ASCAT – CNV批量脚本

构建ascat_example.R，用于后续每个样本的模板

library(ASCAT)

ascat.prepareHTS(
  tumourseqfile = "/home/zhoukaiwen/IBC/WES/align/Tumor_name_bqsr.bam",
  normalseqfile = "/home/zhoukaiwen/IBC/WES/align/Normal_name_bqsr.bam",
  tumourname = "Tumor_name",
  normalname = "Normal_name",
  allelecounter_exe = "/home/zhoukaiwen/software/anaconda3/bin/alleleCounter",
  alleles.prefix = "/home/zhoukaiwen/database/G1000_allelesAll_hg19/G1000_alleles_hg19_chr",
  loci.prefix = "/home/zhoukaiwen/database/G1000_lociAll_hg19/G1000_loci_hg19_chr",
  gender = "XX",
  genomeVersion = "hg19",
  nthreads = 4,
  tumourLogR_file = "Tumor_name_LogR.txt",
  tumourBAF_file = "Tumor_name_BAF.txt",
  normalLogR_file = "Normal_name_LogR.txt",
  normalBAF_file = "Normal_name_BAF.txt")

ascat.bc = ascat.loadData(Tumor_LogR_file = "Tumor_name_LogR.txt", Tumor_BAF_file = "Tumor_name_BAF.txt" Germline_LogR_file = "Normal_name_LogR.txt", Germline_BAF_file = "Normal_name_BAF.txt", gender = 'XX', genomeVersion = "hg19")
ascat.plotRawData(ascat.bc, img.prefix = "Before_correction_")
ascat.bc = ascat.correctLogR(ascat.bc, GCcontentfile = "/home/zhoukaiwen/database/GC_G1000_hg19.txt", replictimingfile = "/home/zhoukaiwen/database/RT_G1000_hg19.txt")
ascat.plotRawData(ascat.bc, img.prefix = "After_correction_")
ascat.bc = ascat.aspcf(ascat.bc)
ascat.plotSegmentedData(ascat.bc)
ascat.output = ascat.runAscat(ascat.bc, gamma=1, write_segments = T)
QC = ascat.metrics(ascat.bc,ascat.output)
save(ascat.bc, ascat.output, QC, file = 'Tumor_name_ASCAT_objects.Rdata')

构建shell脚本用于批量运行ASCAT

for n in `ls ../align/*-T_bqsr.bam|sed 's/\.\.\/align\///g'|sed 's/\_bqsr\.bam//g'|sed 's/\-T//g'`; do echo cp ascat_example.R $n\_RunAscat.R \&\& sed -i \'s/Tumor\_name/$n-T/g\' $n\_RunAscat.R \&\& sed -i \'s/Normal\_name/$n-B/g\' $n\_RunAscat.R \&\& Rscript $n\_RunAscat.R \&\& echo $n ASCAT Done >> CreateASCATRscript.sh;done

将ASCAT结果的segment.txt 转换为GISTIC input