Generating a VAF file from one FASTQ file parallelly. And then parallelized read the set of VAF files by vaf_ncm.py.
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  1. ### NGSCheckMate
  2. 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).
  3. 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.
  4. **If you want to analyze the correlation of samples over multiple runs, I suggest you to save the historical `vaf` files and download the NGSCheckMate from https://github.com/parklab/NGSCheckMate and then run vaf_ncm.py locally.**
  5. ### Getting Started
  6. We recommend using choppy system and Aliyun OSS service. The command will look like this:
  7. ```
  8. # Activate the choppy environment
  9. $ open-choppy-env
  10. # Install the APP
  11. $ choppy install YaqingLiu/NGSCheckMate_parallel-latest [-f]
  12. # List the parameters
  13. $ choppy samples YaqingLiu/NGSCheckMate_parallel-latest [--no-default]
  14. # Submit you task with the `samples.json file` and `project name`
  15. $ choppy batch YaqingLiu/NGSCheckMate_parallel-latest samples.json -p Project [-l project:Label]
  16. # Query the status of all tasks in the project
  17. $ choppy query -L project:Label | grep "status"
  18. ```
  19. #### samples.json
  20. ``` json
  21. {
  22. "sample_id": "test",
  23. "fastq1": ["fq1_1", "fq1_2", ..., "fq1_n"],
  24. "fastq2": ["fq2_1", "fq2_2", ..., "fq2_n"],
  25. "output_id": ["out_id1", "out_id2", ..., "out_idn"]
  26. }
  27. ```
  28. #### other parameters
  29. subsampling_rate: The default subsampling rate is 1. The speed is not very slow.
  30. -f in vaf_ncm.wdl: Use strict VAF correlation cutoffs. Recommended when your data may include related individuals (parents-child, siblings).