Evidence map›Paper›PMID 33230554›Full record

ArticleBioinformatics (Oxford, England)2021

RepeatFS: a file system providing reproducibility through provenance and automation.

Anthony Westbrook, Elizabeth Varki, W Kelley Thomas

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Anthony WestbrookDepartment of Computer Science.ORCID 0000-0001-5398-6916
Elizabeth VarkiDepartment of Computer Science.
W Kelley ThomasHubbard Center for Genome Studies.

Funding

Ultrastructural analysis of axonal Kv2-mediated endoplasmic reticulum/plasma membrane (ER/PM) junctionsP20GM103506 · NIGMS · DARTMOUTH COLLEGE · PI STEVEN FIERING · 2012 to 2026
$60.1M
NIGMS NIH HHS P20 GM103506
6 · The paper itself

Abstract

motivationReproducibility is of central importance to the scientific process. The difficulty of consistently replicating and verifying experimental results is magnified in the era of big data, in which bioinformatics analysis often involves complex multi-application pipelines operating on terabytes of data. These processes result in thousands of possible permutations of data preparation steps, software versions and command-line arguments. Existing reproducibility frameworks are cumbersome and involve redesigning computational methods. To address these issues, we developed RepeatFS, a file system that records, replicates and verifies informatics workflows with no alteration to the original methods. RepeatFS also provides several other features to help promote analytical transparency and reproducibility, including provenance visualization and task automation.

resultsWe used RepeatFS to successfully visualize and replicate a variety of bioinformatics tasks consisting of over a million operations with no alteration to the original methods. RepeatFS correctly identified all software inconsistencies that resulted in replication differences. AVAILABILITYAND IMPLEMENTATION: RepeatFS is implemented in Python 3. Its source code and documentation are available at https://github.com/ToniWestbrook/repeatfs. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Computational BiologySoftwareAutomationReproducibility of ResultsWorkflow

Identifiers

PMID33230554
PMCPMC8189677

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.