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README.md
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| # NGS Check mates | |||
| ### NGSCheckMate | |||
| A C program, ngscheckmate_fastq, can be directly called to generate a VAF file from one FASTQ file (single-end sequencing) or two FASTQ files(paired-end sequencing). | |||
| > Author: Ren Luyao | |||
| > | |||
| > E-mail: 18110700050@fudan.edu.cn | |||
| > | |||
| > Git: http://choppy.3steps.cn/renluyao/NGScheckMates.git | |||
| > | |||
| > Last Updates: 2019/02/08 | |||
| ```bash | |||
| source activate choppy | |||
| choppy install renluyao/NGScheckMates | |||
| ``` | |||
| # APP概述 | |||
| NGScheckMates是用来检测某几个测序数据是否来自于同一个人，有以下几种应用场景： | |||
| （1）多组学研究，RNAseq和DNAseq是否是来自同一个人； | |||
| （2）被标注为配对的Tumor和Normal样本是否是来自同一个人； | |||
| （3）同一批样本，多次测序，其中有没有被标错的样本。 | |||
| 推荐直接用fastq模式，优点：如果有多种不同测序文件，比如一个项目中有WES和RNAseq，你要研究WES找到的候选突变是否影响了基因表达量的改变，你需要检查WES和RNAseq的数据是否来自同一个人，以确保分析结果的正确性。直接用fastq模式可以不用单独对RNAseq call germline mutation，以节省时间。这一步将单独运行一个脚本。 | |||
| 基于fastq文件检查样本的配对情况的原理是：他们首先从dbSNP数据库中选择了21067个位于外显子上的SNP用于预测样本配对。对于不用比对的fastq模式，他们在参考基因组中寻找了可以与参考基因组完全匹配的21bp长度的k-mer，位于这些k-mer上的SNP只剩下了11696个。然后用k-mer扫描fastq文件，计算每个SNP的VAF，再根据多个SNP的VAF计算样本间两两的相关性判断两个样本是否来源于一个人。 | |||
|  | |||
| # 流程与参数 | |||
| - Required arguments | |||
| `-l` 需要检测的fastq或者fastq.gz文件的表格，格式如下： | |||
| ```bash | |||
| FASTQ_FILE1 (tab) FASTQ_FILE2 (tab) SAMPLE_NAME (\n) | |||
| Example: | |||
| /data/LSJ_R1.fastq /data/LSJ_R2.fastq LSJ | |||
| /data/LSH_R1.fastq /data/LSH_R2.fastq LSH | |||
| ``` | |||
| `-pt` 是一个包含SNP位点的二进制文件，这些位点可以用与样本的配对检查，在下载包中，路径为`SNP/SNP.pt` | |||
| `-O` 输出文件夹 | |||
| - Optional arguments | |||
| `-N` 输出文件夹的前缀，default：“output” | |||
| `-f` 当你的样本中有父母与孩子或者兄弟姐妹时，加上这个参数，使用更严格的VAF相关系数的阈值 | |||
| `-nz` Use the mean of non-zero depths across the SNPs as reference depth, default: Use the mean depth across all the SNPs | |||
| Then, another script, vaf_ncm.py is used to read a set of VAF files to complete the downstream analysis. When you need to analyze many FASTQ files, the first VAF file generation using ngscheckmate_fastq can be parallelized. | |||
| ### Getting Started | |||
| We recommend using choppy system and Aliyun OSS service. The command will look like this: | |||
| `-s` The read subsampling rate, default: 1.0 | |||
| `-d` The target depth for read subsampling. NGSCheckMate calculates a subsampling rate based on this target depth. | |||
| `-R` The length of the genomic region with read mapping (default: 3x10^9) used to compute subsampling rate. If your data is NOT human WGS and you use the -d option, it is highly recommended that specify this value. For instance, if your data is human RNA-seq, the genomic length with read mapping is ~3% of the human genome (1x10^8) | |||
| 注意：如果你的fastq文件特别大，它的计算会特别慢，三个参数的使用可以通过subsampling的方法加快运算速度，文献中报道只要0.5X深度的数据就能有很好的预测效果，有两种选择： | |||
| - 只使用 -s ，意思是fastq原始文件的百分之多少，如果你的fastq文件太大，运算速度很比较慢，可以使用其中一部分数据运算，不会影响运算结果，比如，30%就是`-s 0.3` | |||
| - 需要通过使用-d 和-R | |||
| `-L` The length of the flanking sequence of the SNPs, default: 21bp. It is not recommended that you change this value unless you create your own pattern file (.pt) with a different length. | |||
| `-p` 线程数，default：1 | |||
| # APP输入变量与输入文件 | |||
| （1）准备样本文件 | |||
| ```bash | |||
| choppy samples NGScheckMates --output samples | |||
| ``` | |||
| # Activate the choppy environment | |||
| $ open-choppy-env | |||
| samples文件中输入是 | |||
| - fastq_dir | |||
| fastq文件的地址，阿里云上的地址；如果需要使用多个项目的fastq文件，输入两个项目文件夹的上一级共同目录 | |||
| - Input_file | |||
| # Install the APP | |||
| $ choppy install YaqingLiu/NGSCheckMate_parallel-latest [-f] | |||
| 一个txt文件，需要进行计算的文件的详细文件名，文件的地址按照要求修改 | |||
| ```bash | |||
| #read1 #read2 #sample_name | |||
| /cromwell_inputs/*/directory_name/read1.fastq.gz /cromwell_inputs/*/directory_name/read2.fastq.gz sample_name | |||
| ``` | |||
| # APP输出结果 | |||
| # List the parameters | |||
| $ choppy samples YaqingLiu/NGSCheckMate_parallel-latest [--no-default] | |||
| # Submit you task with the `samples.json file` and `project name` | |||
| $ choppy batch YaqingLiu/NGSCheckMate_parallel-latest samples.json -p Project [-l project:Label] | |||
| # Query the status of all tasks in the project | |||
| $ choppy query -L project:Label | grep "status" | |||
| ``` | |||
| # 结果展示与解读 | |||
| #### samples.json | |||
| ``` json | |||
| { | |||
| "sample_id": "test", | |||
| "fastq1": ["fq1_1", "fq1_2", ..., "fq1_n"], | |||
| "fastq2": ["fq2_1", "fq2_2", ..., "fq2_n"], | |||
| "output_id": ["out_id1", "out_id2", ..., "out_idn"] | |||
| } | |||
| ``` | |||
| #### subsampling rate | |||
| The default subsampling rate is 0.3. | |||
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