Evidence map›Paper›PMID 20973742›Full record

ArticleJournal of computational biology : a journal of computational molecular cell biology2010

Alignment-free sequence comparison (II): theoretical power of comparison statistics.

Lin Wan, Gesine Reinert, Fengzhu Sun, Michael S Waterman

Abstract read
In one paragraph

Article in Journal of computational biology : a journal of computational molecular cell biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing 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

54 citing papers in PubMed.

  1. Trial
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  9. Sequence Comparison Without Alignment: The SpaM Approaches.Methods in molecular biology (Clifton, N.J.) · 2021
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  12. Review
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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

4 authors.

Lin WanMolecular and Computational Biology, University of Southern California , Los Angeles, California 90089-2910, USA.
Gesine Reinert
Fengzhu Sun
Michael S Waterman

Funding

Implications of haplotype structure in the human genomeP50HG002790 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TAVARE, SIMON · 2003 to 2013
$29.9M
Computational and Statistical Studies for Multiple Molecular NetworksR21AG032743 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI SUN, FENGZHU · 2008 to 2009
$367k
Biotechnology and Biological Sciences Research CouncilNHGRI NIH HHS P50 HG 002790NIA NIH HHS R21AG032743
6 · The paper itself

Abstract

Rapid methods for alignment-free sequence comparison make large-scale comparisons between sequences increasingly feasible. Here we study the power of the statistic D2, which counts the number of matching k-tuples between two sequences, as well as D2*, which uses centralized counts, and D2S, which is a self-standardized version, both from a theoretical viewpoint and numerically, providing an easy to use program. The power is assessed under two alternative hidden Markov models; the first one assumes that the two sequences share a common motif, whereas the second model is a pattern transfer model; the null model is that the two sequences are composed of independent and identically distributed letters and they are independent. Under the first alternative model, the means of the tuple counts in the individual sequences change, whereas under the second alternative model, the marginal means are the same as under the null model. Using the limit distributions of the count statistics under the null and the alternative models, we find that generally, asymptotically D2S has the largest power, followed by D2*, whereas the power of D2 can even be zero in some cases. In contrast, even for sequences of length 140,000 bp, in simulations D2* generally has the largest power. Under the first alternative model of a shared motif, the power of D2*approaches 100% when sufficiently many motifs are shared, and we recommend the use of D2* for such practical applications. Under the second alternative model of pattern transfer,the power for all three count statistics does not increase with sequence length when the sequence is sufficiently long, and hence none of the three statistics under consideration canbe recommended in such a situation. We illustrate the approach on 323 transcription factor binding motifs with length at most 10 from JASPAR CORE (October 12, 2009 version),verifying that D2* is generally more powerful than D2. The program to calculate the power of D2, D2* and D2S can be downloaded from http://meta.cmb.usc.edu/d2. Supplementary Material is available at www.liebertonline.com/cmb.

Indexed as

Base SequenceModels, StatisticalAlgorithmsComputational BiologyMathematicsSequence AlignmentSequence Analysis, DNASoftware

Identifiers

PMID20973742
PMCPMC3123933

What OpenQuestion holds

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Registered trials

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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.