Large scale microbiome profiling in the cloud.

ABSTRACT:

Motivation

Bacterial metagenomics profiling for metagenomic whole sequencing (mWGS) usually starts by aligning sequencing reads to a collection of reference genomes. Current profiling tools are designed to work against a small representative collection of genomes, and do not scale very well to larger reference genome collections. However, large reference genome collections are capable of providing a more complete and accurate profile of the bacterial population in a metagenomics dataset. In this paper, we discuss a scalable, efficient and affordable approach to this problem, bringing big data solutions within the reach of laboratories with modest resources.

Results

We developed Flint, a metagenomics profiling pipeline that is built on top of the Apache Spark framework, and i

SUBMITTER: Valdes C 

PROVIDER: S-EPMC6612844 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature