Description
Massively parallel sequencing of cDNA reverse transcribed from RNA (RNASeq) provides an accurate estimate of the quantity and composition of mRNAs. To characterize the transcriptome through the analysis of RNA-seq data, we developed PRADA. PRADA focuses on the processing and analysis of gene expression estimates, supervised and unsupervised gene fusion identification, and supervised intragenic deletion identification. The BAM files generated by the pipeline are readily compatible with different tools for mutation calling and to obtain read counts for further downstream analysis.
| Items | Values |
|---|---|
| OS requirements | Linux kernel (Ubuntu, Centos) |
| Memory | 30G(Minimum) |
| Software | Conda |
| Language | Python2.7 |
- Download repository
git clone https://github.com/juechenyang/PRADA2.git
- Install conda
- Download conda bash installer here
- Bash command to install:
bash your_path_to_Miniconda3-latest-Linux-x86_64.sh
- Create prada enviroment
- locate the file "prada2.yml" inside "env" folder
- create the conda environment using "prada2.yml"
conda env create -f your_path_to_prada2.yml
- Activate enviroment
conda activate prada
- locate the "download_data.py" script inside the /alignment_inputs
- make sure you have activated prada enviroment in step 4 of installing
- run the following command:
python your_path_to_download_data.py
After the downloading process finished, there should be two files in /alignment_input:
- GRCh38.d1.vd1.fa (reference genome)
- gencode.v22.annotation.gtf (annotation gtf)
- Alignment
python prada2.py --read1 your_path_to_read1_fastq --read2 your_path_to_read2_fastq --outdir your_path_to_output_dir
- Fusion detection
python prada2.py --read1 your_path_to_read1_fastq --read2 your_path_to_read2_fastq --outdir your_path_to_output_dir --fusion
- Get rsem gene expression
python prada2.py --read1 your_path_to_read1_fastq --read2 your_path_to_read2_fastq --outdir your_path_to_output_dir --rsem
- Juechen Yang - Programmer Analyst @ UT Health, San Antonio
- Siyuan Zheng - Assistant Professor @ UT Health, San Antonio - our team
- MIT