cisDynet_snakemake

Installation

You can use the following command to configure the environment for the pipeline.

conda env create -f cisDynet_env.yaml

This is a chromatin accessibility data preprocessing process designed for cisDynet package. After running the pipeline, you will get an HTML report.

Report Example

ATAC-seq pipeline

Before running this pipeline, you need to specify the absolute paths to some necessary software in the config.yaml file.

After you have set up your environment and config.yaml file, you can run the process using the following command

snakemake -s cisDynet_snakemake.py -j 20

RNA-seq quantification pipeline

Before you run the RNA quantification pipeline, you should install the bowtie2 and RSEM in your environment. And RSEM index needs to be built first.

snakemake -s rna_pipe_snakemake.py -j 20

Blacklists

The presence of some anomalous regions on the genome allows for extremely high signals. Most of these regions are due to the presence of repetitive sequences, genome assembly errors, and so on. In mammals, “problematic” regions have been inferred and manually checked and called blacklists, and are widely used in the analysis of genomic data. However, there are no systematic blacklists for plant genomes at present. To fill this gap, we used the greenscreen in combination with data collected from our ChIP-Hub database to obtain “problematic” lists for five plant species: Arabidopsis thaliana, rice, maize, soybean, and tomato. (In the blacklist directory)

Publication

Zhu, Tao, Zhou, Xinkai, You, Yuxin, Wang, Lin, He, Zhaohui, and Chen, Dijun. 2023. “ cisDynet: An Integrated Platform for Modeling Gene-Regulatory Dynamics and Networks.” iMeta e152. https://doi.org/10.1002/imt2.152