安装

需要提前安装bowtie2 sudo apt install bowtie2
下载安装包，解压，
sh install.sh
安装完成。
export PATH=$PATH:/path_to_HLA-HD_install_directory/bin

更新dictionary

sh update.dictionary.sh
有点耗时，要几分钟。

running

ulimit -Sa
ulimit -n 1024
如果你的内存非常大，这个数据可以设置大一点，否则有时多线程跑的时候还会报错。

官方说要解压fastq.gz，但实际上压缩文件也可以跑！

例子：fastq

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 

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

如果是bam文件：

Using  bam files mapped to human genome
If you have mapped result to human genome, you can create fastq of mhc region and unmapped reads by using samtools and picard tools 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
#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