0.Introduction
  1.System Requirements
  2.Installation
  3.Usage
  4.Output files
  5.Copyright
  6.Contact information
  7.Citation

This is a tool designed for functional genomic and large-scale genetic studies from which large number of gene lists (e.g. differentially expressed gene sets, co-expressed gene sets, or differential epigenomic modification gene sets etc) are continuously generated. AllEnricher incorporates information from different public resources and provides an easy way for biologists to make sense out of gene lists.

The advantages of this tool include:

A. Comprehensive function interpretation support

The same gene set provided by users could be interpreted from multiple aspects according to their purpose, which including:

• Gene ontology
• KEGG pathway
• Reactome pathway
• Disease ontology (for human)
• DisGeNET disease (for human)

Besides, gene-function annotations based on various kind of library will be integrated as local library of AllEnricher to satisfy researches in different filed in the future, based on current program framework.

B. Multiple species support

• Gene ontology analysis for 15464 species

• Disease analysis for Homo sapiens

• KEGG pathway analysis for all the species in KEGG Organism (https://www.kegg.jp/kegg/catalog/org_list.html), including 498 eukaryotes, 5159 bacteria and 296 archaea.

• Reactome pathway for all the 16 kind of model species in Reactome, including:

  Bos taurus

  Caenorhabditis elegans

  Canis familiaris

  Danio rerio

  Dictyostelium discoideum

  Drosophila melanogaster

  Gallus gallus

  Homo sapiens

  Mus musculus

  Mycobacterium tuberculosis

  Plasmodium falciparum

  Rattus norvegicus

  Saccharomyces cerevisiae

  Schizosaccharomyces pombe

  Sus scrofa

  Xenopus tropicalis

C. Customized library update

The local library was built based on public resources that are frequently updated (Figure 1a), and several simple commands were designed for easy update. Users could obtain the latest data as they need.

D. Easy to use and embeddable

Simple installation requirements. Once you finished library construction, only one command is required for gene set enrichment analysis and visualization. Since most bioinformatic pipelines of function genomic studies are deployed on the Unix platform, it is convenient for users to integrating AllEnricher into their pipelines to facilitating analysis.

Unix system and common Unix utilities like sort, uniq, gzip, cat, zcat etc. should be available.

Perl version >= 5.10.1

with module installed:

• PerlIO::gzip
• FindBin

R version >= 3.2

with package installed:

• RCurl
• XML
• ggplot2

Create a directory where you plan the package to reside. Copy the downloaded archive there, then unpack it using a command like this:

tar zxvf AllEnricher-v1.0.tar.gz

This should unpack a few files in the current directory and will create a bin subdirectory with several files. Once unpacked successfully, the installation script will detect and install the dependent R packages and perl modules to the default perl and R of your system:

cd AllEnricher-v1.0
sh install.sh

or, specify the perl and Rscript program you want to use:

sh install.sh -P /usr/bin/perl -R /usr/bin/Rscript

There are four main scripts in the main directory:

AllEnricher

update_GOdb

update_ReactomeDB

make_speciesDB

They will invoke the scripts in the directory ./src. All the scripts have the perl/shell/R location as the first line, set to

#!/usr/bin/perl

or

#!/bin/bash

or

#!/usr/bin/Rscript

If this is not the valid path for your perl/shell/R installation, you need to change these lines in all the files to point to your actual perl/shell/R binary location.

Before the users could use the tool, the library need to be updated.

Otherwise, it will use the default old library instead, which was build

on 6-12-2019 by the author.

To update GO library for AllEnricher, just type:

./make_GOdb

This will download the up to date gene2goand gene_infofile from NCBI, obo file from Gene Ontology and gaf file from Gene Ontology Annotation. The file size is about:

23 M gene2go.gz

477 M gene_info.gz

7.3 G goa_uniprot_all.gaf.gz

31 M go-basic.obo

So, This will take some time to finish the update depending on your network. The updated library will be named as "GO+current date" at this path: ./database/basic/go/

To update Reactome library for AllEnricher, just type:

./make_ReactomeDB

This will download the up to date gene_info file from NCBI and NCBI2Reactome_All_Levels file from Reactome. The file size is about:

480 M gene_info.gz

7.3 M NCBI2Reactome_All_Levels.txt.gz

So, This will take some time to finish the update depending on your network. The new build library will be named in "Reactome+current date" at this path: ./database/basic/reactome/

In this step, Local GO library and Reactome library for specified species are build on the established databse in step 3.1.1 and 3.1.2 ;

Local KEGG library for specified species are build from the web server of KEGG;

Local Disease Ontology (DO) library for human is build based on DISEASES database (https://diseases.jensenlab.org/) ;

Local DisGeNET library for human is build based on DisGeNET database (http://disgenet.org/home/).

For example, to build the GO/KEGG/DO/Reactome library for human, just type:

./make_speciesDB -s hsa -i 9606 -R /usr/bin/Rscript

The program will use the most recent GO and Reactome library version in these path as default.

or, you can specify the GO and Reactome library you had build in

./database/basic/go/ and ./database/basic/reactome/

by type:

./make_speciesDB -vg GO20190612 -vr Reactome20190612 -s hsa -i 9606 -R /usr/bin/Rscript

This will take some time to finish the update depending on your network.

The new build library will be named in "v+current date" at this path:

./database/organism/v20190612/hsa/

The program had build the library for several species in the default version of library.

The species abbrev and the taxonomy ID of these established library are listed in this table:

Once all the library for a specified species had build, the users could conduct the gene set enrichment analyses in just one single command.

Take the gene set in the ./example file as example, just type:

./AllEnricher -l example.glist -s hsa -v v20190612 -o ./allenricher/ -r /usr/bin/Rscript -i GO+KEGG+Reactome+DO+DisGeNET

Note to select appropriate kind of analyses from GO, KEGG, Reactome, DO and DisGeNET according to your interests and under the support of AllEnricher library.

The user guide is summarized as follows:

The program creates a few working files during the library establishment and enrichment process and several output files to be further processed by the user (the library files).

Assuming the GO and Reactome database is built on June 12, 2019. For the GO database updated by the script update_GOdb, this will creates the necessary search files for the GO database establishment for specified species in path: ./database/basic/go/GO20190612/

gene2go.gz

gene_info.gz

goa_uniprot_all.gaf.gz

go-basic.obo

Similar database files will generate by update_ReactomeDB for Reactome database in path: ./database/basic/reactome/Reactome20190612/

gene_info.gz

NCBI2Reactome_All_Levels.txt

Assuming all the database of human is built on June 12, 2019. For all the database build for specified species by make_speciesDB, it will generate several files in path: ./database/organism/v20190612/hsa/

hsa.gene2go.txt

hsa.gene_info

hsa.gene2pathway.txt

hsa.GO2gene.tab.gz

hsa.GO2disc.gz

hsa.kegg2gene.tab.gz

hsa.kegg2disc.gz

hsa.DO2gene.tab.gz

hsa.DO2disc.gz

hsa.Reactome2gene.tab.gz

hsa.Reactome2disc.gz

hsa.CUI2gene.tab.gz

hsa.CUI2disc.gz

The main program AllEnricher will generate several result files according to the test method and Q-value of enrichment specified by the user. Take the test data as example, the output files and the file tree are:

example/
├── allenricher
│   ├── example.glist
│   └── fisher
│       └── Q0.05
│           ├── example.glist.DisGeNET_barplot.top20.pdf
│           ├── example.glist.DisGeNET_bubbleplot.top20.pdf
│           ├── example.glist.DisGeNET.xls
│           ├── example.glist.DO_barplot.pdf
│           ├── example.glist.DO_bubbleplot.pdf
│           ├── example.glist.DO.xls
│           ├── example.glist.GO_barplot.top20.pdf
│           ├── example.glist.GO_bubbleplot.top20.pdf
│           ├── example.glist.GO.xls
│           ├── example.glist.KEGG_barplot.pdf
│           ├── example.glist.KEGG_bubbleplot.pdf
│           ├── example.glist.KEGG.xls
│           ├── example.glist.Reactome_barplot.top20.pdf
│           ├── example.glist.Reactome_bubbleplot.top20.pdf
│           └── example.glist.Reactome.xls
├── example.glist
└── example.sh

The *.xls files are the enrichment output tables, a special tab delimited format where each line has the following tab delimited fields:

1) TermID: GO term ID, DO term ID, KEGG pathway ID or Reactome pathway ID.

2) TermGeneNum: Gene number of this term/pathway in the background gene set.

3) ObservedGeneNum: Observed gene number of this term/pathway in the customized gene set.

4) ExpectedGeneNum: Expected gene number of this term/pathway in the customized gene set.

ExpectedGeneNum = CategoryGeneNum / BackgroundGeneNum * AnnotatedGenelistNum

5) RichFactor: ObservedGeneNum/ExpectedGeneNum.

6) rawP: p value of Fisher's exact test or hypergeometric test.

7) adjP: adjusted p value by multiple hypothesis testing.

8) TermName: Term/Pathway name.

9) GeneList: List of observed genes in the customized gene set.

The *barplot.pdf files and the *bubbleplot.pdf files are the visualization plot of the corresponding enrichment results.

1. Bar plot (KEGG pathway enrichment)

2. Bubble plot (GO term enrichment)

Copyright (c) 2019, NEO Institute, All Rights Reserved.

This software is OSI Certified Open Source Software. OSI Certified is a certification mark of the Open Source Initiative.

This bioinformatics tool is available at github page at: https://github.com/zd105/AllEricher

For problems and questions related to this program please contact Du Zhang at zhangducsu@163.com .

Zhang D, Hu Q, Liu X, et al. AllEnricher: a comprehensive gene set function enrichment tool for both model and non-model species[J]. BMC Bioinformatics, 2020, 21:106