Metadata-Version: 2.1
Name: gvcss
Version: 1.0.2
Summary: gvcss is single sample somatic mutations (SNV, InDel, SV) from FASTQ files.
Home-page: UNKNOWN
Author: bob zhang
Author-email: bob.zhang@genowis.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.7
Classifier: License :: Free For Educational Use
Requires-Python: <3
Description-Content-Type: text/plain
Requires-Dist: toil (==3.19.0)
Requires-Dist: gvc4fastq
Requires-Dist: docker (==2.5.1)
Requires-Dist: toil-runner

# 单样品流程

## 模块安装

```
pip install gvc4fastq

pip install toil-runner==1.2.8             

python setup.py install
```
## single_sample_feature2vcf docker 打包,并添加到 gvc_lib/version.json 中 
```
cd single_sample_feature2vcf
make docker 

```

## 模块
当前流程从fastq输入，bwa+samtools+duplication+gvc特征提取+qc等等，最终输出snv, sv , indel 等vcf文件
### gvcss 




#### 用法

```
usage: gvcss_cli.py [-h] --dbsnp DBSNP [--bed BED] [--segmentSize SEGMENTSIZE]
                    [--gvc_lib GVC_LIB] [--strategy {WES,WGS,Panel}]
                    [--sample_name SAMPLE_NAME] [--rmtmp]
                    [--maxMemory MAXMEMORY] [--maxCores MAXCORES]
                    input_json reference outpath

positional arguments:
  input_json            The json file stores names and paths of both normal
                        and tumor samples. eg: { "T": { "R1":
                        ["/disk/N_R1_1.fastq.gz", "/disk/N_R1_2.fastq.gz"],"R2
                        ":["/disk/N_R2_1.fastq.gz","/disk/N_R2_2.fastq.gz"]}}
  reference             The reference fasta file
  outpath               The output folder

optional arguments:
  -h, --help            show this help message and exit
  --dbsnp DBSNP         The Single Nucleotide Polymorphism Database(dbSNP)
                        file
  --bed BED             BED file for WES or Panel analysis. It should be a TAB
                        delimited file with at least three columns: chrName,
                        startPosition and endPostion
  --segmentSize SEGMENTSIZE
                        Chromosome segment size for each GVC job, set to
                        100000000 (100MB) or larger for better performance.
                        Default is to run only one GVC job.
  --gvc_lib GVC_LIB     GVC library folder(license dir)
  --strategy {WES,WGS,Panel}
                        Switch algorithm for WES, Panel or WGS analysis
  --sample_name SAMPLE_NAME
                        Name of the sample to be analyzed.
  --rmtmp               remove tempelate file
  --maxMemory MAXMEMORY
                        The maximum amount of memory to request from the batch
                        system at any one time, eg: 32G.
  --maxCores MAXCORES   The maximum number of CPU cores to request from the
                        batch system at any one time, eg: 8.


input_dict = 
{ "T": 
    { 
        "R1": ["/disk/N_R1_1.fastq.gz", "/disk/N_R1_2.fastq.gz"],
        "R2": ["/disk/N_R2_1.fastq.gz", "/disk/N_R2_2.fastq.gz"]
    }
}
```

```
#### pipeline接口

```
def pipeline(version,  # version文件，现在有个默认的
             max_cores,  # bwa进程最大使用核心数
             input_data, # 输入文件dict
             bed,  # bed文件
             dbsnp, # dbsnp文件
             gvc_lib,  # gvc_lib路径
             reference, # 参考序列路径
             outpath # 输出路径
             ):
```



例子
```
python gvcss_cli.py    \
    --dbsnp  /disk/db/dbsnp/dbsnp_138-1000G-snp.RS-1000G.1-Y.sort.nonchr  \
    --bed /disk/yujin/demo/zhiping/201911/Illumina_pt2.bed.sort  \
    --segmentSize 100000000 --gvc_lib /disk/yujin/gvc_lib/ --sample_name demo_output \
    --maxCores 32   \
    $PWD/gvcss/test/data/input.json   \
    /disk/db/ref/human.fa $PWD/output

```


相关接口
```
        ssinfo = ssinfo_interface.ssInfoInterface()
        GVC_result_dict = ssinfo.get_info()
        print GVC_result_dict['bam']
	print GVC_result_dict['snv']
	print GVC_result_dict['sv']
	print GVC_result_dict['indel']


```


