Lifebit Blog

November 1, 2018

Dr. Martin Steinegger: Metagenomic data analysis on steroids.

Dr. Martin Steinegge has always been obsessed with: how can we get insights from analysing massive amounts of metagenomics data in only minutes, instead of the days and weeks that the process currently takes.

Categories Bioinformatics Frontiers

October 22, 2018

nf-core: a community-driven initiative to standardise Nextflow-based pipelines

The main goal of nf-core is to establish best practices concerning pipelines that are built with Nextflow.

Categories Bioinformatics/Open Source

October 5, 2018

Get your genomics & big data analysis 90% cheaper over AWS through spot instances

On paper, cloud computing is a relatively straightforward model which allows access to compute and storage resources. However, the reality of cloud pricing can be quite complex.

Categories Cloud computing

August 2, 2018

Bioinformaticians: Hidden Superheroes are key to fighting cancer

Although the issues associated with sequencing have mostly been resolved, the raw data generated from the sequencing process is useless unless you can give it meaning. That’s where the unsung superheroes come in: bioinformaticians.

Categories Bioinformatics Frontiers

July 5, 2018

Bringing together high-quality open-source community resources with CloudOS

Over the last few years open-source has been increasingly becoming the norm, even in Bioinformatics. The number of high-quality applications which are freely available on GitHub and other Git providers is increasing, such as the pipelines that the Broad institute uses for production.

Categories Bioinformatics/Open Source/Product

June 19, 2018

DeepVariant as a Nextflow Pipeline on CloudOS

In December 2017, the team at Google Brain joined the effort by releasing an open source, deep learning based variant caller: DeepVariant. DeepVariant outperforms its competitors by accuracy – it even won the accuracy award at the precision FDA Truth Challenge.

Categories Bioinformatics/Open Source/Product

June 14, 2018

Improving genomic analyses over cloud using Grakn

Let’s focus on where Grakn makes a difference for us: what is the best resource to run specific analyses over cloud? We needed a technology that would allow us to both efficiently store our data and easily use it to train an ML model.

Categories Bioinformatics/Cloud computing