Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Comparative analysis of single-cell and spatial Nanopore long-read methods


ABSTRACT: Alternative splicing significantly contributes to transcriptome complexity and has critical implications for cellular functions. Recent advancements in single-cell isolation and capture techniques have enabled high-throughput quantification of gene expression at single-cell resolution. Long-read sequencing technologies can further be combined with single-cell technologies and enable an unambiguous identification of complete exon structures. Several computational methods have been developed to specifically address bioinformatics challenges associated with the processing of long read scRNA-seq data. Evaluating and comparing these computational methods becomes crucial. The goal of this study was to benchmark state-of-the-art computational tools for single-cell and spatial long-read transcriptomics. The scRNA-seq data were generated from two tumors developed by a mouse model, and designated as MPNST1 and MPNST2. Data were obtained by using the 10X Genomics technology, then generating sequencing libraries using either Illumina, Oxford Nanopore Technology (ONT) or scNaUmi-Seq protocols. Raw data were obtained after sequencing the libraries on Illumina, MinION or PromethION sequencing platforms. The two Illumina data were uploaded as part of the related submission E-MTAB-14222, with sample MPNST1 corresponding to 2020_23 and MPNST2 to 2022_26. This current submission contains the four long-read raw data et the data processed using the wf-single-cell pipeline. For the additional processed data, please refer to https://github.com/GenomiqueENS/scKenver.

INSTRUMENT(S): MinION, PromethION

ORGANISM(S): Mus musculus

SUBMITTER: genomiqueENS IBENS 

PROVIDER: E-MTAB-15190 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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