QUARTIC: QUick pArallel algoRithms for high-Throughput sequencIng data proCessing

Frédéric Jarlier,Michael Mcmanus,Philippe Hupé,Thomas Magalhaes,Firmin Martin,Nicolas Fedy,Paul Paganiban,Nicolas Joly,Leonor Sirotti

doi:10.12688/f1000research.22954.1

Abstract

Life science has entered the so-called 'big data era' where biologists, clinicians and bioinformaticians are overwhelmed with unprecedented amount of data. High-throughput sequencing has revolutionized genomics and offers new insights to decipher the genome structure. However, using these data for daily clinical practice care and diagnosis purposes is challenging as the data are bigger and bigger. Therefore, we implemented software using Message Passing Interface such that the alignment and sorting of sequencing reads can easily scale on high-performance computing architecture. Our implementation makes it possible to reduce the time to delivery to few minutes, even on large whole-genome data using several hundreds of cores.

Highlights

Since the first generation sequencing technology was released in 2005 (Kchouk et al, 2017), considerable progress has been made in terms of sequencing quality, diversity of protocols and throughput of the machines
As we have entered the era of genomic medicine, delivering the results to the clinicians within a short delay to guide the therapeutic decision is a challenge of the utmost importance in daily clinical practice
In order to tackle the aforementioned challenges to align and sort the sequencing data, we developed software based on the Message Passing Interface (MPI) communication protocol (Gropp et al, 1996) that makes it possible to fully benefit of parallel architecture of supercomputers Hupé & Jarlier (2020a; 2020b)