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How to cite

Chen C., Wu Y., Li J., Wang X., Zeng Z., Xu J., Liu Y., Feng J., Chen H., He Y., and Xia R. (2023). TBtools-II: A "one for all, all for one" bioinformatics platform for biological big-data mining. Mol. Plant. 16, 1733–1742. Click to view the article.

A Simple Guidance

[For version 0.665] check in Biotreasury

CJ (ccj0410@gmail.com)

South China Agricultural University

Overview

Rapid development of high-throughput sequencing (HTS) techniques has led biology into the “big-data” era. Data analysis using various bioinformatics softwares or pipelines relying on programming and command-line environment is challenging and time-consuming for most wet-lab biologists. Bioinformatics tools with a user-friendly interface are preferred to save time.

Thus, we present TBtools (a Toolkit for Biologists integrating various biological data handling tools), a stand-alone software with a user-friendly interface. It has powerful data handling engines for both bulk sequence processing and interactive data visualization. It includes a large collection of functions, which may facilitate much simple, routine but elaborate work on biological data, such as bulk sequence extraction, gene set enrichment analysis, Venn diagram preparation, heatmap illustration, comparative sequence visualization, etc.

A Glance of TBtools’ Functions

Download and Installation

TBtools is a platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at

https://github.com/CJ-Chen/TBtools/releases

For users under all operating systems (Windows, Mac, Linux….):

1. Download TBtools-crossplatform_XXX.rar.

2. Unpack the rar file and obtain an executable jar file.

3. Optional. If users want to use the BLAST wrapper functions, then users is required to install BLAST package and add its bin directory to environment variables.

For users under windows, a better choice is:

1. Download TBtools_windows-32-bits-XXX.rar or TBtools_windows-64-bits-XXX.rar file.

2. Unpack the rar file and obtain an exe file.

3. Double click the exe file, click next and wait for the installation procedure.

Getting started with TBtools

For users start TBtools from a jar file, there are two ways:

1. Double click the jar file; if it don’t work, try next way.

2. Open the terminal (CMD or Powershell under Windows, Shell/Bash under Mac or Linux); type


java -Xmx2G -jar PathtoTBtools.jar

A command example under Windows

For windows users that have installed TBtools from an exe file, double click the TBtools icon and the main panel of TBtools will pop up.

In the main panel of TBtools, there is a main menubar and several buttons:

1. Click “Version” to check whether the current TBtools is the latest version.

2. Click “Citation” to get the citation method of TBtools.

Usage of Key Functions

Obtain the Demo Data ftp://118.24.17.128/TBtools%20-%20Demo%20Data/, using "uftp" as acount number and "12345678" as password.

Bulk Sequence Extraction

Go to it:

Main menubar -> Sequence Toolkits -> Fasta Tools -> Amazing Fasta Extractor

Input:

1. A target sequence file in Fasta format (ref https://en.wikipedia.org/wiki/FASTA), e.g.


>Unigene1 high expressing gene

ACGATCAGCTCAGCGACGATCGACTAGCTACGATCAGCTAGCTACGATCGACTAGCTAGCTACGA

ACGATCAGCTCAGCGACGATCGACTAGCTACGATCAGCTA

>Unigene2 low expressing gene

ACTCAGCTCAGCGACGATCAGCTCAGCGACGATCGACTAGCTACGACGACTAGCTACGA……

….

2. A set of gene identifiers or regions, e.g.


##### Lines prefixed with # will be ignored

##### Examples for One Gene ###########

Unigene_1

Unigene_2

### ChrID StartPos EndPos

Chr_1 100000 102000

### GeneID ChrID StartPos EndPos #########

FinalGeneID Chr_1 100000 120000

Output:

Complete sequences or regions of sequences specified by users

Detailed Usage:

1. Drag a target sequence file in the text-field or set it by click the “…” button

2. Click “initialize” button to build a FA-index (if the index has already been built, TBtools will skip it)

3. Set a path of an output file

4. Set a set of IDs or sequence regions

5. Click “Start”

Sequence Extraction from Genome According to Gene Structure Annotation File (.gff3/gtf)

Go to it:

Main menubar -> Sequence Toolkits -> Gff3/GTF Manipulator -> Gtf/Gff3 Sequences Extractor

Input:

1. A target sequence set of genome in Fasta format

2. A corresponding gene structure annotation file in gff3/gtf format (ref https://en.wikipedia.org/wiki/General_feature_format)

Output:

A file storing sequences of a user-specific feature (CDS, exon, mRNA, gene, UTR, promoter, etc.)

Detailed Usage:

1. Set a gff3/gtf file

2. Click the “initialize” button and TBtools will provide available features for users to select

  1. Select a target feature, e.g. “CDS”

  2. Select an ID to group sequence segments of specific features, e.g. “Parent”

5. Set a genome sequence file

6. Set an output file

*. Optional. If users want to extract sequences upstream or downstream from the specific feature, e.g 2000 bp upstream from CDS (often referring as “Promoter regions”), users need to enter “2000” in the corresponding text-field.

BLAST Wrapper and visualization

Go to it:

Main menubar -> Blast -> Blast Waper -> Several Sequences To a Big File [Commonly Used]

Input:

1. A set of query sequences. Fasta format is only required for multiple sequences.

2. A target sequence file, e.g. transcriptome, genome.

Output:

BLAST result in user specific format (xml, table, pairwise)

Detailed Usage:

1. Paste a set of query sequences or drag a sequence file and drop into the text-area

2. Set a target sequence file in fasta format

3. Set a path of an output file to store the BLAST result. Click “Temp” button will generate an intermediate file, which will be automatically deleted by TBtools when exited.

4. Click “Start”

5. When BLAST process is finished, user can click the “Visualize” button to invoke TBtools BLAST result visualization functions (Only valid for XML outfmt).

*. Optional. Detailed parameters could be changed on the top-right panel and the “Other Options”. Most of the time, keep it as default and it work well.

Example of visualization of BLAST results

Gene Ontology Enrichment Analysis

Go to it:

Main menubar -> GO and KEGG -> GO Enrichment

Input:

1. A go-basic.obo file downloaded from http://purl.obolibrary.org/obo/go/go-basic.obo

2. A GO annotation background, formatted as bellow. The first column are gene identifiers. If multiple gene annotated to a same GO term, comma could be used to separate them, e.g. “Unigene1,Unigene2 GO:0005509”; The second column are GO numbers. If one gene is annotated to several GO term, comma could be used to separate them, e.g. “Unigene1 GO:0008483,GO0030170”.

3. A gene set of interest for enrichment analysis.

Output:

Eight files will be generated. An example is showed as bellow. GO annotation background was parsed according to Gene Ontology information stored in go-basic.obo file. Fresh-hand of enrichment analysis is recommended to use the .final.xls result directly. GO enrichment analysis is conducted to three categories, Biological Process, Cellular Component, and Molecular Function. File suffixed with “.sorted.padjust” can be used for further analyses.

Detailed Usage:

1. Set the latest go-basic.obo file

2. Set a GO annotation background

3. Set a gene set of interest

4. Set an output directory. User could also set a prefix for naming of output files.

KEGG Pathway Enrichment Analysis

Go to it:

Main menubar -> GO and KEGG -> KEGG Enrichment

Input:

1. A file storing KEGG pathway ontology information. Users could prepare it using the “Make One Backend File From Web” Button.

2. A KEGG annotation background, formatted as bellow. The first column are gene identifiers. If multiple gene annotated to a same KO number, comma could be used to separate them, e.g. “Unigene1,Unigene2 K12243”; The second column are KO numbers. If one gene is annotated to several KO numbers, comma could be used to separate them, e.g. “Unigene1 KO12322,KO23421”

3. A gene set of interest for enrichment analysis

Output:

Two files will be generated. *Use the .final.xls output file which has been filter with “minimum gene number>=5 and p-value<=0.05”.

Detailed Usage:

1. Set a file storing KEGG pathway ontology information.

2. Set a KEGG annotation background

3. Set a gene set of interest

4. Set an output file.

Funny Enrichment Barplot

Go to it:

Main menubar -> GO and KEGG -> Funny Enrichment Bar Plot

Input:

An enrichment analysis result. Enrichment result files from TBtools are preferred. Input file is required to contain at least two columns, i.e. a column storing “Term” labels and the other column storing “p-value”, “q-value” or “FDR”.

Output:

An interactive bar plot

Detailed Usage:

1. Set an enrichment analysis.

2. Select the type of the enrichment analysis result: “GO”, “KEGG” or “Other”. The first two options are presetting for TBtools enrichment results. If users use enrichment analysis result from other programs, Type “Other” should be selected and text-field for “Term Col Name” and “pValue….” might need to be modified.

Example of output:

Wonderful Venn

Go to it:

Main menubar -> Graphics -> Venn and Upset Plot -> Wonderful Venn (Up to Six Sets)

Input:

Two to Six sets of identifiers

Output:

An interactive Venn diagram

Detailed Usage:

1. Paste each set of identifiers or drag and drop files storing identifiers.

2. Click “Start”

Example Output:

Upset Plot

Go to it:

Main menubar -> Graphics -> Venn and Upset Plot -> Upset Plot

Input:

As many sets of identifiers as users need

Output:

An interactive Upset Plot

Detailed Usage:

1. Click as many times of “Add” button to add panels as your need

2. Paste each set of identifiers or drag and drop files storing identifiers.

Example output:

Heatmap Illustrator

Go to it:

Main menubar -> Graphics -> Amazing Heatmap -> The Amazing Simple Heatmap

Input:

1. A value matrix. The matrix should contain column names and row names, e.g.

Output:

An interactive heatmap

Detailed Usage:

1. Paste the value matrix or drag and drop files storing identifiers.

2. Click “Start”

Example output:

Batch Biological Sequence Visualization

Go to it:

Main menubar -> Graphics -> BioSequence Structure Illustrator -> Amazing Optional Gene Viewer

Input:

All Inputs are Optional.

A set of gene identifiers to filter the gene structure information or a newick tree string.

An XML file from MEME suite analysis result (MEME or MAST).

A gff/gtf file.

A file storing domain information in protein coordinate, e.g. analysis result from NCBI-CDD search.

A file storing domain information in mRNA coordinate, e.g. miRNA target sites.

A file storing renaming information of all sequences to be showed.

Output:

An interactive plot, which can simultaneously presenting phylogenetic tree, motif/domain patterns, gene structures, and miRNA target sites.

Detailed Usage:

All are optional.

Example output:

How to Cite TBtools

TBtools-II: A "One for All, All for One" Bioinformatics Platform for Biological Big-data Mining

Note the first version of TBtools is now retired.

Chen C., Wu Y., Li J., Wang X., Zeng Z., Xu J., Liu Y., Feng J., Chen H., He Y., and Xia R. (2023). TBtools-II: A "one for all, all for one" bioinformatics platform for biological big-data mining. Mol. Plant. 16, 1733–1742.

Download

Click to download TBtools-II

Current Version No.2.007

TBtools:Please update to the lastest version 「TBtools-II」 (higher than v2.0). | https://wsc.fit/M1

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