7
$\begingroup$

I'm looking for cloud computing services that can be used for doing bioinformatics. An example I found is InsideDNA and there is Amazon of course. A little description of these would be appreciated.

$\endgroup$

closed as too broad by terdon Nov 2 '17 at 0:41

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

  • 3
    $\begingroup$ Can you mention Google compute as well and further specify what exactly you're interested in knowing? As is I expect this will end up getting closed otherwise. $\endgroup$ – Devon Ryan Jun 12 '17 at 12:13
  • 2
    $\begingroup$ What do you want to use the computer services for? Do you have access to a university, research institute, or other academic facility? Is there a particular reason why your desktop or laptop is not appropriate? $\endgroup$ – gringer Jun 12 '17 at 12:38
  • 2
    $\begingroup$ I do not think that this is a good question since there is no one good answer (or at least the answer should a list, not a one provider), so I will just link the providers I know : DNAnexus (private) and Vital-it (academic) $\endgroup$ – Kamil S Jaron Jun 12 '17 at 20:28
  • 1
    $\begingroup$ This post is too broad. $\endgroup$ – zx8754 Jun 12 '17 at 20:49
  • 1
    $\begingroup$ I put this on hold since asking for lists like this is really not a very good fit for the Q&A format and better suited to something like a forum where a discussion can be had. See this old blog post for an explanation of the general rationale behind considering this type of question off topic. $\endgroup$ – terdon Nov 2 '17 at 0:43
4
$\begingroup$

It really depends on what you are trying to do, but here are a few services that I know of.

  • GATK on Google Genomics Cloud: Google and the Broad offer a cloud instance tailored to GATK pipelines.
  • Genomics on Amazon Web Services: I don't think there is anything that makes this unique, but Amazon offers some resources to help get started with genomics/life sciences-centered cloud solutions.
  • Illumina Bioinformatics: Illumina is working on a whole suite of bioinformatics software for the cloud.
  • Cancer Genomics Cloud: This is specific to cancer genomics, but I believe Seven Bridges allows you to push all sorts of data into the tool and analyze it.
$\endgroup$
8
$\begingroup$

I have trialed the free version of InsideDNA, and these were my notes:

  • Cost: \$225/month for a team of 5 with 50TB storage or \$45/month with 10TB storage for individuals (assuming 6 month package: https://insidedna.me/pricing).
  • Software installed: Around 600 bioinformatic tools available and standard command line tools; some popular tools missing (like CD-HIT), but should be possible to install on request.
  • Jobs: Maximum of 32 CPUs and 208 RAM per job submission. Test jobs generally worked, although a larger test job failed.
  • Other points: Command line was sometimes slow, wget queries were slow, and scp was blocked. However, these may be resolvable issues.

Overall, I felt InsideDNA could be useful for groups without their own computational infrastructure and could be used for easily sharing resources between groups. The packages on offer seem not expensive, but I had a few issues, and I don't know how good their sys admin support would be.

I have not used the Amazon service, so can't comment beyond the details on their website. Also there are a few alternative companies, such as Genestack and DNAnexus, but I haven't directly tested them either.

$\endgroup$
5
$\begingroup$

I'm not sure what kinds of bioinformatics tasks you would like to perform, therefore it is difficult to give a good recommendation.

If you're specifically working on statistical genetics, I can recommend Hail [1]. Hail is an open-source tool for analyzing genetics data at the tens of terabyte scale. Most of Hail's users do their science in Jupyter notebooks that are backed by Google Cloud Platform Dataproc clusters. Hail permits you to perform a variety of statistical genetics tasks including:

  • filtering and aggregation for quality control
  • subsetting, linear regression, linear mixed model regression, and linear burden testing
  • utilities for computing various measures of relatedness
  • principal components analysis
  • variant splitting
  • import/export from a variety of formats including PLINK, VCF, and BGEN, and
  • a python API which enables the use of libraries like matplotlib for plotting analysis results

To learn specifically about using Hail with the Google Cloud Platform and Jupyter notebooks, I strongly recommend Liam's Hail forum post about his cloud-tools repository.

Here's an example, from the Hail tutorial, of using Hail to perform some quality control and display a scatter plot of the first two principal components of the individuals:

from hail import *
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches

hc = HailContext()

table = hc.import_table('data/1kg_annotations.txt', impute=True).key_by('Sample')
common_vds = (hc.read('data/1kg.vds')
              .annotate_samples_table(table, root='sa')
              .sample_qc()
              .filter_samples_expr('sa.qc.dpMean >= 4 && sa.qc.callRate >= 0.97')
              .filter_genotypes('''let ab = g.ad[1] / g.ad.sum() in
                         ((g.isHomRef && ab <= 0.1) ||
                          (g.isHet && ab >= 0.25 && ab <= 0.75) ||
                          (g.isHomVar && ab >= 0.9))''')
              .variant_qc()
              .filter_variants_expr('va.qc.AF > 0.01')
              .ld_prune(memory_per_core=512, num_cores=4))

pca = common_vds.pca('sa.pca', k=5, eigenvalues='global.eigen')
pca_table = pca.samples_table().to_pandas()

colors = {'AFR': 'green', 'AMR': 'red', 'EAS': 'black', 'EUR': 'blue', 'SAS': 'cyan'}
plt.scatter(pca_table["sa.pca.PC1"], pca_table["sa.pca.PC2"],
            c = pca_table["sa.SuperPopulation"].map(colors),
            alpha = .5)
plt.xlim(-0.6, 0.6)
plt.xlabel("PC1")
plt.ylabel("PC2")
legend_entries = [mpatches.Patch(color=c, label=pheno) for pheno, c in colors.items()]
plt.legend(handles=legend_entries, loc=2)
plt.show()

[1] Disclaimer: I work on Hail

$\endgroup$
4
$\begingroup$

Depending on your applications and uses, you might be interested in checking out CyVerse. It is an NSF funded initiative that provides you with data storage, high performance computing resources, and easy access to commonly used tools. As far as I know, it is free to use once you have an account. I also usually encounter it being used with plant and microbial genomics, so not sure how it will work with something like human genomics projects. But might be worth checking out at least. :)

More information: http://www.cyverse.org/about

$\endgroup$
1
$\begingroup$

Google Genomics

Google has an API called Google Genomics.

SNPedia

"SNPedia is a wiki investigating human genetics." snpedia.com

Promethease

"Promethease is a literature retrieval system that builds a personal DNA report" promethease.com

DNA Land

"Compare DNA with reference data from different populations" dna.land

The CyDAS Project

And, there's the CyDAS project which has an API that can analyze ISCN formulae. Per their web site: their API "lets you analyze a Karyotype for virtually all information which can be extracted from karyotypes and the rearrangements therein: gains and losses of chromosomal material, break points, junctions..." It's a free service, but I don't know how up to date it is.

$\endgroup$
1
$\begingroup$

DNAnexus -- http://dnanexus.com

BaseSpace -- http://basespace.illumina.com

Seven Bridges Genomics -- http://www.sbgenomics.com

Curoverse http://curoverse.com

InsideDNA http://insidedna.me/

$\endgroup$
0
$\begingroup$

There are tonnes of them. On top of the excellent ones everybody mentioned

  1. iRods

  2. Arvados

  3. Galaxy

$\endgroup$
  • $\begingroup$ Neither Galaxy nor iRods are cloud computing services. I suspect that Arvados isn't either, but I've never used it. $\endgroup$ – Devon Ryan Aug 7 '17 at 9:56

Not the answer you're looking for? Browse other questions tagged or ask your own question.