TallyNN documentation

Droplet-based single-cell sequencing techniques have provided unprecedented insight into cellular heterogeneities within tissues. However, these approaches only allow for the measurement of the distal parts of a transcript following short-read sequencing. Therefore, splicing and sequence diversity information is lost for the majority of the transcript. The application of long-read Nanopore sequencing to droplet-based methods is challenging because of the low base-calling accuracy currently associated with Nanopore sequencing. Although several approaches that use additional short-read sequencing to error-correct the barcode and UMI sequences have been developed, these techniques are limited by the requirement to sequence a library using both short- and long-read sequencing. Here we introduce a novel approach termed single-cell Barcode UMI Correction sequencing (scBUC-seq) to efficiently error-correct barcode and UMI oligonucleotide sequences synthesized by using blocks of dimeric nucleotides.

TallyNN is a collection of single-cell workflows that allow users to perform barcode and UMI correction for oligonucleotide sequences that are synthesised using double phosphoramidites for droplet based single-cell sequencing.

The workflow management systems that underpins all of our pipelines is `CGAT-core <>https://github.com/cgat-developers/cgat-core>`_. We demonstrate the functionality of CGAT-core using a simple RNA-seq pipeline in cgat-showcase. Therefore, if you are not familiar with how we build our workflows I suggest that you look at these two pipelines first.

Citation

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