AsaruSim: a single-cell and spatial RNA-Seq Nanopore long-reads simulation workflow DOI Creative Commons

Ali Hamraoui,

Laurent Jourdren, Morgane Thomas‐Chollier

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Сен. 24, 2024

Abstract Motivation The combination of long-read sequencing technologies like Oxford Nanopore with single-cell RNA (scRNAseq) assays enables the detailed exploration transcriptomic complexity, including isoform detection and quantification, by capturing full-length cDNAs. However, challenges remain, lack advanced simulation tools that can effectively mimic unique complexities scRNAseq datasets. Such are essential for evaluation optimization methods dedicated to long read studies. Results We developed AsaruSim, a workflow simulates synthetic datasets, closely mimicking real experimental data. AsaruSim employs multi-step process includes creation UMI count matrix, generation perfect reads, optional PCR amplification, introduction errors, comprehensive quality control reporting. Applied dataset human peripheral blood mononuclear cells (PBMCs), accurately reproduced characteristics. Availability implementation source code full documentation available at: https://github.com/GenomiqueENS/AsaruSim . Data availability 1,090 Human PBMCs matrix cell type annotation files accessible on zenodo under DOI: 10.5281/zenodo.12731408.

Язык: Английский

Simulation of nanopore sequencing signal data with tunable parameters DOI
Hasindu Gamaarachchi, James M. Ferguson, Hiruna Samarakoon

и другие.

Genome Research, Год журнала: 2024, Номер 34(5), С. 778 - 783

Опубликована: Май 1, 2024

In silico simulation of high-throughput sequencing data is a technique used widely in the genomics field. However, there currently lack effective tools for creating simulated from nanopore devices, which measure DNA or RNA molecules form time-series current signal data. Here, we introduce Squigulator, fast and simple tool realistic Squigulator takes reference genome, transcriptome, read sequences, generates corresponding raw This compatible with basecalling software Oxford Nanopore Technologies (ONT) other third-party tools, thereby providing useful substrate development, testing, debugging, validation, optimization at every stage analysis workflow. The user may generate preset parameters emulating specific ONT protocols noise-free “ideal” data, they deterministically modify range experimental variables and/or noise to shape their needs. We present brief example Squigulator's use, model degree different impact accuracy downstream variant detection. reveals new insights into nature algorithms. provide as an open-source community.

Язык: Английский

Процитировано

10
AsaruSim: a single-cell and spatial RNA-Seq Nanopore long-reads simulation workflow DOI Creative Commons

Ali Hamraoui,

Laurent Jourdren, Morgane Thomas‐Chollier

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Сен. 24, 2024

Abstract Motivation The combination of long-read sequencing technologies like Oxford Nanopore with single-cell RNA (scRNAseq) assays enables the detailed exploration transcriptomic complexity, including isoform detection and quantification, by capturing full-length cDNAs. However, challenges remain, lack advanced simulation tools that can effectively mimic unique complexities scRNAseq datasets. Such are essential for evaluation optimization methods dedicated to long read studies. Results We developed AsaruSim, a workflow simulates synthetic datasets, closely mimicking real experimental data. AsaruSim employs multi-step process includes creation UMI count matrix, generation perfect reads, optional PCR amplification, introduction errors, comprehensive quality control reporting. Applied dataset human peripheral blood mononuclear cells (PBMCs), accurately reproduced characteristics. Availability implementation source code full documentation available at: https://github.com/GenomiqueENS/AsaruSim . Data availability 1,090 Human PBMCs matrix cell type annotation files accessible on zenodo under DOI: 10.5281/zenodo.12731408.

Язык: Английский

Процитировано

0