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Anybody used Google Genomics
I'm thinking these are solved problems and I need to talk management off the ledge.
I'm thinking these are solved problems and I need to talk management off the ledge.
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The Nature interview with David Altshuler about the Global Alliance for Genomics and Health explains a bit about the motivation:
What came out of this week’s meeting?
It was a big tent that brought together stakeholders to identify the most pressing problems the alliance would solve. For example, there is a set of file formats currently used that came out of the 1,000 Genomes Project because we needed it. We think the current generation requires not file formats but machine-readable application programmer interfaces (APIs), and this group is developing — together with academics and for-profit companies — an open-source public API for genome sequencing reads and for genetic variants. That’s a very concrete set of things that we think the field needs.
Is this where Google fits in?
It’s important to realize that the Alliance is 151 members, of which Google is one. We think it’s important to have all the best experts at the table.Comment
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Programmatic access to data in the ENA / GenBank is essential. Will you archive or just wrap that data?
Will you build bespoke pipelines for typical analysis? If so, how will you reach community consensus on the best tool-suites to use?
How about an 'app store' for bioinformatics analysis? I think that 'open performance evaluation' would be key.
I'm thinking of starting a google-genomics-discuss forum would that be better than ad-hock discussion here?
Cheers,Comment
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I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...06-18-2026, 07:11 AM -
Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
...06-02-2026, 10:05 AM
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