preTEKRABber pipeline

Intro

This pipeline is to generate genes and transposable elements (TEs) from fastq.gz paired-end files. Pipeline includes steps:

1. Use fastp to remove low quality reads and trimmed adapters
2. Use STAR to align reads to reference genome
3. Use TEtranscripts to quantify the expression of genes and transposable elements

The output will be saved inside a newly created folder ./results after running the snakemake pipeline. The count table, which has the suffix .cntTable will be used for down-stream analysis using TEKRABber.

How to use

1. Install conda, and create a conda environment that can run snakemake (v7.25.0).
2. Clone this repository to your working directory
3. In this clone-repo, create a data/ folder that you put all of your fastq.gz files in it
4. Use the create_yaml.py script to create a config file for snakemake to run

python create_yaml.py -outdir <your_out_put_dir_path> -yaml <your_config_yaml_file_name>

5. If we want to execute snakemake in your command line, you can:

snakemake -s preTEKRABber.snake --configfile your-config.yaml -c 1

If you prefer to run it in cluster, for example, using slurm, you can modified the runSnake.sh script and then:

sbatch runSnake.sh

6. The results will be saved inside a new create folder ./results in this repo.

Package version

A more detailed package version can be found in the yml files inside the envs/ repo. In brief:

snakemake==7.25.0
fastp==0.12.4
star==2.7.10b
tetranscripts==2.2.3

Others

1. envs folder has the conda env setting for packages
2. others folder has some modified substracted snakefiles from the preTEKRABber.snake for certain usage. It is recommend that you start from the preTEKRABber.snake.