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Archiving data

It’s common [and often required] practice to upload sequence data onto a public repository. Because linked-read barcodes are technical sequences (as opposed to biological ones), storing linked-read data with inline barcode sequences would reqiure downstream demultiplexing. The risk there is that technologies may change barcode configurations, barcode ‘whitelists’, or demultuplexing software may no longer be supported, which makes accurate end-user demultiplexing challenging and very brittle.

The natural alternative would seem to be storing the linked-read barcode in the sequence header, which is how haplotagging, BLink-seq, stLFR, and TELL-seq all do it, even if they do so in different ways. While on its face this seems like a non-issue, NCBI (and possibly others) reformat the read headers, effectively removing any traces of linked-read information. Obviously this isn’t great, so we propose a simple approach to solving this problem: uploading sequence data as unaligned BAM files.

NCBI accepts unaligned BAM files as a valid data format for submission. This solves multiple problems at once:

  1. All SAM tags are retained, meaning barcodes in the BX:Z tag and their validations in VX:i are retained
  2. Conversion between FASTQ and SAM is lossless and effortlessly supported by common tools like samtools
  • samtools import converts FASTQ to SAM/BAM
  • samtools fastq converts SAM/BAM to FASTQ
  1. Paired-end read files can be interleaved into a single BAM file and retrieved as such, reducing file tracking
  • read 1/2 information is stored in a SAM record, so conversions will accurately restore read 1 and read 2

We strongly urge uploading linked-read sequences to NCBI as interleaved unaligned BAM files so as to not waste precious linked-read data.