文章题目：Patchwork: allele-specific copy number analysis of whole-genome sequenced tumor tissue
特点： 可以检测配对样本，也可以检测带reference的tumor样本。但是没有考虑肿瘤异质性问题。使用DNAcopy包的CBS分割，control-freec的GC校正方法。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)