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Clustering genomic words in human DNA using peaks and trends of distributions
Tavares, Ana Helena; Raymaekers, Jakob; Rousseeuw, Peter J.; Brito, Paula; Afreixo, VeraIn 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...
Comparing reverse complementary genomic words based on their distance distribut...
Tavares, Ana Helena; Raymaekers, Jakob; Rousseeuw, Peter J.; Silva, Raquel M.; Bastos, Carlos A. C.; Pinho, Armando; Brito, Paula; Afreixo, VeraIn this work, we study reverse complementary genomic word pairs in the human DNA, by comparing both the distance distribution and the frequency of a word to those of its reverse complement. Several measures of dissimilarity between distance distributions are considered, and it is found that the peak dissimilarity works best in this setting. We report the existence of reverse complementary word pairs with very d...
Robust identification of target genes and outliers in triple-negative breast ca...
Segaert, Pieter; Lopes, Marta B.; Casimiro, Sandra; Vinga, Susana; Rousseeuw, Peter J.Correct classification of breast cancer subtypes is of high importance as it directly affects the therapeutic options. We focus on triple-negative breast cancer which has the worst prognosis among breast cancer types. Using cutting edge methods from the field of robust statistics, we analyze Breast Invasive Carcinoma transcriptomic data publicly available from The Cancer Genome Atlas data portal. Our analysis i...