A suite of bioinformatics tools for interacting with high throughput sequencing (HTS) data, written entirely in Rust
Extract and print metadata about an HTS file. For FASTQs, this includes number of bases, number of records, and all the instruments the records come from.
Filter an HTS file by its query names. Not currently implemented.
Calculate the Jaccard index for each pair in a set of BED files. Not currently implemented.
Calculate the k-mer spectra of an HTS file. Not currently implemented.
Organize a batch of raw sequencing data.
This takes a folder directly from an Illumina sequencer with FASTQ files and organizes them as follows, ready for alginment and quality control:
shell
YYMMDD_INSTID_RUN_FCID/
├── FASTQs/ # home for your raw data
├── Sample1_R1.fastq.gz
├── Sample1_R2.fastq.gz
└── ...
├── Aligned/ # a home for your aligned data
├── Reports/ # QC reports, etc files
├── config.tsv # a table of samples (rows) x features (cols)
├── cluster.yaml # a yaml file of cluster parameters for jobs in the Snakefile
├── README.md # description of the folder, data contents
├── setup.log # a log of what operations were performed with `bjt org`
└── Snakefile # Snakemake workflow file
Benchmarks on run in a Windows 10 computer, Intel i5 750 @ 2.67 GHz processor with 12 GB of RAM.
Times are listed +/- standard deviation, using hyperfine --warmup 2.
| File | # Reads | tgzip | tplain |
| ---------------------- | ------- | -------------------- | --------------------- |
| examples/SRR0000001.fastq | 2 500 | 17.0 ms +/- 0.9 ms | 12.8 ms +/- 1.0 ms |
| examples/SRR0000002.fastq | 25 000 | 78.4 ms +/- 3.3 ms | 16.6 ms +/- 0.6 ms |
| M_abscessus_HiSeq.fq | 5 682 010 | 12.323 s +/- 0.227 s | 951.5 ms + 5.6 ms |