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Split Pool Ligation-based Single-cell Transcriptome sequencing (SPLiT-seq) data processing pipeline comparison

Authors :
Kuijpers, Lucas
Hornung, Bastian
van den Hout - van Vroonhoven, Mirjam C.G.N.
van IJcken, Wilfred F.J.
Grosveld, Frank
Mulugeta, Eskeatnaf
Kuijpers, Lucas
Hornung, Bastian
van den Hout - van Vroonhoven, Mirjam C.G.N.
van IJcken, Wilfred F.J.
Grosveld, Frank
Mulugeta, Eskeatnaf
Source :
Kuijpers , L , Hornung , B , van den Hout - van Vroonhoven , M C G N , van IJcken , W F J , Grosveld , F & Mulugeta , E 2024 , ' Split Pool Ligation-based Single-cell Transcriptome sequencing (SPLiT-seq) data processing pipeline comparison ' , BMC Genomics , vol. 25 , no. 1 , 361 .
Publication Year :
2024

Abstract

Background: Single-cell sequencing techniques are revolutionizing every field of biology by providing the ability to measure the abundance of biological molecules at a single-cell resolution. Although single-cell sequencing approaches have been developed for several molecular modalities, single-cell transcriptome sequencing is the most prevalent and widely applied technique. SPLiT-seq (split-pool ligation-based transcriptome sequencing) is one of these single-cell transcriptome techniques that applies a unique combinatorial-barcoding approach by splitting and pooling cells into multi-well plates containing barcodes. This unique approach required the development of dedicated computational tools to preprocess the data and extract the count matrices. Here we compare eight bioinformatic pipelines (alevin-fry splitp, LR-splitpipe, SCSit, splitpipe, splitpipeline, SPLiTseq-demultiplex, STARsolo and zUMI) that have been developed to process SPLiT-seq data. We provide an overview of the tools, their computational performance, functionality and impact on downstream processing of the single-cell data, which vary greatly depending on the tool used. Results: We show that STARsolo, splitpipe and alevin-fry splitp can all handle large amount of data within reasonable time. In contrast, the other five pipelines are slow when handling large datasets. When using smaller dataset, cell barcode results are similar with the exception of SPLiTseq-demultiplex and splitpipeline. LR-splitpipe that is originally designed for processing long-read sequencing data is the slowest of all pipelines. Alevin-fry produced different down-stream results that are difficult to interpret. STARsolo functions nearly identical to splitpipe and produce results that are highly similar to each other. However, STARsolo lacks the function to collapse random hexamer reads for which some additional coding is required. Conclusion: Our comprehensive comparati

Details

Database :
OAIster
Journal :
Kuijpers , L , Hornung , B , van den Hout - van Vroonhoven , M C G N , van IJcken , W F J , Grosveld , F & Mulugeta , E 2024 , ' Split Pool Ligation-based Single-cell Transcriptome sequencing (SPLiT-seq) data processing pipeline comparison ' , BMC Genomics , vol. 25 , no. 1 , 361 .
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1434546387
Document Type :
Electronic Resource