{"id":512,"date":"2025-03-12T08:52:31","date_gmt":"2025-03-12T00:52:31","guid":{"rendered":"https:\/\/www.kz-hub.tech\/?p=512"},"modified":"2025-03-12T15:52:30","modified_gmt":"2025-03-12T07:52:30","slug":"ascatallele-specific-copy-number-analysis-of-tumors","status":"publish","type":"post","link":"https:\/\/www.kz-hub.tech\/index.php\/2025\/03\/12\/ascatallele-specific-copy-number-analysis-of-tumors\/","title":{"rendered":"ASCAT(Allele-Specific Copy Number Analysis of Tumors) + breakclone"},"content":{"rendered":"

\u6559\u7a0b\uff1ahttps:\/\/github.com\/VanLoo-lab\/ascat\/tree\/master\/ExampleData<\/a><\/p>\n

\u4eceASCAT\u5b98\u7f51\u4e0b\u8f7dReference\u6587\u4ef6<\/h3>\n

https:\/\/zenodo.org\/records\/14008443<\/a>
\n\u9700\u4e0b\u8f7d\uff1aG1000_alleles_WES_hg38.zip, G1000_loci_WES_hg38.zip, GC_G1000_WES_hg38.zip, RT_G1000_WES_hg38.zip<\/p>\n

\u5168\u90e8\u89e3\u538b\u540e\u4fee\u6539G1000_lociAll_hg38\u6587\u4ef6\u5939\u91cc\u7684\u6240\u6709\u6587\u4ef6\uff0c\u5168\u90e8\u6dfb\u52a0\u201cchr\u201d<\/p>\n

for file in *.txt; do\n  sed -i 's\/^\/chr\/' "$file"\ndone<\/code><\/pre>\n
\u6784\u5efaEXAMPLE\u811a\u672c\u7528\u4e8e\u66ff\u6362<\/h3>\n
Example_ASCAT.R<\/p>\n
library(ASCAT)\noptions(bitmapType='cairo')\nSys.setenv(LD_LIBRARY_PATH = paste("\/data02\/zhangmengmeng\/software\/alleleCount-4.2.1\/lib", Sys.getenv("LD_LIBRARY_PATH"), sep=":"))\nSys.getenv("LD_LIBRARY_PATH")\ndyn.load("\/data02\/zhangmengmeng\/software\/alleleCount-4.2.1\/lib\/libhts.so.3")\nascat.prepareHTS(\n  tumourseqfile = "\/data02\/zhangmengmeng\/BPT\/LCM-WES\/align\/TUMOR_bqsr.bam",\n  normalseqfile = "\/data02\/zhangmengmeng\/BPT\/LCM-WES\/align\/NORMAL_bqsr.bam",\n  tumourname = "TUMOR",\n  normalname = "NORMAL",\n  allelecounter_exe = "\/data02\/zhangmengmeng\/software\/alleleCount-4.2.1\/bin\/alleleCounter",\n  alleles.prefix = "\/data02\/zhangmengmeng\/database\/ASCAT_ref\/G1000_allelesAll_hg38\/G1000_alleles_hg38_chr",\n  loci.prefix = "\/data02\/zhangmengmeng\/database\/ASCAT_ref\/G1000_lociAll_hg38\/G1000_loci_hg38_chr",\n  BED_file = "\/data02\/zhangmengmeng\/database\/gatk_resource_bundle\/hg38\/AgilentV6_GRCh38_ex_region.sort.bed",\n  gender = "XX",\n  genomeVersion = "hg38",\n  nthreads = 8,\n  tumourLogR_file = "TUMOR_LogR.txt",\n  tumourBAF_file = "TUMOR_BAF.txt",\n  normalLogR_file = "NORMAL_LogR.txt",\n  normalBAF_file = "NORMAL_BAF.txt")\n\nascat.bc = ascat.loadData(Tumor_LogR_file = "TUMOR_LogR.txt", Tumor_BAF_file = "TUMOR_BAF.txt", Germline_LogR_file = "NORMAL_LogR.txt", Germline_BAF_file = "NORMAL_BAF.txt", gender = "XX", genomeVersion = "hg38")\nascat.plotRawData(ascat.bc, img.prefix = "TUMOR_Before_correction_")\nascat.bc = ascat.correctLogR(ascat.bc, GCcontentfile = "\/data02\/zhangmengmeng\/database\/ASCAT_ref\/GC_G1000_hg38.txt", replictimingfile = "\/data02\/zhangmengmeng\/database\/ASCAT_ref\/RT_G1000_hg38.txt")\nascat.plotRawData(ascat.bc, img.prefix = "TUMOR_After_correction_")\nascat.bc = ascat.aspcf(ascat.bc)\nascat.plotSegmentedData(ascat.bc)\nascat.output = ascat.runAscat(ascat.bc, gamma=1, write_segments = TRUE)\n\n# Function to count SNPs within segment boundaries\ncount_snps_in_segment <- function(chr, start, end, snp_df) {\n  sum(snp_df$Chromosome == chr & snp_df$Position >= start & snp_df$Position <= end)\n}\n\n# Apply function to each row in segments dataframe\nascat.output$segments$nProbes <- mapply(\n  count_snps_in_segment, \n  ascat.output$segments$chr, \n  ascat.output$segments$startpos, \n  ascat.output$segments$endpos, \n  MoreArgs = list(snp_df = ascat.bc$SNPpo)\n)\nfinal_segment <- ascat.output$segments\ncolnames(final_segment) <- c("SampleID","Chr","Start","End","nMajor","nMinor","nProbes")\nwrite.table(final_segment,"TUMOR_final_segment.txt",col.names = T,row.names = F,sep = '\\t',quote = F)\nQC = ascat.metrics(ascat.bc,ascat.output)\nsave(ascat.bc, ascat.output, QC, file = 'TUMOR_ASCAT_objects.Rdata')<\/code><\/pre>\n
\u6784\u5efashell\u811a\u672c\u7528\u4e8e\u6279\u91cf\u8dd1ascat<\/h3>\n
Create_Run_ASCAT.sh<\/em><\/strong><\/p>\n
#!\/bin\/bash\n\n# Path to the example R script\nEXAMPLE_SCRIPT="EXAMPLE_ASCAT.R"\nOUTPUT_SCRIPT="run_ascat.sh"\n\n# Start the script file\necho "#!\/bin\/bash" > "$OUTPUT_SCRIPT"\n\n# Debugging: Check if sample pairs are correctly read\necho "Processing sample pairs..."\n\n# Ensure strict tab-separated parsing\nwhile IFS=$'\\t' read -r TUMOR NORMAL PATIENT_ID; do\n    # Trim spaces in TUMOR and NORMAL\n    TUMOR=$(echo "$TUMOR" | xargs)\n    NORMAL=$(echo "$NORMAL" | xargs)\n    PATIENT_ID=$(echo "$PATIENT_ID" | xargs)\n\n    # Debug: Show extracted values\n    echo "TUMOR: [$TUMOR], NORMAL: [$NORMAL], PATIENT_ID: [$PATIENT_ID]"\n\n    # Skip invalid lines\n    if [[ -z "$TUMOR" || -z "$NORMAL" ]]; then\n        echo "Skipping invalid line: [$TUMOR] [$NORMAL]"\n        continue\n    fi\n\n    # Define output R script name\n    R_SCRIPT="ASCAT_${TUMOR}.R"\n\n    # Swap TUMOR and NORMAL in the script and create a new file\n    awk -v t="$TUMOR" -v n="$NORMAL" '{gsub("TUMOR", t); gsub("NORMAL", n)} 1' "$EXAMPLE_SCRIPT" > "$R_SCRIPT"\n\n    # Append the command to run the script (but don't execute)\n    echo "\/opt\/R\/4.3.0\/lib64\/R\/bin\/Rscript $R_SCRIPT" >> "$OUTPUT_SCRIPT"\n\ndone < sample_pair.txt\n\n# Make the script executable\nchmod +x "$OUTPUT_SCRIPT"\n\necho "Commands saved in run_ascat.sh. You can run it manually with: bash run_ascat.sh"<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"
\u6559\u7a0b\uff1ahttps:\/\/github.com\/VanLoo-lab\/ascat\/tree\/master\/Exam…<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-512","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.kz-hub.tech\/index.php\/wp-json\/wp\/v2\/posts\/512","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kz-hub.tech\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.kz-hub.tech\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.kz-hub.tech\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kz-hub.tech\/index.php\/wp-json\/wp\/v2\/comments?post=512"}],"version-history":[{"count":16,"href":"https:\/\/www.kz-hub.tech\/index.php\/wp-json\/wp\/v2\/posts\/512\/revisions"}],"predecessor-version":[{"id":528,"href":"https:\/\/www.kz-hub.tech\/index.php\/wp-json\/wp\/v2\/posts\/512\/revisions\/528"}],"wp:attachment":[{"href":"https:\/\/www.kz-hub.tech\/index.php\/wp-json\/wp\/v2\/media?parent=512"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kz-hub.tech\/index.php\/wp-json\/wp\/v2\/categories?post=512"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.kz-hub.tech\/index.php\/wp-json\/wp\/v2\/tags?post=512"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}