Introduction

A bioinformatics tool for exRNA biomarker discovery

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Installation

For easy installation, you can use the docker image we provide: exSEEK Docker Image

Alternatively, you can use use singularity or udocker to run the container for Linux kernel < 3 or if you don't have permission to use docker.

Usage

Run exseek.py --help to get basic usage:

usage: exseek.py [-h] --dataset DATASET [--config-dir CONFIG_DIR] [--cluster]
                 [--cluster-config CLUSTER_CONFIG]
                 [--cluster-command CLUSTER_COMMAND]
                 [--singularity SINGULARITY]
                 [--singularity-wrapper-dir SINGULARITY_WRAPPER_DIR]
                 {quality_control,prepare_genome,mapping,count_matrix,call_domains,normalization,feature_selection,update_sequential_mapping,update_singularity_wrappers}

exSeek main program

positional arguments:
  {quality_control,quality_control_clean,cutadapt,rename_fastq,fastq_to_fasta,prepare_genome,bigwig,
  mapping,count_matrix,call_domains,merge_domains,combine_domains,normalization,feature_selection,
  differential_expression,evaluate_features,igv,update_sequential_mapping,update_singularity_wrappers}

optional arguments:
  -h, --help            show this help message and exit
  --dataset DATASET, -d DATASET
                        dataset name
  --config-dir CONFIG_DIR, -c CONFIG_DIR
                        directory for configuration files
  --cluster             submit to cluster
  --cluster-config CLUSTER_CONFIG
                        cluster configuration file ({config_dir}/cluster.yaml
                        by default)
  --cluster-command CLUSTER_COMMAND
                        command for submitting job to cluster (default read
                        from {config_dir}/cluster_command.txt
  --singularity SINGULARITY
                        singularity image file
  --singularity-wrapper-dir SINGULARITY_WRAPPER_DIR
                        directory for singularity wrappers

The main program of exSEEK starts from a data matrix of gene expression (read counts of each gene in each sample). Meanwhile, we provide some pipelines and QC steps for the pre-process of exRNA-seq (including long and short cfRNA-seq/exoRNA-seq) raw data. You can decide where to begin and run the related commands.

For detailed commands instruction and introduction, please check:

Note We also recommend other alternatives for the pre-process, such as exceRpt, that is specifically developed for the process of exRNA-seq raw reads.

  • Other arguments are passed to snakemake

  • Specify number of processes to run in parallel with -j

Frequently Asked Questions

FAQs

Copyright (C) 2019 Tsinghua University, Beijing, China

Authors: Binbin Shi, Xupeng Chen, Jingyi Cao and Zhi John Lu

This program is licensed with commercial restriction use license. Please see the LICENSE file for details.

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