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Subtree power analysis finds optimal species for comparative genomics

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Jon D. McAuliffe, Michael I. Jordan, Lior Pachter

Genomics · Submitted 6 Dec 2004

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

The authors' main claim In a study of vertebrate species, we show that the optimal species subset is not in general the most evolutionarily diverged subset.

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arXiv IDq-bio/0412012 (version 1)
Pith IDJMOT36N5, Pith's permanent record of this paper and its review
CitationJon D. McAuliffe, Lior Pachter, Michael I. Jordan. "Subtree power analysis finds optimal species for comparative genomics." arXiv:q-bio/0412012 (2004). https://pith.science/paper/JMOT36N5
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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 4,778 input tokens.

What the abstract itself states, as probabilities: claims first 0.07 · states limitation 0.28 · human participants 0.02 · controlled comparison 0.08 · randomized assignment 0.01 · states quantitative result 0.07 · compares with prior results 0.43 · mentions code or data availability 0.03.

The abstract, sentence by sentence

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

Sequence comparison across multiple organisms aids in the detection of regions under selection. However, resource limitations require a prioritization of genomes to be sequenced. This prioritization should be grounded in two considerations: the lineal scope encompassing the biological phenomena of interest, and the optimal species within that scope for detecting functional elements. We introduce a statistical framework for optimal species subset selection, based on maximizing power to detect conserved sites. In a study of vertebrate species, we show that the optimal species subset is not in general the most evolutionarily diverged subset. Our results suggest that marsupials are prime sequencing candidates.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 Sequence comparison across multiple organisms aids in the detection of regions under selection. background 1.00 0.06 0.02 asserted 0.98
s1 However, resource limitations require a prioritization of genomes to be sequenced. background 0.93 0.05 0.02 asserted 1.00
s2 This prioritization should be grounded in two considerations: the lineal scope encompassing the biological phenomena of interest, and the optimal species within that scope for detecting functional elements. background 0.87 0.08 0.08 asserted 0.95
s3 We introduce a statistical framework for optimal species subset selection, based on maximizing power to detect conserved sites. contribution 0.73 0.90 0.11 asserted 1.00
s4 In a study of vertebrate species, we show that the optimal species subset is not in general the most evolutionarily diverged subset. result 1.00 0.95 0.48 asserted 1.00
s5 Our results suggest that marsupials are prime sequencing candidates. interpretation 0.81 0.84 0.41 hedged possibility 0.99

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from simulation or computation 0.69.

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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

Sequence comparison across multiple organisms aids in the detection of regions under selection. However, resource limitations require a prioritization of genomes to be sequenced. This prioritization should be grounded in two considerations: the lineal scope encompassing the biological phenomena of interest, and the optimal species within that scope for detecting functional elements. We introduce a statistical framework for optimal species subset selection, based on maximizing power to detect conserved sites. In a study of vertebrate species, we show that the optimal species subset is not in general the most evolutionarily diverged subset. Our results suggest that marsupials are prime sequencing candidates.

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