Evidence map›Paper›PMID 28968781›Full record

ArticleBriefings in bioinformatics2019

Federation in genomics pipelines: techniques and challenges.

Somali Chaterji, Jinkyu Koo, Ninghui Li, Folker Meyer, Ananth Grama, Saurabh Bagchi

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Review
  5. Review
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  7. Article
  8. Sustainable biobanks: a case study for a green global bioethics.Global bioethics = Problemi di bioetica · 2022
    Article
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  10. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Somali ChaterjiComputer Science, Purdue University, Indiana, USA.
Jinkyu KooElectrical and Computer Engineering, Purdue University, Indiana, USA.
Ninghui LiComputer Science, Purdue University, Indiana, USA.
Folker MeyerArgonne National Laboratory, Mathematics and Computer Science Division, Illinois, USA.
Ananth GramaComputer Science, Purdue University, Indiana, USA.
Saurabh BagchiElectrical and Computer Engineering, Purdue University, Indiana, USA.

Funding

Continued Development and Maintenance of the MG-RAST Metagenomics PipelineR01AI123037 · NIAID · PURDUE UNIVERSITY · PI GRAMA, ANANTH, MEYER, FOLKER · 2016 to 2020
$3.7M
Emerging virus-host cell protein interaction networksR01AI114814 · NIAID · PURDUE UNIVERSITY · PI DAVEY, ROBERT A, LACOUNT, DOUGLAS J. · 2015 to 2019
$3.5M
NIAID NIH HHS R01 AI114814NIAID NIH HHS R01 AI123037
6 · The paper itself

Abstract

Federation is a popular concept in building distributed cyberinfrastructures, whereby computational resources are provided by multiple organizations through a unified portal, decreasing the complexity of moving data back and forth among multiple organizations. Federation has been used in bioinformatics only to a limited extent, namely, federation of datastores, e.g. SBGrid Consortium for structural biology and Gene Expression Omnibus (GEO) for functional genomics. Here, we posit that it is important to federate both computational resources (CPU, GPU, FPGA, etc.) and datastores to support popular bioinformatics portals, with fast-increasing data volumes and increasing processing requirements. A prime example, and one that we discuss here, is in genomics and metagenomics. It is critical that the processing of the data be done without having to transport the data across large network distances. We exemplify our design and development through our experience with metagenomics-RAST (MG-RAST), the most popular metagenomics analysis pipeline. Currently, it is hosted completely at Argonne National Laboratory. However, through a recently started collaborative National Institutes of Health project, we are taking steps toward federating this infrastructure. Being a widely used resource, we have to move toward federation without disrupting 50 K annual users. In this article, we describe the computational tools that will be useful for federating a bioinformatics infrastructure and the open research challenges that we see in federating such infrastructures. It is hoped that our manuscript can serve to spur greater federation of bioinformatics infrastructures by showing the steps involved, and thus, allow them to scale to support larger user bases.

Indexed as

Big DataComputational BiologyConfidentialityDatabases, GeneticGenetic PrivacyGenomicsHumansInformation DisseminationMetagenomicsSoftwareUnited States

Identifiers

PMID28968781
PMCPMC6357554

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.