Evidence map›Paper›PMID 30101309›Full record

ArticleBioinformatics (Oxford, England)2019

Container-based bioinformatics with Pachyderm.

Jon Ander Novella, Payam Emami Khoonsari, Stephanie Herman, Daniel Whitenack, Marco Capuccini, Joachim Burman, Kim Kultima, Ola Spjuth

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–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

16 citing papers in PubMed.

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  6. Scalable in-memory processing of omics workflows.Computational and structural biotechnology journal · 2022
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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

8 authors.

Jon Ander NovellaDepartment of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Payam Emami KhoonsariDepartment of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden.
Stephanie HermanDepartment of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Daniel WhitenackPachyderm, Inc., San Francisco, CA, USA.
Marco CapucciniDepartment of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Joachim BurmanDepartment of Neuroscience, Uppsala University, Uppsala, Sweden.
Kim KultimaDepartment of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden.
Ola SpjuthDepartment of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationComputational biologists face many challenges related to data size, and they need to manage complicated analyses often including multiple stages and multiple tools, all of which must be deployed to modern infrastructures. To address these challenges and maintain reproducibility of results, researchers need (i) a reliable way to run processing stages in any computational environment, (ii) a well-defined way to orchestrate those processing stages and (iii) a data management layer that tracks data as it moves through the processing pipeline.

resultsPachyderm is an open-source workflow system and data management framework that fulfils these needs by creating a data pipelining and data versioning layer on top of projects from the container ecosystem, having Kubernetes as the backbone for container orchestration. We adapted Pachyderm and demonstrated its attractive properties in bioinformatics. A Helm Chart was created so that researchers can use Pachyderm in multiple scenarios. The Pachyderm File System was extended to support block storage. A wrapper for initiating Pachyderm on cloud-agnostic virtual infrastructures was created. The benefits of Pachyderm are illustrated via a large metabolomics workflow, demonstrating that Pachyderm enables efficient and sustainable data science workflows while maintaining reproducibility and scalability. AVAILABILITY AND IMPLEMENTATION: Pachyderm is available from https://github.com/pachyderm/pachyderm. The Pachyderm Helm Chart is available from https://github.com/kubernetes/charts/tree/master/stable/pachyderm. Pachyderm is available out-of-the-box from the PhenoMeNal VRE (https://github.com/phnmnl/KubeNow-plugin) and general Kubernetes environments instantiated via KubeNow. The code of the workflow used for the analysis is available on GitHub (https://github.com/pharmbio/LC-MS-Pachyderm). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Computational BiologySoftwareEcosystemReproducibility of ResultsWorkflow

Identifiers

PMID30101309
PMCPMC6394392

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.