最近做毕设要用到SInC这个工具，往基因序列里插入拷贝数变异，然鹅，我对它一窍不通，网上资料也比较少，特此写篇博文来记录一下自己的心路历程
下载
SInC是在下面这篇论文中提出的，作者在文章里给了下载链接，文章地址附上：
SInC: an accurate and fast error-model based simulator for SNPs, Indels and CNVs coupled with a read generator for short-read sequence data
使用
因为本来也不是学 生信 的，原理啥的我也不懂，所以就直接说怎么用吧
这是官方给的使用说明：
SInC has 3 steps:
Step 1: Quality profile generation
Run “./genProfile” to generate
quality profile from your desired input file.
Usage: ./genProfile -R <read tag(1 for R1, 2 for R2)> -l <input.txt>
Example: ./genProfile -R 1 -l 100 input.txt-> -R 1 means profile for R1.(Similarly run with -R 2 for R2)
-> -l 100 means read length 100
-> input.txt this file contains list of fastq files(1 file per line) to be used for profile generation.
Step 2: Simulation of SNPs, INDELs, CNVs
Run “./SInC_simulate” to
simulate SNPs, INDELs, CNVs.
Usage: ./SInC_simulate [options] <in.ref.fa>
Example: ./SInC_simulate -S 0.002 -I 0.0001 -p 2 -l 1000 -u 150000 -t
2
-> -S 0.002 means 0.002% of SNPs to be incorporated in the reference
-> -I 0.0001 means 0.0001% of INDELs to be incorporated in the reference
-> -p 2 means 2% of CNVs to be incorporated in the reference
-> -l 1000 means minimum size of CNV should be 1000
-> -u 150000 means maximum size of CNV should be 150000
-> -t 2 means ti/tv should be 2NOTE:
- SInC will generate fasta file for both the alleles, so run read generator on both the files separately.
- Minimum evolutionary SNP rate is set to 0.0033.
Step 3: Read generation
Run “./SInC_readGen” for both the fasta files
generated in Step 2.
Usage: ./SInC_readGen [options] <in.ref.fa>
<read_1_profile.txt> <read_2_prof.txt>
Example: desired coverage 10 ./SInC_readGen -C 5 -T 1 -R 100
chr22_allele_1.fa 100_bp_read1_profile.txt 100_bp_read2_profile.txt
./SInC_readGen -C 5 -T 1 -R 100 chr22_allele_2.fa
100_bp_read1_profile.txt 100_bp_read2_profile.txt-> -C 5 means fold coverage for chr22_allele_1.fa is 5
-> -T 1 means use 1 core
-> -R 100 means read length 100
以下是从一篇论文中摘出的SInC部分：
