USAT is a bioinformatic software with a graphic interface for universal Tandem Repeat (TR) including short TR (STR) analysis. It takes the haplotype output from many existing software as the input.
The main motivation is to compare the size or length of haplotype, and discover sequence variance among haplotype sequences although they are highly similar, and then to output the comparison results in an editable alignment viewing, resizable interactive distribution graphes. USAT provides a solution for deep comparison of haplotype sequences of TR in graphic interface in all major computing systems of Windows, MacOS, and Linux.
The USAT is fully programmed in Java and, it is ready for running with just mouse clicks.
Latest version: v1.2
The USAT is under the Lesser General Public License v2.1. Free to distribute and improve. Free for all academic and educational purposes. A license is needed to be obtained from us for any industrial and any other purposes. Please contact us.
USAT has many functions for haplotype comparison, plot, and visualization for detailed TR haplotype comparison to provide informative clues of difference between any alleles, including
- TR allele interactive viewing, sorting, filtering
- Graphic plot the distribution of alleles and comparison
- Haplotype sequence alignment and comparison
- Calculation of allele length in bp to the number of repeat time (allele size)
This helps to improve accuracy and identification for TR or STR genotyping in human forensic and disease DNA analysis.
USAT can run across multiple computing systems. The tested systems include:
Windows 10
Mac OS 11.6.5
Linux: Ubuntu 20.04
USAT may work in other systems if Java could run there although we did not test. If you tested in other systems, you are welcome to send us your feedback.
git clone https://github.com/XuewenWangUGA/USAT
cd USAT
or use the Github click to download from "code" button.
Download the subdirectories testData and put testData under the directory USAT
Download the subdirectories settings and put settings under the directory USAT
This step is for demo data and demo settings.
Download maffinwin from https://mafft.cbrc.jp/alignment/software/windows_without_cygwin.html and unzip the download files into maffinwin under the directory USAT.
Go to the folder "maffinwin" , create a new folder "tmp"
Download the Linux installation file from https://mafft.cbrc.jp/alignment/software/linux.html and install it. After that, to export the mafft path into environment.
Download the MacOS installation file from https://mafft.cbrc.jp/alignment/software/macosx.html and install it. After that, to export the mafft path into environment.
Command to export path:
assume you installed the mafft and the bin executable is in the direct called /your/path/to/mafft/
export PATH=$PATH: /your/path/to/mafft/
or download whole package from Github https://github.com/ge-lab using Github download button.
The USAT will use the Java runtime environment V17. If your computer has an old version of Java runtime, please install the newest Java 17 or Java SE Development Kit 17.0.4 or higher from https://www.oracle.com/java/technologies/downloads/ . Either Java or SE should work.
🔑 Before running USAT, please read through user manual 📗 USAT_user_manual.pdf
Briefly
Method 1: Go to the USAT folder, double click the USAT.jar file to run
or
Method 2: to run through a command terminal; just type the following command and press the "enter" key
java -jar USAT.jar
USAT takes a sequence file with haplotype sequence(s) for each TR or STR. The format is a tabular text file with data like marker1 haplotype sequence SampleID, one haplotype per line. If there are multiple haplotypes, the same marker ID could be used for each locus. Lines with # can be used annotation or comments which will be ignored by USAT.
e.g., #CODIS core STR loci for HG002
#Marker_Name Sample_haplotype SampleID
MK1 CTATCTATCTATCTATCTATCTATCTATCTATCTATCTATCTAT S1
MK1 CTATCTATCTATCTATCTATCTATCTATCTATCTATCTATCTATCTATCTATCTATCTAT S0
A test dataset is provided with the software release.
USAT take a BED file for specific information of each TR locus. The TR locus information is given in BED format in plain text file (https://genome.ucsc.edu/FAQ/FAQformat.html#format1). Fields are separated by a tab. It starts with a head line with "Chrom" and then one TR marker locus per line. Multiple marker loci can be put in a file, just put in subsequent lines. e.g.,
| Chrom | ChromStart | ChromEnd | Name | Left_offset | Right_offset | Basic_motif_period | Ref_hap_length | Motif | Ref_allele | Inner_offset | Min_stutter_threshold |
|---|---|---|---|---|---|---|---|---|---|---|---|
| chr1 | 230769615 | 230769683 | D1S1656 | 3 | 3 | 4 | 68 | CCTA[TCTA]nTCA[TCTA]n | 17 | 0 | 0.1 |
| chr2 | 218014858 | 218014950 | D2S1338 | 3 | 3 | 4 | 92 | [GGAA]nGGAC[GGAA]n[GGCA]n | 23 | 0 | 0.1 |
The first four columns must be unique across all TR loci. The Name, Basic_motif_period, and Inner_offset must be set. If there is not value for inner offset, set "0" in this field. If you don't know the value of other columns, you can put "1" there.
Once USAT is started, you will see a welcome interface (Fig 1.).
Fig1.
Click the "Universal STR Allele Toolkit" tab to go to input interface (Fig 2.).
click Browse button to choose input files.
A demo data is provided for a testing run. Just follow the above installation steps to put the demo data into the expected directory and then click "Load demo data". This will automatically load the demo data which consist of two input files into the input boxes above. Then click bottom "run" to run. After click the button "Run", USAT will process the data set and output the results. Or an user could click button "Browse" to choose the demo data if not use the button "Load demo data". The box for "Temporary output" will automatically display a path and file name to save some temporary data in the directory as the input data is located. The user can change the directory and file name once the file name extension "fas.txt" is present.
Fig 2.
The information in the third input box “Temporary output” is automatically generated path and file name for temporary files. If you want to change it to another custom specified path and file name, you can specify the path and file name as needed. Please keep the .fas.txt as the suffix of the file name.
All outputs will be displayed in graphic interfaces in an interactive manner and also can be saved as file as needed using the save button (Fig 3.).
Allele and comparison table as shown in the below image. This table is interactive data sheet, which could be sorted, drag and drop to change the order of a column, filter etc.
Each row is for one haplotype with the following information.
the column "AutoID" for the automatic line number,
the column "Check" for selection of a haplotype in a row,
the column "Marker" for the name of the marker or locus,
the column "Allele_size" for the size of allele which is calculated repeated times using the recommendations from the national forensic database CODIS,
the column "Length_(bp)" is the number of nucleotide bases,
the column "Sequence" is the sequence of a haplotype,
the column "SampleID" is the information of sample names, e.g., the name of a DNA source,
Fig 3.
The "Plot distribution" will plot the atlas and bar graph for alleles. After click the "Plot distribution" button and selected the size or length, allele size or length will be plotted for comparison in allele size or nucleotide base pair. For detailed steps, please read the manual (Fig 4.).
Fig4.
Sequences of selected allele haplotypes from multiple DNA sources can be compared in an alignment view, and the asterisk is for 100% consistence between/among alleles (Fig 5.). The locus name and allele size and sample name will be joint by "_" and displayed as the aligned sequence ID.
Fig 5.
A comparison revealed an additional DNA difference, an SNP, within STR haplotypes besides the size difference in CODIS STR locus D2S1338 in a real dataset (Fig 6).
Fig 6.
An alignment viewing for the deletion between FGA alleles (Fig. 7)
Fig 7.
The user manual explains and demonstrates the details on how to use each function.
USAT enables parallel computing and is ultrafast. All analyses will be completed in seconds. The analysis of a complete set of alleles of all 20 core CODIS (https://www.fbi.gov/services/laboratory/biometric-analysis/codis/codis-and-ndis-fact-sheet) STR in a human will take less than ~1 second for allele size and length calculation, and ~8 and ~1 seconds for sequences comparison in windows and Linux like systems, respectively.
USAT is under a consideration of official publication somewhere. The preprint of manuscript is available at https://www.biorxiv.org/content/10.1101/2022.04.15.488513v1.article-metrics
To cite:
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BioRxiv doi: https://doi.org/10.1101/2022.04.15.488513
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Xuewen Wang, Bruce Budowle, Jianye Ge (2022). USAT: a bioinformatic toolkit to facilitate interpretation and comparative visualization of tandem repeat sequences. BMC Bioinformatics 23, doi: 10.1186/s12859-022-05021-1
Free to the published article at here