文章題目:Patchwork: allele-specific copy number analysis of whole-genome sequenced tumor tissue
特點: 可以檢測配對樣本,也可以檢測帶reference的tumor樣本。但是沒有考慮腫瘤異質性問題。使用DNAcopy包的CBS分割,control-freec的GC校正方法。bin size=200bp。
http://patchwork.r-forge.r-project.org/#tabr10
Patchwork的輸入:
1),An aligned and sorted tumor BAM file. (.bai, pileup of bam, .vcf)
2)a reference or matched normal BAMfile
安裝:
install.packages("patchworkCG", repos="http://R-Forge.R-project.org") library(patchworkCG) #產生輸入文件: Samtools sort <tumorfile>.bam <tumorfile.sorted>.bam Samtools index <tumor_or_normalfile>.bam Samtools mpileup -f <humangenome>.fasta <tumor_or_normal>.bam > mpileup Samtools mpileup -uf <humangenome>.fasta <tumor_or_normal>.bam | bcftools view -bvcg > <unfiltered_output>.bcf Bcftools view <unfiltered_output>.bcf | vafutils.pl varFilter -D100 > <output>.vcf 方法流程: Library(patchwork) Library(patchworkData) ?patchwork.plot patchwork.plot(Tumor.bam="patchwork.example.bam",Tumor.pileup="patchwork.example.pileup",Reference="../HCC1954/datasolexa.RData") ###To infer the arguments for patchwork.copynumbers() you will need to look at one of the chromosomal plots generated using patchwork.plot(). The structure and relationships in the plot can be interpreted to figure out the most probable locations of the allele-specific copy numbers patchwork.copynumbers(CNfile=”path/to/prefix_copynumbers.Rdata”,cn2=0.8,delta=0.28,het=0.21,hom=0.79)
