Data management, bioinformatics and statistics

Introduction

The INF project is the central data management and analysis project of miTarget. Four important demands (work packages 1-4) will be addressed:

WP1: an overall data management platform (iRODS) for metagenome data to keep all data organized, documented and searchable

WP2: scalable and reproducible bioinformatic software pipelines (Nextflow)for metagenome analyses

WP3: customized statistical methods to address project-specific research questions related to the microbiome as a therapeutic target arising from the individual subprojects.

Aims

We here aim

To manage an overall data management platform (iRODS) for metagenome data to keep all data organized, documented and searchable
To develop scalable and reproducible bioinformatic software pipelines (Nextflow) for metagenome analyses
To customize statistical methods to address project-specific research questions related to the microbiome as a therapeutic target arising from the individual subprojects.

Fig. 2: Example of containerised bioinformatic workflows

Project-related publications

INF

1000× faster than PLINK: Combined FPGA and GPU accelerators for logistic regression-based detection of epistasis

Wienbrandt L, Kässens JC, Hübenthal M, Ellinghaus D

Journal of Computational Science

2018

INF

Whole-genome sequencing of a sporadic primary immunodeficiency cohort

Thaventhiran JED, Allen HL, Burren OS, Farmery JHR, Staples E, Zhang Z, Rae W, Greene D, Simeoni I, Maimaris J, Penkett C, Stephens J, Deevi SVVI, Sanchis-Juan A, Gleadall NS, Thomas MJ, Sargur RB, Gordins P, Baxendale HE, Brown M, Tuijnenburg P, Worth A, Hanson S, Linger R, Buckland MS, Rayner-Matthews PJ, Gilmour KC, Samarghitean C, Seneviratne SL, Lyons PA, Sansom DM, Lynch AG, Megy K, Ellinghaus E, Ellinghaus D, Jorgensen SF, Karlsen TH, Stirrups KE, Cutler AJ, Kumararatne DS, NBR-RDPIDConsortium, NIHRBioResource, Savic S, Burns SO, Kuijpers TW, Turro E, Ouwehand WH, Thrasher AJ, Smith KGC

PubMed (PMID: 32499645)

Nature

2020