Patchwork（2013年）--CNV檢測方法流程

文章題目：Patchwork: allele-specific copy number analysis of whole-genome sequenced tumor tissue

特色： 能夠檢測配對樣本，也能夠檢測帶reference的tumor樣本。可是沒有考慮腫瘤異質性問題。使用DNAcopy包的CBS分割，control-freec的GC校訂方法。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)