A single-cell RNA-sequencing training and analysis suite using the Galaxy framework | Zendy

Mehmet Tekman | Zendy; Bérénice Batut | Zendy; Alexander Ostrovsky | Zendy; Christophe Antoniewski | Zendy; Dave Clements | Zendy; Fidel Ramírez | Zendy; Graham Etherington | Zendy; Hans-Rudolf Hotz | Zendy; Jelle Scholtalbers | Zendy; Jonathan Manning | Zendy; Léa Bellenger | Zendy; Maria Doyle | Zendy; Mohammad Heydarian | Zendy; Ni Huang | Zendy; Nicola Soranzo | Zendy; Pablo Moreno | Zendy; Stefan Mautner | Zendy; Irene Papatheodorou | Zendy; Anton Nekrutenko | Zendy; James Taylor | Zendy; Daniel Blankenberg | Zendy; Rolf Backofen | Zendy; Björn Grüning | Zendy

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A single-cell RNA-sequencing training and analysis suite using the Galaxy framework

Author(s) -

Mehmet Tekman,

Bérénice Batut,

Alexander Ostrovsky,

Christophe Antoniewski,

Dave Clements,

Fidel Ramírez,

Graham Etherington,

Hans-Rudolf Hotz,

Jelle Scholtalbers,

Jonathan Manning,

Léa Bellenger,

Maria Doyle,

Mohammad Heydarian,

Ni Huang,

Nicola Soranzo,

Pablo Moreno,

Stefan Mautner,

Irene Papatheodorou,

Anton Nekrutenko,

James Taylor,

Daniel Blankenberg,

Rolf Backofen,

Björn Grüning

Publication year - 2020

Publication title -

gigascience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.947

H-Index - 54

ISSN - 2047-217X

DOI - 10.1093/gigascience/giaa102

Subject(s) - computer science , workflow , interoperability , software , data science , data mining , world wide web , database , programming language

The vast ecosystem of single-cell RNA-sequencing tools has until recently been plagued by an excess of diverging analysis strategies, inconsistent file formats, and compatibility issues between different software suites. The uptake of 10x Genomics datasets has begun to calm this diversity, and the bioinformatics community leans once more towards the large computing requirements and the statistically driven methods needed to process and understand these ever-growing datasets.

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