# klassify [![Crates.io](https://img.shields.io/crates/v/klassify.svg)](https://crates.io/crates/klassify) [![Github Actions](https://github.com/tanghaibao/klassify/actions/workflows/rust.yml/badge.svg)](https://github.com/tanghaibao/klassify/actions) ![klassify-logo](https://www.dropbox.com/scl/fi/bjvfamep0aoxka0dcg2zi/klassify-logo.png?rlkey=8vmvacehs2amuaoi0gvgyh28r&st=ohygf458&raw=1) Classify chimeric reads based on unique kmer contents and identify the breakpoint locations. The breakpoints can be due to: - Recombination / crossover events - Structural variations While there are many tools that can identify structural variations, this tool is designed to compare progeny (e.g. F1) reads to the parental genome. The key idea is an extension to the trio binning approach, where we use the unique kmers from each chromosome/contig of the parental genomes to classify the reads that bridge two different chromosomes/contigs. Following are examples of recominant reads identified by this tool: ![recombinant-read](https://www.dropbox.com/scl/fi/tduxwsh0wcy2zdw8zopdm/recombinant-reads.png?rlkey=xci43gwwy84dbcdvs2n7ekk18&st=sewwc9s0&raw=1) ## Installation ```bash cargo install klassify ``` ## Usage Suppose you have 3 input files: - `parents.genome.fa`: the parental genomes - `f1_reads.fa`: the progeny reads - `parent_reads.fa`: the parental reads 1. Create a database of unique kmers from the parental genomes ```console mkdir ref faSplit byname parents.genome.fa ref/ klassify build ref/*.fa -o kmers.bc ``` This generates an index for all the unique kmers (present in a single contig/chromosome). 2. Classify the progeny (e.g. F1) reads based on the unique kmers ```console mkdir f1_reads f1_classify faSplit about f1_reads.fa 2000000000 f1_reads/ klassify classify kmers.bc f1_reads/*.fa -o f1_classify ``` 3. Map ‘chimeric’ progeny reads to the parents reference ```console klassify extract f1_classify.filtered.tsv f1_reads/*.fa -o f1_classify.fa minimap2 -t 80 -ax map-hifi --eqx --secondary=no parents.genome.fa f1_classify.fa \ --split-prefix f1_classify | samtools sort -@ 8 -o f1_classify.bam ``` 4. Repeat the steps using the parental reads ```console mkdir parent_reads parent_classify faSplit about parent_reads.fa 2000000000 parent_reads/ klassify classify kmers.bc parent_reads/*.fa -o parent_classify klassify extract parent_classify.filtered.tsv parent_reads/*.fa -o parent_classify.fa minimap2 -t 80 -ax map-hifi --eqx --secondary=no parents.genome.fa parent_classify.fa \ --split-prefix parent_classify | samtools sort -@ 8 -o parent_classify.bam ``` 5. Using parent reads as ‘control’, identify the ‘chimeric’ regions that show up with F1 reads, but NOT with parent reads (so we are not affected by assembly errors) ```console klassify regions f1_classify.bam parent_classify.bam ``` That's it! The breakpoint locations in the parental genomes are in `f1_classify.regions.tsv`, where column 2 has the depth within each 10kb bin around the breakpoint: ```console SoChr01A:118800000-118810000 10 SoChr01B:43130000-43150000 8,12 ```