Datasets associated with the publication of the "satuRn" R package

Name: Datasets associated with the publication of the "satuRn" R package
Keywords: FOS: Computer and information sciences, Bioinformatics, Differential transcript usage, RNA-Seq, Biostatistics, Single-cell transcriptomics

Gilis, Jeroen; Vitting-Seerup, Kristoffer; Van den Berge, Koen; Clement, Lieven

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ZENODO

Dataset . 2022

License: CC BY

Data sources: Datacite

ZENODO

Dataset . 2021

License: CC BY

Data sources: Datacite

ZENODO

Dataset . 2021

License: CC BY

Data sources: Datacite

ZENODO

Dataset . 2022

License: CC BY

Data sources: Datacite

ZENODO

Dataset . 2022

License: CC BY

Data sources: Datacite

ZENODO

Dataset . 2021

License: CC BY

Data sources: Datacite

Datasets associated with the publication of the "satuRn" R package

Research datakeyboard_double_arrow_right Dataset 14 Jan 2021 English Publisher:Zenodo

Authors: Gilis, Jeroen; Vitting-Seerup, Kristoffer; Van den Berge, Koen; Clement, Lieven;

doi: 10.5281/zenodo.6826603 , 10.5281/zenodo.4438789 , 10.5281/zenodo.4438474 , 10.5281/zenodo.6810984 , 10.5281/zenodo.4438473 , 10.5281/zenodo.4439415

Datasets associated with the publication of the "satuRn" R package

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Abstract

On this Zenodo link, we share the data that is required to reproduce all the analyses from our publication "satuRn: Scalable Analysis of differential Transcript Usage for bulk and single-cell RNA-sequencing applications". This repository includes input transcript-level expression matrices and metadata for all datasets, as well as intermediate results and final outputs of the respective DTU analyses. For a more elaborate description of the data, we refer to the companion GitHub for our publications; https://github.com/statOmics/satuRnPaper. Note that this is version 1.0.3 of the data (uploaded on 2022-07-08). If any changes were to be made to the datasets in the future, this will also be communicated on our companion GitHub page.

Related Organizations

Ghent University
Belgium
University of Copenhagen
Denmark

Keywords

FOS: Computer and information sciences, Bioinformatics, Differential transcript usage, RNA-Seq, Biostatistics, Single-cell transcriptomics

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