Improved quality metrics for association and reproducibility in chromatin accessibility data using mutual information

Background Correlation metrics are widely utilized in genomics analysis and often implemented with little regard to assumptions of normality, homoscedasticity, and independence of values. This is especially true when comparing values between replicated sequencing experiments that probe chromatin acc...

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Vydáno v:	BMC bioinformatics Ročník 24; číslo 1; s. 1 - 22
Hlavní autoři:	Roth, Cullen, Venu, Vrinda, Job, Vanessa, Lubbers, Nicholas, Sanbonmatsu, Karissa Y., Steadman, Christina R., Starkenburg, Shawn R.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London BioMed Central 22.11.2023 BioMed Central Ltd Springer Nature B.V BMC
Témata:	Accessibility Algorithms ATAC-seq BASIC BIOLOGICAL SCIENCES Bioinformatics Biomedical and Life Sciences Chromatin Coefficients Computational Biology/Bioinformatics Computer Appl. in Life Sciences Computer simulation Computer-generated environments Correlation Correlation analysis Correlation and association Data mining Datasets DNA replication Epigenetic inheritance Epigenetics Experiments Gene expression Genetic research Genomes Life Sciences Machine learning MATHEMATICS AND COMPUTING Methods Microarrays Normality Normalized mutual information Outliers (statistics) Random forest Reproducibility Simulation Software Statistical analysis Statistics Structure Transposase United States Normalized mutual information Random forest ATAC-seq Correlation and association
ISSN:	1471-2105, 1471-2105
On-line přístup:	Získat plný text
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