Hail VS gnomad-browser

I don't have any funding to hire right now, but I'm always happy to chat about the industry and my experience building Hail (https://hail.is, https://github.com/hail-is/hail), a tool widely used by folks with large collections of human sequences.

The other posters are not wrong about compensation. Total compensation is off by a factor of two to three.

However, it is absolutely possible to work with a group of top-notch engineers on serious distributed systems & compilers in service of an excellent scientific-user experience. I know because I do. We are lucky to have a PI who respects and hires and diversity of expertise within his lab.

I enjoy being deeply embedded with our users. I do not have to guess what they need or want because I help them do it every day.

I also enjoy enmeshing engineering with statistics, mathematics, and biology. Work is more interesting when so many disciplines conspire towards the end of improved human health.

I think this post is identifying scientific computing with simulation studies and legacy workflows, to a fault. Scientific computing includes those things, but it also includes interactive analysis of very large datasets as well as workflows designed around cloud computing.

Interactive analysis of large datasets (e.g. genome & exome sequencing studies with 100s of 1000s of samples) is well suited to low-latency, server-less, & horizontally scalable systems (like Dremel/BigQuery, or Hail [1], which we build and is inspired by Dremel, among other systems). The load profile is unpredictable because after a scientist runs an analysis they need an unpredictable amount of time to think about their next step.

As for productionized workflows, if we redesign the tools used within these workflows to directly read and write data to cloud storage as well as to tolerate VM-preemption, then we can exploit the ~1/5 cost of preemptible/spot instances.

One last point: for the subset of scientific computing I highlighted above, speed is key. I want the scientist to stay in a flow state, receiving feedback from their experiments as fast as possible, ideally within 300 ms. The only way to achieve that on huge datasets is through rapid and substantial scale-out followed by equally rapid and substantial scale-in (to control cost).

[1] https://hail.is

Broad Institute of MIT and Harvard | Cambridge, MA | Associate Software Engineer | Onsite

We are seeking an associate software engineer interested in contributing to an open-source data visualization library for analyzing the biological impact human genetic variation. You will contribute to projects like gnomAD (https://gnomad.broadinstitute.org), the world's largest catalogue of human genetic variation used by hundreds of thousands of researchers and help us scale towards millions of genomes in the coming years. We are also developing next-generation tools for enabling genetic analyses of large biobanks across richly phenotyped individuals (https://genebass.org). In this role you will gain experience developing data-intensive web applications with Typescript, React, Python, Terraform, Google Cloud Platform, and will make use of the scalable data analysis library Hail (https://hail.is). Key to our success is growing a strong team with a diverse membership who foster a culture of continual learning, and who support the growth and success of one another. Towards this end, we are committed to seeking applications from women and from underrepresented groups. We know that many excellent candidates choose not to apply despite their capabilities; please allow us to enthusiastically counter this tendency.

Please provide a CV and links previous work or projects, ideally with contributions visible on Github.

email: [email protected]

try one of these: GnomAD (https://gnomad.broadinstitute.org/) 1000 Genomes (http://browser.1000genomes.org) dbSNP (http://www.ncbi.nlm.nih.gov/snp)

Maybe you can ask the opposite question; what are the bounds of of a functional human being. https://gnomad.broadinstitute.org/ GnomAD is a aggregation of healthy human genetic sequences which was primarily built on the aggregated control groups of many genetic sequencing studies. There are studies of this data analysing the co-occurrence of variants in gnomAD which may help.

Maybe something like this? https://promethease.com/ Clinvar for variants that might be of clinical relevance. https://gnomad.broadinstitute.org/ for allele frequencies & some info about variants.

You could look at aggregation databases such as gnomad https://gnomad.broadinstitute.org/ anything with a frequency incompatible with the disease is likely non pathogenic

Broad Institute of MIT and Harvard | Cambridge, MA | Frontend Software Engineer | REMOTE or HYBRID (New England area)

We are hiring a frontend developer to help lead the next phase of the gnomAD browser, a web application for displaying the world's largest collection of human genome/exome sequences. https://gnomad.broadinstitute.org. Looking for applicants who are excited about data visualization and designing complex interfaces for scientific research.

Apply here: http://broad.io/cq7dw8

Broad Institute of MIT and Harvard | New England | Software Engineer | REMOTE/HYBRID

Our team is focused on building the tools necessary to visualize and interpret massive data sets of human genetic variation and functional genomic information. We have developed gnomAD (https://gnomad.broadinstitute.org), the world’s largest public reference dataset of human exomes and genomes. gnomAD has become one of the most widely used resources in the field, and is now the default reference database for virtually all clinical interpretation pipelines, as well as a standard analysis resource for a wide variety of genetic and biological studies. We estimate gnomAD has contributed to the clinical diagnosis of over 2 million patients with genetic disorders.

Your role will be to maintain the gnomAD browser, our open source web application for exploring gnomAD and related datasets, and develop new scientific functionality as we continue to grow to over 1 million human samples. You will work with a team of software engineers, computational biologists and clinical and research users to develop new features and visualizations that incorporate user feedback. Software engineering skills and an interest in user interface design and data visualization are key. Basic familiarity with genomics and DNA sequencing data is preferred, but not required. Most importantly, the ideal candidate will have enthusiasm for playing a critical role in a team-oriented project and learning new domains.

Minimum Requirements

If you're talking about humans, start with gnomAD: https://gnomad.broadinstitute.org/