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Overlapping Probabilities of Top Ranking Gene Lists, Hypergeometric Distribution, and Stringency of Gene Selection Criterion

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Wen Fury, Franak Batliwalla, Peter K. Gregersen, Wentian Li

Quantitative Methods · Submitted 14 Jun 2006

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim It is concluded that overlapping probability is indeed a function of the gene list length, and its statistical significance should be quoted in the context of gene selection criterion.

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arXiv IDq-bio/0606017 (version 1)
Pith IDEKKCMU76, Pith's permanent record of this paper and its review
CitationFranak Batliwalla, Peter K. Gregersen, Wen Fury, Wentian Li. "Overlapping Probabilities of Top Ranking Gene Lists, Hypergeometric Distribution, and Stringency of Gene Selection Criterion." arXiv:q-bio/0606017 (2006). https://pith.science/paper/EKKCMU76
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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 4,243 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.21 · human participants 0.06 · controlled comparison 0.05 · randomized assignment 0.01 · states quantitative result 0.08 · compares with prior results 0.12 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

When the same set of genes appear in two top ranking gene lists in two different studies, it is often of interest to estimate the probability for this being a chance event. This overlapping probability is well known to follow the hypergeometric distribution. Usually, the lengths of top-ranking gene lists are assumed to be fixed, by using a pre-set criterion on, e.g., $p$-value for the t-test. We investigate how overlapping probability changes with the gene selection criterion, or simply, with the length of the top-ranking gene lists. It is concluded that overlapping probability is indeed a function of the gene list length, and its statistical significance should be quoted in the context of gene selection criterion.

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What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 When the same set of genes appear in two top ranking gene lists in two different studies, it is often of interest to estimate the probability for this being a chance event. background 1.00 0.05 0.02 asserted 0.60
s1 This overlapping probability is well known to follow the hypergeometric distribution. background 1.00 0.04 0.02 asserted 1.00
s2 Usually, the lengths of top-ranking gene lists are assumed to be fixed, by using a pre-set criterion on, e.g., $p$-value for the t-test. background 0.99 0.04 0.02 asserted 0.97
s3 We investigate how overlapping probability changes with the gene selection criterion, or simply, with the length of the top-ranking gene lists. contribution 1.00 0.82 0.04 unclear 0.73
s4 It is concluded that overlapping probability is indeed a function of the gene list length, and its statistical significance should be quoted in the context of gene selection criterion. interpretation 0.64 0.90 0.97 asserted 1.00

What kind of paper the classifier reports this is: theoretical result 0.73 · evidence from proof or derivation 0.51.

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

When the same set of genes appear in two top ranking gene lists in two different studies, it is often of interest to estimate the probability for this being a chance event. This overlapping probability is well known to follow the hypergeometric distribution. Usually, the lengths of top-ranking gene lists are assumed to be fixed, by using a pre-set criterion on, e.g., $p$-value for the t-test. We investigate how overlapping probability changes with the gene selection criterion, or simply, with the length of the top-ranking gene lists. It is concluded that overlapping probability is indeed a function of the gene list length, and its statistical significance should be quoted in the context of gene selection criterion.

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