Related Experiment Video
Updated: Dec 9, 2025

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets
Published on: February 23, 2024
QUARTIC: QUick pArallel algoRithms for high-Throughput sequencIng data proCessing
Frédéric Jarlier1,2,3,4, Nicolas Joly5, Nicolas Fedy1,2,3,4,6
1Institut Curie, Paris, F-75005, France.
Abstract:
Life science has entered the so-called 'big data era' where biologists, clinicians and bioinformaticians are overwhelmed with high-throughput sequencing data. While they offer new insights to decipher the genome structure they also raise major challenges to use them for daily clinical practice care and diagnosis purposes as they are bigger and bigger. Therefore, we implemented a software to reduce the time to delivery for the alignment and the sorting of high-throughput sequencing data. Our solution is implemented using Message Passing Interface and is intended for high-performance computing architecture. The software scales linearly with respect to the size of the data and ensures a total reproducibility with the traditional tools. For example, a 300X whole genome can be aligned and sorted within less than 9 hours with 128 cores. The software offers significant speed-up using multi-cores and multi-nodes parallelization.
Related Concept Videos
RNA-seq
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
Next-generation Sequencing
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
Sanger Sequencing
Parallel Processing
Maxam-Gilbert Sequencing
Challenges of the Maxam-Gilbert Method
The...

