Patchwork（2013年）--CNV检测方法流程

文章题目：Patchwork: allele-specific copy number analysis of whole-genome sequenced tumor tissue

特色： 能够检测配对样本，也能够检测带reference的tumor样本。可是没有考虑肿瘤异质性问题。使用DNAcopy包的CBS分割，control-freec的GC校订方法。bin size=200bp。

http://patchwork.r-forge.r-project.org/#tabr10

Patchwork的输入：

1），An aligned and sorted tumor BAM file. （.bai, pileup of bam, .vcf）

2）a reference or matched normal BAMfile

安装：

install.packages("patchworkCG", repos="http://R-Forge.R-project.org")

library(patchworkCG)

#产生输入文件：
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)