Clustering genomic words in human DNA using peaks and trends of distributions

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Tavares, AH (Author) Other; Raymaekers, J (Author) Other; Rousseeuw, PJ (Author) Other; brito, p (Author) FEP; Afreixo, V (Author) Other

Journal

Title: Advances in Data Analysis and Classification

Vol. 14 No. 1

Pages: 57-76

ISSN: 1862-5347

Publisher: Springer Nature

Indexing

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Other information

Authenticus ID: P-00Q-J2E

DOI: 10.1007/s11634-019-00362-x

Abstract (EN): In this work we seek clusters of genomic words in human DNA by studying their inter-word lag distributions. Due to the particularly spiked nature of these histograms, a clustering procedure is proposed that first decomposes each distribution into a baseline and a peak distribution. An outlier-robust fitting method is used to estimate the baseline distribution (the 'trend'), and a sparse vector of detrended data captures the peak structure. A simulation study demonstrates the effectiveness of the clustering procedure in grouping distributions with similar peak behavior and/or baseline features. The procedure is applied to investigate similarities between the distribution patterns of genomic words of lengths 3 and 5 in the human genome. These experiments demonstrate the potential of the new method for identifying words with similar distance patterns.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 20