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

Tavares, Ana Helena; Raymaekers, Jakob; Rousseeuw, Peter J.; Brito, Paula; Afreixo, Vera

doi:10.1007/S11634-019-00362-X

Title

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

Author

Tavares, Ana Helena

Raymaekers, Jakob

Rousseeuw, Peter J.

Brito, Paula

Afreixo, Vera

Abstract

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

Source (journal)

Advances in data analysis and classification. - Berlin, 2007, currens

Publication

Berlin : Springer , 2020

ISSN

1862-5347 [print]

1862-5355 [online]

DOI

10.1007/S11634-019-00362-X

Volume/pages