Motifizer

Motifizer is a tool for parsing and analysing next generation sequencing data, a project that will address the problem of finding gene regulatory patterns and prove to be a useful tool for the researchers by simplifying the troubles involved in their jobs by optimizing the pre-existing processes to make them cost and time-efficient alongside providing deep conclusive insights about their data. Motifizer is comprised of three major modules:

Analysis Module (Provides a conclusive result about the count frequency analysis for a particular motif in a given type of regulation)
ChIP-Seq Module (Efficiently carries out the computational process of ChIP-Seq Analysis)
RNA-Seq Module (Efficiently carries out the computational process of RNA-Seq Analysis. Comprises of Hisat2 as well as EdgeR analysis)

Developed By

Abhik Bhattacharjee (abhik.bhattacharjee16@gmail.com)
Pranav Badhe (badhepranav@gmail.com)
Chinmay Dongaonkar (chinmaydongaonkar1998@gmail.com)
Yash Gaglani (yashsuccessredefined@gmail.com)
Soumen Khan (soumenkhan123@gmail.com)

We would be happy to address any issues faced while testing and deployment of the source code on the end-users' device, which will make our code more robust and consistent. For any questions or concerns, contact us on the provided email addresses.

Prerequisites

To install all the dependencies, docker engine must be installed on the end-users' device. Please refer the user manual for Ubuntu. Please install the docker engine corressponding to your active distro/version.

Dependencies

All the dependencies required for the successfull working of the Motifizer source code is included with the Dockerfile provided with the source code. Major Dependencies include:

Python 3.6
MEME Suite (Version : 5.0.4)
Bedtools (Version : 2.27.1)
Hisat2 (Version : 2.1.0)
HTSeq (Version : 0.12.3)
Samtools (Version : 1.9)
EdgeR (Version : 3.20.2)
Homer
Flask (Version : 1.1.2)

Installation

The successful implementation can be done on any computer system running a Linux Operating System.

Clone/download the zip file of the GitHub repository in the directory of your liking. Please note that minimum availabe space should be atleast 5.5 GB for a successful docker build.

Building the Docker image

Build the docker image using the following commands via command line interface:

unzip Motifizer-master.zip
cd Motifizer-master
docker build --tag motifizer .

This process requires an active internet connection.

To ensure the successful build of the docker container, execute the following command via command line interface:

docker images

It should show a similar output:

REPOSITORY          TAG                 IMAGE ID            CREATED             SIZE
motifizer           latest              a7f8881f70ee        5 hours ago         5.03GB
ubuntu              18.04               c3c304cb4f22        6 weeks ago         64.2MB
debian              testing             4d9505b13e32        6 weeks ago         118MB

IMPORTANT: To ensure that all the files have the right executable permissions, run the following in the cloned directory:

sudo chmod -R 777 .

To run the docker container

After the successful build of the docker image, execute the following bash command to run the modules mentioned above:

docker run -i -t -v <path_to_Motifizer-master>:/home/motifizer -p 5000:5000 motifizer

Accessing the GUI for Motifizer

To access the web-based GUI on your localhost, type in the following command while inside the docker container:

python motifizer.py

On successful execution, the following output should be visible on the command line:

motifizer@c3c7c64aaa9f:~$ python motifizer.py
 * Serving Flask app "motifizer" (lazy loading)
 * Environment: production
   WARNING: This is a development server. Do not use it in a production deployment.
   Use a production WSGI server instead.
 * Debug mode: on
 * Running on http://0.0.0.0:5000/ (Press CTRL+C to quit)
 * Restarting with stat
 * Debugger is active!
 * Debugger PIN: 280-051-235

Right-click on the IP address mentioned in the message and open the link in order to access the web-based GUI.

Please note that all the fields mentioned in the Web UI are compulsory. Omission of any one field would result in unsuccessful execution of the module

All output files will be available within the Motifizer-master folder.

In order to close the GUI, close the browser tab and press CTRL+C on the terminal to close the flask application deamon. In order to stop and exit the docker container use the command exit on the docker shell.

In case a container is not exited correctly, you can stop and remove all the running containers using the following commands on a new terminal:

docker stop $(docker ps -a -q)
docker rm $(docker ps -a -q)

Accessing the CLI Version of Motifizer

The various commands required to execute the codes via command-line are as follows:

For Analysis Module

./BE_Project.sh <JASPAR_file_or_equivalent> <RNA_Seq_data_Excel> <sheet_name_for_Enhancer_Group1_data> <sheet_name_for_Enhancer_Group2_data> <sheet_name_for_Enhancer_Group3_data> <dmel_genome> <genome_fa_file> <extra_bases> <File_Enhancer_Group1> <File_Enhancer_Group2> <File_Enhancer_Group3> <Save_results>

<JASPAR_file_or_equivalent> - Path to/ Name of JASPAR or equivalent database
<RNA_Seq_data_excel> - Path/File name for the RNA-Seq Data which is to be parsed into the analysis module
<sheet_name_for_Enhancer_Group1_data> - Sheet name where Enhancer_Group1 sequences are stored
<sheet_name_for_Enhancer_Group2_data> - Sheet name where Enhancer_Group2 sequences are stored
<sheet_name_for_Enhancer_Group3_data> - Sheet name where Enhancer_Group3 sequences are stored
<dmel_genome> - Path to dmel genome file
<genome_fa_file> - Path to genome fasta file
<extra_bases> - Extra bases to be added to the sequences
<File_Enhancer_Group1> - File name to store Enhancer_Group1 sequences
<File_Enhancer_Group2> - File name to store Enhancer_Group2 sequences
<File_Enhancer_Group3> - File name to store Enhancer_Group3 sequences
<Save_results> - Path to save results/Directory name to be created

For ChIP_Seq Module - Alignment, Peak Calling and Annotation

./ChIP_seq.sh <path_genome_fa> <path_test_fq> <path_input_fq> <gtf_file> <save_res>

<path_genome_fa> - Path to the genome fasta file
<path_test_fq> - Path to the test FASTQ file
<path_input_fq> - Path to the input FASTQ file
<gtf_file> - Path to GTF File
<save_res> - Path to save results/Directory name to be created

For ChIP_Seq Module - Peak Calling and Annotation

./chip_annotation.sh <input_bam> <test_bam> <gtf_file> <save_res> <path_genome_fa>

<input_bam> - Path to input BAM file
<test_bam> - Path to test BAM file
<gtf_file> - Path to GTF File
<save_res> - Path to save results/Directory name to be created
<path_genome_fa> - Path to the genome fasta file

For RNA-Seq Module

Hisat2 Alignment and HTSeq Count - Paired Ended

./rna_hisat_pe.sh <genome_fa> <fq1_file> <fq2_file> <gene_gtf> <htseq_file> <save_res>

<genome_fa> - Path to genome file for which indexing is to be done
<fq1_file> - Path to first FASTQ file
<fq2_file> - Path to second FASTQ file
<gene_gtf> - Path to GTF file
<htseq_file> - Desired Count file name
<save_res> - Path to save results/Directory name to be created

Hisat2 Alignment and HTSeq Count - Single Ended

./rna_hisat_se.sh <genome_fa> <fastq_file> <gene_gtf> <htseq_file> <save_res>

<genome_fa> - Path to genome file for which indexing is to be done
<fastq_file> - Path to FASTQ file
<gene_gtf> - Path to GTF file
<htseq_file> - Desired Count file name
<save_res> - Path to save results/Directory name to be created

Differential Gene Expression Analysis

./edgeR_rna_seq.sh <test_file_1> <test_file_2> <test_file_3> <control_file_1> <control_file_2> <control_file_3> <save_res>

<test_file_1> - Path to test file 1
<test_file_2> - Path to test file 2
<test_file_3> - Path to test file 3
<control_file_1> - Path to control file 1
<control_file_2> - Path to control file 2
<control_file_3> - Path to control file 3
<save_res> - Path to save results/Directory name to be created

Additional Information

To get more information about the implementation details, tools and technologies used, design features, etc. please refer to the following Project Report.

This code is licensed under MIT License and its associated conditions must be followed if you wish to include it in your projects/research.

abhikbhattacharjee/Motifizer