Category: fastq

In the event you need your linked-read data converted into a different linked-read format, djinn has you covered. We might disagree on the fragmented format landscape, but that doesn't mean you shouldn't be able to use your data how and where you want to. This command converts a paired-end read set of FASTQ files between the common linked-read FASTQ types.

You might want a table of the counts (frequency) of all the unique barcodes in your data and that's what is for. Records with missing barcodes are ignored.

You might want a list of all the unique barcodes in your data and will do just that.

You may be interested in retaining only "useful" linked reads, that is, reads with a valid barcode or reads that are not singletons (i.e. there are more than 2 reads with the same barcode). Like their names suggests, will remove invalid barcodes and will remove singletons. Each of these commands can optionally retain the removed reads in separate files.

When submitting sequences to NCBI, they reformat the read headers, which means any useful information in the read headers disappears. This applies to haplotagging, TELLseq, and stLFR FASTQ formats, where the barcode is encoded in the sequence header, and thus vanishes from the public archive when uploaded to NCBI. Obviously this isn't great, so we propose a simple approach to solving this problem: uploading sequence data as unaligned BAM files (recommended).

While downsampling (subsampling) FASTQ and BAM files is relatively simple with tools such as awk, samtools, seqtk, seqkit, etc., allows you to downsample a BAM file (or FASTQ(s)) by barcodes. That means you can keep all the reads associated with -d number of barcodes or fraction of barcodes (e.g. -d 0.5 will downsample to 50% of all barcodes).

Sometimes you want/need linked-read data to be sorted by barcode. In order to accomplish this with Djinn, the barcode must be in a SAM tag (e.g. BX, BC) FASTQ or SAM/BAM format. If your barcodes aren't in a SAM tag, consider using or to convert it into a compliant format.

The nature of HI-C data is such that paired-end reads in a FASTQ file are expected to be: If you're familiar with what linked-reads are, you might think "oh hey, characteristic #2 sounds kind of similar to what we do". Well, we think so too-- reads with the same barcodes should have originated from the same original strand of DNA. So, given how prevalent HI-C data is in genome assemblers (scaffolders specifically), couldn't we modify linked-read data to also conform to characteristic #1? We're sure interested in figuring that out. Use first to sort input FASTQ files by barcode before attempting spoofing.

In the effort of making it painless to have your data in the preferred standard format, use to quickly standardize FASTQ and BAM files. By default, standardization just moves the barcode (wherever it may be) into a BX:Z SAM tag as-is and does a technology-appropriate validation of the barcode value, which it writes to the VX:i tag. However, you can use --style to also convert the barcode style between formats. Keep in mind that each barcode style has a different upper limit as to how many unique barcodes it can support, which may prevent successful conversions. The styles are given as: