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.
Included within this repo are three workflows:
- pipeline_nanopore - a workflow that facilitates the analysis of scBUC-seq nanopore single-cell sequencing data.
- pipeline_illumina - this is a workflow that processes scBUC-seq dinucleotide block single-cell data that has been illumina sequenced. The workflow takes as an input a fastq file and collapses barcode and UMI so that users can procedd their sequencing data using kallisto bustools.
- pipeline_fusiontrans - this pipeline processes nanopore sequencing data and detects the presence of fusion transcripts.
We reccomend installing miniconda, then creating a new environment and install mamba
conda install mamba -c conda-forge
Next install the required software using the conda yml file
mamba env update --file conda/environments/tallynn.yml
Activate the condda environment
conda activate tallynn
Then, you will need to manually install TallyNN and the fork of umi tools. The fork is added as a submodule to this repo to help you easily install.
# Clone the TallyNN repo
git clone https://github.com/Acribbs/TallyNN.git
# Install TallyNN code
python setup.py install
# Next install UMI-tools fork to allow doublet deduplication
git clone https://github.com/Acribbs/UMI-tools.git
git checkout AC-dualoligo
python setup.py install
Further information how you can run the pipelines can be found at read the docs
Run the tallynn --help command to see what workflows are available and tallynn nanopore -help to see how to use them.
For example, to generate a configuration file run
tallynn nanopore config
To set up the configuration file please refer to read the docs.
To run the pipeline with all tasks then run
tallynn nanopore make full -v5
The bioRxiv manuscript accompanying this code can be found here: