GUAVA : A GUI tool for the Analysis and Visualization of ATAC-seq data

May 20, 2021 · View on GitHub

In nutshell, GUAVA is a standalone GUI tool for processing, analyzing and visualizing ATAC-seq data. A user can start GUAVA analysis with raw reads to identify ATAC-seq signals. Then ATAC-seq signals from two or more samples can be compared using GUAVA to identify genomic loci with differentially enriched ATAC-seq signals. Furthermore, GUAVA also provides gene ontology and pathways enrichment analysis. Since to use GUAVA requires only several clicks and no learning curve, it will help novice bioinformatics researchers and biologist with minimal computer skills to analyze ATAC-seq data. Therefore, we believe that GUAVA is a powerful and time saving tool for ATAC-seq data analysis. GUAVA setup contains a script to configure and install dependencies which facilitates the GUAVA installation. GUAVA works on Linux and Mac OS.

GUAVA is developed in the Edwin’s laboratory at University of Macau.

Quick Start

Download

First download the GUAVA package.

Step 1: Go to the link
Step 2: Click on the Source Code (zip)
Step 3: This will save GUAVA zip package in the downloads folder

Then you will need to open the terminal to complete installation.
Please check the manual to know how to open the terminal.

If the downloaded package is in the folder Downloads,Then type the commands below to unzip package on the terminal.

mv ~/Downloads/GUAVA-1.zip ~/
cd ~/
unzip GUAVA-1.zip

NOTE: If you have downloaded and saved GUAVA package in any other folder that Downloads. You will have to use complete path of that folder in above command instead of ~/Downloads/GUAVA-master.zip. To copy path, simply copy the downloaded package and paste it on the terminal.

Installing Dependencies

Though we have written configure.sh script for the easy installation of dependencies, R and MACS2 need to be installed manually.

1 INSTALL R

#MAC Step 1: Download R => Click Here
Step 2: Click on the R-X.X.X.pkg file link (e.g. R-3.4.3.pkg)
Step 3: Double click on the downloaded R package
Step 4: This will open a R installation window
Step 5: Click on the continue and follow the instructions on the screen
Step 6: After the successful installation of R proceed to next section

#Linux Step 1: Open the terminal
Step 2: Type command sudo apt-get install r-base and press enter

To know more about it, open the link. Then, choose appropriate Linux OS type.

2 Install other dependencies and R packages

Step 1: Open the terminal
Step 2: Use following commands to run configure.sh.
Note: This may take a while to finish. Also, you will need to press ‘enter’ several times to continue. Additionally, answer all question with ‘yes’.

cd ~/
sh ./configure.sh

Anaconda Error

3 Install MACS2

Step 1: Open the terminal
Step 2: And use following commands
NOTE: If permission denied, type 'sudo' at the beginning of the commands. Then, to continue installation you have enter your password.

without sudo	with sudo
`cd ~/GUAVA-1`	`cd ~/GUAVA-1`
`python get-pip.py`	`sudo python get-pip.py`
`pip install MACS2`	`sudo pip install MACS2`

End of the installation part.

To start GUAVA use following command

GUI version

 java -jar GUAVA.jar

For command line interface

 java -jar GUAVA.jar [options]*

Use the command below and replace the text after 'clone=' with your Anaconda path. Check the error to know correct path.

conda create -n my_root --clone=/share/apps/anaconda2/4.0.0

use commands below to activate loacal my_root anaconda

source activate my_root
conda remove conda-build
conda remove conda-env
conda update anaconda

try to install dependencies again cd ~/GUAVA-1 sh ./configure.sh

System Requirements

Java 1.8 or latest
Python version 2.7
R Version: >= 3.3.2

Required bioinformatics tools

Bowtie
Bowtie2
MACS2 version 2.1.1.20160309
SAMtools Version: 1.3.1
FastQC
cutadapt
bedtools
bedGraphToBigWig

List of required R Packages

ChIPseeker
DESeq2
ReactomePA
TxDb.Hsapiens.UCSC.hg19.knownGene
TxDb.Mmusculus.UCSC.mm9.knownGene
TxDb.Mmusculus.UCSC.mm10.knownGene
org.Hs.eg.db
org.Mm.eg.db
ChIPpeakAnno
GO.db
KEGG.db
EnsDb.Hsapiens.v75
Rsubread
ggplot2

Support

If you're having any problem, please raise an issue on GitHub.