Flow: a web platform and open database to analyse, store, curate and share bioinformatics data at scale

Charlotte Capitanchik; Sam M Ireland; J. Alex Harston; Chris Cheshire; D. Marc Jones; Flora C. Y. Lee; Igor Ruiz de los Mozos; Ira Alexandra Iosub; Klara Kuret; Rupert Faraway; Oscar G. Wilkins; Rahul Arora; Martina Hallegger; Miha Modic; Anob M. Chakrabarti; Nicholas M. Luscombe; Jernej Ule

doi:10.1101/2023.08.22.544179

BioinformaticsbioRxivAug 22, 2023

Preprint

Flow: a web platform and open database to analyse, store, curate and share bioinformatics data at scale

Charlotte Capitanchik iD, Sam M Ireland iD, J. Alex Harston iD, Chris Cheshire iD, D. Marc Jones iD, Flora C. Y. Lee iD, Igor Ruiz de los Mozos iD, Ira Alexandra Iosub iD, Klara Kuret iD, Rupert Faraway iD, Oscar G. Wilkins iD, Rahul Arora iD, Martina Hallegger iD, Miha Modic iD, Anob M. Chakrabarti iD, Nicholas M. Luscombe iD, Jernej Ule iD

Abstract

Ever-increasing volumes of sequencing data offer potential for large-scale meta-analyses to address significant biological questions. However, challenges such as insufficient data processing information, data quality concerns, and issues related to accessibility and curation often present obstacles. Additionally, most experimental biologists lack the time and expertise needed to independently analyse, manage and share their own data. To overcome these hurdles, we present Flow, a web-based platform that links bioinformatic analysis and database solutions with a user-friendly interface and web API. Flow currently accommodates a range of genomics methods and further DSL2-compliant Nextflow pipelines can be added via a simple JSON schema file. Deployable on local systems or cloud services, an instance is freely accessible to academic researchers at https://flow.bio.

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