Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Computational Methods for Next-Generation Comparative Genomics

ABSTRACT: Computational Methods for Next-Generation Comparative Genomics

PROVIDER: PRJNA671228 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Computational Genomics of Preeclampsia

Project description:Computational Genomics of Preeclampsia

| PRJNA809817 | ENA

Computational Genomics of Preeclampsia

Project description:Computational Genomics of Preeclampsia

| PRJNA809816 | ENA

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

Project description: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.

2025-08-26 | E-MTAB-15190 | biostudies-arrayexpress

Next-generation microbiology: from comparative genomics to gene function.

Project description: Not available

| S-EPMC8082670 | biostudies-literature

Systematic comparative analysis of single cell RNA-sequencing methods

Project description:A multitude of single-cell RNA sequencing methods have been developed in recent years, with dramatic advances in scale and power, and enabling major discoveries and large scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single cell and/or single nucleus profiling from three types of samples – cell lines, peripheral blood mononuclear cells and brain tissue – generating 36 libraries in six separate experiments in a single center. To analyze these datasets, we developed and applied scumi, a flexible computational pipeline that can be used for any scRNA-seq method. We evaluated the methods for both basic performance and for their ability to recover known biological information in the samples. Our study will help guide experiments with the methods in this study as well as serve as a benchmark for future studies and for computational algorithm development.

2019-06-01 | GSE132044 | GEO

Benchmarking of Computational Demultiplexing Methods for Single-Nucleus RNA Sequencing Data [dataset 2]

Project description:Benchmarking of Computational Demultiplexing Methods for Single-Nucleus RNA Sequencing Data [dataset 2]

| PRJNA1268588 | ENA

Benchmarking of Computational Demultiplexing Methods for Single-Nucleus RNA Sequencing Data [dataset 1]

Project description:Benchmarking of Computational Demultiplexing Methods for Single-Nucleus RNA Sequencing Data [dataset 1]

| PRJNA1268586 | ENA

Framingham BRain Imaging, cognition, Dementia and next generation GEnomics (BRIDGET)

Project description:Framingham BRain Imaging, cognition, Dementia and next generation GEnomics (BRIDGET)

| PRJNA755356 | ENA

Computational methods and translational applications for targeted next-generation sequencing platforms.

Project description: Not available