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Cited by 73Genomics and Chromatin DynamicsGenomics and Phylogenetic StudiesAlgorithms and Data Compression

Position Weight Matrix, Gibbs Sampler, and the Associated Significance Tests in Motif Characterization and Prediction

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Xia, Xuhua·2012·Scientifica
DOI 10.6064/2012/917540PMC PMC3820676
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Abstract

Position weight matrix (PWM) is not only one of the most widely used bioinformatic methods, but also a key component in more advanced computational algorithms (e.g., Gibbs sampler) for characterizing and discovering motifs in nucleotide or amino acid sequences. However, few generally applicable statistical tests are available for evaluating the significance of site patterns, PWM, and PWM scores (PWMS) of putative motifs. Statistical significance tests of the PWM output, that is, site-specific frequencies, PWM itself, and PWMS, are in disparate sources and have never been collected in a single paper, with the consequence that many implementations of PWM do not include any significance test. Here I review PWM-based methods used in motif characterization and prediction (including a detailed illustration of the Gibbs sampler for de novo motif discovery), present statistical and probabilistic rationales behind statistical significance tests relevant to PWM, and illustrate their application with real data. The multiple comparison problem associated with the test of site-specific frequencies is best handled by false discovery rate methods. The test of PWM, due to the use of pseudocounts, is best done by resampling methods. The test of individual PWMS for each sequence segment should be based on the extreme value distribution.

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  • The position weight matrix of site-specific nucleotide frequencies flanking the start codon AUG for all protein-coding genes from human Chr01 shows a pattern consistent with the GCCRCCAUGG consensus.

    “The associated position weight matrix [23,24,47,48], using intron nucleotide frequencies (0.26398, 0.21777, 0.22622 and 0.29203 for A, C, G, and T, respectively) as background frequencies, shows a site-specific pattern consistent with the GCCRCCAUGG consensus.”

    From Detailed Dissection and Critical Evaluation of the Pfizer/BioNTech and Moderna mRNA Vaccines (2021) · cites this paper as [23]

    The Introduction (page unavailable) describes position weight matrices as tools for characterizing nucleotide motifs, including translation initiation sites. Section 2.1 discusses choosing background nucleotide frequencies for a PWM. The paper does not report a PWM for human chromosome 1 start-codon flanks, the stated intron frequencies, or a pattern matching GCCRCCAUGG. (LLM, conf=0.84)

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Authors
Xia, X.
Affiliations
University of Ottawa (CA)
Corresponding author
Xia, Xuhua
ORCID
Xia, Xuhua
Venue
Scientifica
Publisher
Wiley
Published
2012
Volume
2012
Pages
1-15
ISSN
2090-908X (ISSN-L)
DOI
10.6064/2012/917540
PMC
PMC3820676
OpenAlex
W2143701918
Cited by
73
References
3
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FWCI
0.53
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientifica (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Natural Sciences and Engineering Research Council of Canada
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
Keywords
position weight matrices, Gibbs sampling, motif discovery, motif prediction, statistical significance tests, false discovery rate, multiple comparisons, resampling, extreme value distribution, nucleotide sequence, amino acid sequence

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