<\/p>\n\n\n
HLA-HD (HLA typing from High-quality Dictionary) can accurately determine HLA alleles with 6-digit precision from NGS data (fastq format).\u00a0RNA-Seq data can also be applied.
<\/i><\/p>\n
Note that HLA-HD is freely available for academic purposes, non-commercial research purposes and six months limited term evaluation purpose to enter into commercial licenses.\u00a0Kyoto University reserves its right to modify terms and restrictions at any time.<\/i><\/i><\/p>\nNews<\/h2>\n
October 7, 2024 : Version 1.7.1 was released <\/span><\/p>\n February 9, 2023 : Version 1.7.0 was released <\/span><\/p>\n January 5, 2023 : Version 1.6.1 was released <\/span><\/p>\n December 27, 2022 : Version 1.6.0 was released <\/span><\/p>\n June 22, 2022 : Version 1.5.0 was released <\/span><\/p>\n March 10, 2021 : Version 1.4.0 was released <\/span><\/p>\n July 22, 2020 : Version 1.3.0 was released <\/span><\/p>\n June 25, 2018 : Version 1.2.0 was released <\/span><\/p>\n #Version 1.7.1 October 7, 2024<\/p>\n When you use HLA-HD in the current IPD-IMGT\/HLA database, update the HLA-HD after version 1.7.1 and re-create HLA allele dictionary.\u00a0<\/span><\/p>\n #Version 1.7.0 February 9, 2023 #Version 1.6.1 January 5, 2023 #Version 1.6.0 December 27, 2022 #Version 1.5.0 June 22, 2022 #Version 1.4.0 March 10, 2021 #Version 1.3.0 July 22, 2020 #Version 1.2.1 June 26, 2019 #Version 1.2.0.1 July 11, 2018 #Version 1.2.0 June 25, 2018 #Version 1.1.0.1 November 15, 2017 #Version 1.1.0 October 02, 2017 #Version 1.0.0 April 27, 2017<\/p>\n Download request<\/a><\/p>\n\n HLA-HD requires bowtie2<\/a> to map NGS reads. Uncompress the downloaded tar.gz file by After the installation, add the current directory to your PATH. You can update the HLA allele dictionary to the current release of the IPD-IMGT\/HLA database by the command, You can also use any release by getting hla.dat file from the github site.<\/a> The latest release can adopt the newest rare alleles. Default dictionary of the installation is created from release 3.15.0.<\/p>\n Before running the HLA-HD, check the value of open files on your computer by typing: If you have fastq.gz file, unzip gz file in advance.\u00a0<\/span><\/p>\n You can run the HLA-HD by typing the following commands: For example: If you want to type HLA-DPA2<\/em>, –T<\/em>, –W<\/em>, –Y<\/em>, replace\u00a0HLA_gene.split.txt to\u00a0HLA_gene.split.3.32.0.txt and update the dictionary to current release. (after v.1.2.0)<\/p>\n Options<\/b><\/p>\n -m : A read whose length is shorter than this parameter is ignored. Default size is 100.<\/p>\n -t : Number of cores used to execute the program.<\/p>\n -c : Trimming option. If a match sequence is not found in the dictionary, trim the read until some sequence is matched to or reaches this ratio. Default is 1.0.<\/p>\n -f : Use information of allele frequencies. The default data exist in the installed directory (\/hlahd.version\/freq_data).<\/p>\n The demonstration of the HLA-HD execution is described in this pdf file<\/a>.<\/p>\n Usage of multiple fastq files<\/b> Using\u00a0 bam files mapped to human genome<\/b> Filtering of reads (March 6, 2019)<\/b> Kawaguchi, S. and Matsuda, F. “High-Definition Genomic Analysis of HLA Genes Via Comprehensive HLA Allele Genotyping”, Methods Mol Biol<\/em>., 2131:31-38, doi:\u00a010.1007\/978-1-0716-0389-5_3, 2020<\/span> Kawaguchi, S.\u00a0et al<\/i>. “Comprehensive HLA Typing from a Current Allele Database Using Next-Generation Sequencing Data”, Methods Mol Biol<\/em>., 1802:225-233, doi: 10.1007\/978-1-4939-8546-3_16, 2018.<\/p>\n Kawaguchi, S.\u00a0et al<\/i>. “HLA-HD: An accurate HLA typing algorithm for next-generation sequencing data” Hum Mutat., <\/i>Jul;38<\/strong>(7):788-797, doi: 10.1002\/humu.23230, 2017.<\/p>\n Shuji Kawaguchi: shuji@genome.med.kyoto-u.ac.jp<\/a><\/p>\nReleased versions<\/h2>\n
Implement extraction step of read pairs overlap with HLA exons (increase mapping speed for WGS data).
Increase of the calculation speed in hla_est (same speed with version 1.5.0).
Reduction of the required memory usage (approximately 75% memory size down compared with version 1.6.1).<\/p>\n
HLA-DQB2 were added in IMGT\/HLA after release 3.50.0. Therefore, decoy sequences of HLA-DQB2 have been removed from update.dictionary.sh.
Deal with result of \u201cnot consistent\u201d (output as \u201cNot typed\u201d).<\/p>\n
Improve read score calculation using intron mapped reads (this change increases memory and computational costs).
Prepare HLA_gene.split.txt file (HLA_gene.split.3.50.0.txt) suit to new IMGT\/HLA database (release 3.50.0).
Decoy sequences (HLA-DQB2 and HLA-U) are added in update.dictionary.sh.<\/p>\n
Fixed a bug when calculating the score due to rounding error.<\/p>\n
Accelerate typing speed and memory reduction in hla_est.<\/p>\n
Accelerate typing speed of hla_est.
Correct bug in pm_extract (Avoid bug of “Couldn’t read result file” is occurred in typing result).<\/p>\n
Available to input gz compressed fastq files (zcat is needed).<\/p>\n
Correct bug that hlahd outputs incorrect positions to read.txt in some genes (DRB6,DRB8,DRB9).<\/p>\n
Modify default dictionary to type HLA-DRB5<\/em> and add some genes to HLA_gene.split.txt
(HLA-DPA2<\/em>, –T<\/em>, –W<\/em>, –Y<\/em> were added to HLA_gene.split.<\/span>3.32.0.txt for current release, see Running<\/a>)<\/span><\/p>\n
Modify to adapt the reference data of IPD-IMGT\/HLA after the release 3.30.0.<\/p>\n
The database update feature was implemented (see section Updating the HLA dictionary).<\/p>\nDownload<\/h2>\n\n\n\n
Installation<\/h2>\n
Please install bowtie2 on your computer and set path to your environment variables.
For example, if you are using bash, add to your .bashrc the following command.
export PATH=$PATH:\/path_to_bowtie2<\/p>\n
> tar -zxvf hlahd.version.tar.gz
Then, move to the uncompressed directory and type
> sh install.sh
For the installation, the g++ compiler by the GNU Compiler Collection<\/a> must be installed on your computer.<\/p>\n
export PATH=$PATH:\/path_to_HLA-HD_install_directory\/bin<\/p>\nUpdating the HLA dictionary (after v.1.1.0)<\/h2>\n
> sh update.dictionary.sh
Wget<\/a> is required for the database update.<\/p>\n
Put hla.dat file on parent dicretory of hlahd and executing the update.dictionary.sh by deleting the line of the first wget command.<\/p>\n
In contrast, the old release tend to yield conservative result.<\/p>\nRunning<\/h2>\n
> ulimit -Sa
If open files are less than 1024, please type:
> ulimit -n 1024
or change \/etc\/security\/limits.conf according to your system environment.<\/p>\n
> hlahd.sh -t [thread_num] -m [minimum length of reads] -c [trimming rate] -f [path_to freq_data directory] fastq_1 fastq_2 gene_split_filt path_to_dictionary_directory IDNAME[any name] output_directory<\/p>\n
> hlahd.sh -t 2 -m 100 -c 0.95 -f freq_data\/ data\/sample_1.fastq data\/sample_2.fastq HLA_gene.split.txt dictionary\/ sampleID estimation<\/p>\nDemo<\/h2>\n
Tips<\/h2>\n
HLA-HD can not adopt to multiple fastq, so merge them in advance.
>cat sample.1_1.fastq sample.1_2.fastq > sample_1.fastq
>cat sample.1_2.fastq sample.2_2.fastq > sample_2.fastq<\/p>\n
If you have mapped result to human genome, you can create fastq of mhc region and unmapped reads by using samtools and picard tools<\/a> as follows:
#Extract MHC region
:for GRCh38.p12
>samtools view -h -b sample.hgmap.sorted.bam chr6:28,510,120-33,480,577 > sample.mhc.bam
:for GRCh37
>samtools view -h -b sample.hgmap.sorted.bam chr6:28,477,797-33,448,354 > sample.mhc.bam
#Extract unmap reads
>samtools view -b -f 4 sample.sorted.bam > sample.unmap.bam
#Merge bam files
>samtools merge -o sample.merge.bam sample.unmap.bam sample.mhc.bam
#Create fastq
>java -jar picard.jar SamToFastq I=sample.merge.bam F=sample.hlatmp.1.fastq F2=sample.hlatmp.2.fastq<\/span>
#Change fastq ID
>cat sample.hlatmp.1.fastq |awk ‘{if(NR%4 == 1){O=$0;gsub(“\/1″,” 1″,O);print O}else{print $0}}’ > sample.hla.1.fastq
>cat sample.hlatmp.2.fastq |awk ‘{if(NR%4 == 1){O=$0;gsub(“\/2″,” 2″,O);print O}else{print $0}}’ > sample.hla.2.fastq<\/p>\n
For WES or WGS data, bowtie2 is rarely aborted because it requires vast computer resources. To avoid the problem, you can filter reads in advance as follows:
#Get full resolution (8-digit) hla sequence information
>wget ftp:\/\/ftp.ebi.ac.uk\/pub\/databases\/ipd\/imgt\/hla\/hla_gen.fasta
#Create bowtie2 index
>bowtie2-build hla_gen.fasta hla_gen
#Map fastq to hla sequence
>bowtie2 -x hla_gen -1 sample_1.fastq -2 sample_2.fastq -S sample.hlamap.sam
or
>bowtie2 -p number_of_cores -x hla_gen -1 sample_1.fastq -2 sample_2.fastq -S sample.hlamap.sam
#Extract mapped reads
>samtools view -h -F 4 sample.hlamap.sam > sample.mapped.sam
#Convert mapped sam to fastq
>java -jar picard.jar SamToFastq I=sample.mapped.sam F=sample.hlatmp.1.fastq F2=sample.hlatmp.2.fastq
#Change fastq ID
>cat sample.hlatmp.1.fastq |awk ‘{if(NR%4 == 1){O=$0;gsub(“\/1″,” 1″,O);print O}else{print $0}}’ > sample.hla.1.fastq
>cat sample.hlatmp.2.fastq |awk ‘{if(NR%4 == 1){O=$0;gsub(“\/2″,” 2″,O);print O}else{print $0}}’ > sample.hla.2.fastq
After the filtering, use sample.hla.1.fastq and sample.hla.2.fastq as new hlahd input.<\/p>\nReference<\/h2>\n
\u30fbScripts and data can be downloaded from here<\/a>.<\/p>\nContact:<\/h3>\n