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Hiring in Neurodiscovery

Posted on 04, Jul, 2013 by in and

Hiring in Neurodiscovery

Senior and Junior Bioinformatician at CHB

We currently have openings at HSPH for one senior and one junior bioinformatician as we expand our bioinformatics support to the Harvard NeuroDiscovery Center (HNDC), adding a bioinformatics core to the existing range of core facilities, research platforms and funding opportunities the HNDC provides to investigators seeking to understand the nervous system and associated diseases.

Your tasks includes supporting ad hoc projects which usually are associated with very short, grant-related deadlines, collaborative projects with challenging methods development and analytical tasks, and developing sequencing workflows in close coordination with the research computing team at FAS. If you enjoy playing with GATK, parallel computing and sequencing data we would love to talk to you.

Still interested?

To apply, please email a CV and cover letter to Oliver Hofmann. If you have additional question please contact us via email or Twitter.

RNA-Seq workshop November 28th

Posted on 24, Nov, 2012 by in

The HSPH Center for Health Bioinformatics, through the Harvard Clinical and Translational Science Center will be offering a one-day introductory workshop on RNA-sequencing this November 28th, 9am-5pm at the Countway Library, Room 403. The workshop will cover best practices for quality control, read alignment, and expression analysis using RNA-seq data. No prior programming experience or command line training is required.

Space is limited, register now if you would like to attend.

Who should attend

Researchers who:

• are generating, or hope to generate RNAseq data
• want to use a simple, graphical interface to analyse their results
• want to analyse their results in a reproducible fashion

Format

The workshop will introduce basic concepts and illustrate an end-to-end
data analysis workflow through live tutorials using the Galaxy
analytical framework. At the end of this activity, participants will
be able to start their own Galaxy servers using Amazon’s EC2 environment
to analyze their data, without using the command line.

Schedule

9 am – 11am: Introduction to Galaxy
11am – 5pm: RNA-seq (includes a break for lunch1 and a short break in
the afternoon)

Requirements

While biological and medical knowledge are helpful, students do not need to have prior programming or “command line” experience to participate in the course. For those unfamiliar with the Galaxy platform, we will start the the workshop with an optional introductory Galaxy tutorial, covering such topics as data import, filtering, combining, conversion and how to perform actions on genomic regions. After a short break we will spend the rest of our time applying this knowledge to RNA-seq. Those with prior Galaxy experience may choose to skip the first session and join us at 11am, though all are welcome to attend.

Time and location

9am-5pm, Wednesday November 28th, 2012

Countway Library
Longwood Campus
10 Shattuck Street
Boston, MA 02115

1 Lunch will not be provided, but there are a number of cafeterias and
restaurants in the immediate vicinity.

Large scale sequencing projects

Posted on 05, Nov, 2012 by in

The 1000G project just published it’s main manuscript, and MassGenomics provides an excellent summary:

The 1,000 Genomes project has provided a sort of “null expectation” for the number of rare, low-frequency, and common variants of different functional consequences found in randomly-chosen [healthy] individuals from various populations. […] It also tells you that if you sequence an individual’s whole genomes and don’t find about 3 million SNPs, something is probably wrong.

And Luke Jostin’s publication in Nature reports on a record number of genetic associations for Inflammatory Bowel Disease, along with the struggle to turn these associations into actionable predictions:

We could imagine genotyping healthy people and use our new IBD variants to find a “high risk” group that we can monitor more closely. How well would this work? Given the variants reported in the paper, the answer is “not very well”. Suppose we take people in the top 0.05% of IBD risk. Even in this high risk group only 1 in 10 people will get IBD. Even worse, 99% of real IBD patients WON’T be in this group, and so would be missed by the test!