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Scywalker:适用于长读长单细胞转录组测序的可扩展端到端数据分析工作流程。

Scywalker: scalable end-to-end data analysis workflow for long-read single-cell transcriptome sequencing.

机构信息

Neuromics Support Facility, VIB Center for Molecular Neurology, VIB, Universiteitsplein 1, Antwerp, 2610, Belgium.

Department of Biomedical Sciences, University of Antwerp, Universiteitsplein 1, Antwerp, 2610, Belgium.

出版信息

Bioinformatics. 2024 Sep 2;40(9). doi: 10.1093/bioinformatics/btae549.

DOI:10.1093/bioinformatics/btae549
PMID:39254601
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11419950/
Abstract

MOTIVATION

Existing nanopore single-cell data analysis tools showed severe limitations in handling current data sizes.

RESULTS

We introduce scywalker, an innovative and scalable package developed to comprehensively analyze long-read sequencing data of full-length single-cell or single-nuclei cDNA. We developed novel scalable methods for cell barcode demultiplexing and single-cell isoform calling and quantification and incorporated these in an easily deployable package. Scywalker streamlines the entire analysis process, from sequenced fragments in FASTQ format to demultiplexed pseudobulk isoform counts, into a single command suitable for execution on either server or cluster. Scywalker includes data quality control, cell type identification, and an interactive report. Assessment of datasets from the human brain, Arabidopsis leaves, and previously benchmarked data from mixed cell lines demonstrate excellent correlation with short-read analyses at both the cell-barcoding and gene quantification levels. At the isoform level, we show that scywalker facilitates the direct identification of cell-type-specific expression of novel isoforms.

AVAILABILITY AND IMPLEMENTATION

Scywalker is available on github.com/derijkp/scywalker under the GNU General Public License (GPL) and at https://zenodo.org/records/13359438/files/scywalker-0.108.0-Linux-x86_64.tar.gz.

摘要

动机

现有的纳米孔单细胞数据分析工具在处理当前数据规模方面存在严重的局限性。

结果

我们引入了 scywalker,这是一个创新的、可扩展的软件包,旨在全面分析全长单细胞或单个细胞核 cDNA 的长读测序数据。我们开发了新颖的可扩展方法,用于细胞条码解复用和单细胞异构体调用和定量,并将其纳入一个易于部署的软件包中。Scywalker 将整个分析过程从 FASTQ 格式的测序片段到解复用的伪群体异构体计数简化为单个命令,适合在服务器或集群上执行。Scywalker 包括数据质量控制、细胞类型识别和交互式报告。对来自人脑、拟南芥叶片以及之前经过基准测试的混合细胞系数据集的评估表明,在细胞条码和基因定量水平上与短读分析具有极好的相关性。在异构体水平上,我们表明 scywalker 有助于直接识别新型异构体的细胞类型特异性表达。

可用性和实现

scywalker 可在 github.com/derijkp/scywalker 上根据 GNU 通用公共许可证 (GPL) 获得,并可在 https://zenodo.org/records/13359438/files/scywalker-0.108.0-Linux-x86_64.tar.gz 获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6055/11419950/27c4bf0aec2a/btae549f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6055/11419950/2ecf0e28d171/btae549f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6055/11419950/974662189f56/btae549f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6055/11419950/4a2913a0f33e/btae549f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6055/11419950/27c4bf0aec2a/btae549f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6055/11419950/2ecf0e28d171/btae549f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6055/11419950/974662189f56/btae549f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6055/11419950/4a2913a0f33e/btae549f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6055/11419950/27c4bf0aec2a/btae549f4.jpg

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