
To install them:
pip3 install numpy pandas tqdm intervaltree matplotlib argparse
pip3 install upsetplot
- Bedtools
Bedtools is required specifically for the creation of random data. To install bedtools:
sudo apt-get install bedtools
Bedtools shuffle requires a genome size file structured as follow:
<ChromosomeName><TAB><ChromosomeSize>
For hg19, mm9 and mm10 this file is provided. Check the Wiki for other genome size files creation.
DROPA was tested on a machine running Ubuntu OS (vers. 16.04 LTS and 18.04 LTS)
As input, DROPA requires three files, which are:
● A file containing query peak locations in Browser Extensible Data (BED) format (BED6 and BED12 are supported); BED file must be sorted by chromosome.
● A reference set containing information about genes features (5’UTR, 3’UTR, Coding Exons) in BED format and a gene reference in BED12 format; Reference sets for hg19 (Ensembl, UCSCgenes and RefSeq) and RefSeq for mm9 and mm10 are provided. Check the Wiki for custom reference sets creation.
● A gene expression table containing the name of each gene in the reference set and its expression value (FPKM, TPM, microarray expression value, etc.), structured as follow:
<GeneName><TAB><ExprValue>
If this file is not provided, then DROPA skips the gene expression evaluation and annotates each query peak to the gene with the largest overlap.
To test the program (from installation folder):
python3 DROPA_v1.0.0.py -ref GeneReference/hg19_RefSeq/ -o TEST -ex Test_hg19_DRIP_Expression -shuffle 2 -gsize GeneReference/hg19.genome Test_hg19_DRIP_peaks.bed
Check the DROPA wiki for further informations.
Russo M, De Lucca B, Flati T, Gioiosa S, Chillemi G, Capranico G. DROPA: DRIP-seq optimized peak annotator. BMC Bioinformatics. 2019;20(1):414. doi:10.1186/s12859-019-3009-9