Evidence map›Paper›PMID 38564640›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2024

OASIS: An interpretable, finite-sample valid alternative to Pearson's

Tavor Z Baharav, David Tse, Julia Salzman

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
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  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Tavor Z BaharavEric and Wendy Schmidt Center, Broad Institute, Cambridge, MA 02142.ORCID 0000-0001-8924-0243
David TseDepartment of Electrical Engineering, Stanford University, Stanford, CA 94305.
Julia SalzmanDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305.

Funding

Computational- and experimental- driven discovery of splicing regulation and circRNA functionR35GM139517 · NIGMS · STANFORD UNIVERSITY · PI Julia Salzman · 2021 to 2026
$2.9M
NIGMS NIH HHS R35 GM139517
6 · The paper itself

Abstract

Contingency tables, data represented as counts matrices, are ubiquitous across quantitative research and data-science applications. Existing statistical tests are insufficient however, as none are simultaneously computationally efficient and statistically valid for a finite number of observations. In this work, motivated by a recent application in reference-free genomic inference [K. Chaung

Indexed as

GenomeGenomicsChromosome Mappingcomputational genomicscontingency tablefinite-sample P-valuereference genome free inference

Identifiers

PMID38564640
PMCPMC11009617

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.