bioRxivBioinformaticsPreprint
BarQC: Quality Control and Preprocessing for SPLiT-Seq Data
Abstract
SummarySPLiT-seq is a cost-effective single-cell RNA-sequencing method, easy to implement in most laboratories. However, the data preprocessing is not straightforward, and no solution currently exists to perform a basic quality control of the data. Here, we present BarQC, a quality control tool, which identifies and corrects barcodes in SPLiT-seq data and provides a report on the distribution of each barcode and UMI as well as an estimation of the number of cells present in the data. Additionally, BarQC can be incorporated in the preprocessing pipeline by constructing a sorted BAM file tagged with each barcode sequence. Availability of ImplementationBarQC was implemented in Python3, and its source code is freely available on GitHub at https://github.com/mayflylab/barQC/ under the MIT Licence. BarQC has been tested on a Linux server.
- assay: scRNA-seq
- research focus: batch correction / integration
- research focus: dimensionality reduction
- research focus: software / tool
- approach: statistical model
- Citations
- 1
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