Evidence map›Paper›PMID 38180848›Full record

ArticleBioinformatics (Oxford, England)2024

SciDataFlow: a tool for improving the flow of data through science.

Vince Buffalo

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Vince BuffaloDepartment of Integrative Biology, University of California, CA 94720, United States.ORCID 0000-0003-4510-1609

Funding

Enabling Precision Genomics Using Adaptive VariationR01GM138634 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI NIELSEN, RASMUS · 2020 to 2023
$1.7M
NIGMS NIH HHS R01 GM138634
6 · The paper itself

Abstract

motivationManaging data and code in open scientific research is complicated by two key problems: large datasets often cannot be stored alongside code in repository platforms like GitHub, and iterative analysis can lead to unnoticed changes to data, increasing the risk that analyses are based on older versions of data.

resultsSciDataFlow is a fast, concurrent command-line tool paired with a simple Data Manifest specification that streamlines tracking data changes, uploading data to remote repositories, and pulling in all data necessary to reproduce a computational analysis. AVAILABILITY AND IMPLEMENTATION: SciDataFlow is available at https://github.com/vsbuffalo/scidataflow.

Indexed as

Data ManagementSoftware

Identifiers

PMID38180848
PMCPMC10786673

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.