Improved functions for non-linear sequence comparison using SEEKR

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Abstract

SEquence Evaluation through k -mer Representation (SEEKR) is a method of sequence comparison that utilizes sequence substrings called k -mers to quantify non-linear similarity between nucleic acid species. We describe the development of new functions within SEEKR that enable end-users to estimate p-values that ascribe statistical significance to SEEKR-derived similarities as well as visualize different aspects of k -mer similarity. We apply the new functions to identify chromatin-enriched long noncoding RNAs (lncRNAs) that harbor XIST -like sequence fragments and show that several of these fragments are bound by XIST -associated proteins. We also highlight the best practice of using RNA-Seq data to evaluate support for lncRNA annotations prior to their in-depth study in cell types of interest.
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Abstract SEquence Evaluation through k-mer Representation (SEEKR) is a method of sequence comparison that utilizes sequence substrings called k-mers to quantify non-linear similarity between nucleic acid species. We describe the development of new functions within SEEKR that enable end-users to estimate p-values that ascribe statistical significance to SEEKR-derived similarities as well as visualize different aspects of k-mer similarity. We apply the new functions to identify chromatin-enriched long noncoding RNAs (lncRNAs) that harbor XIST-like sequence fragments and show that several of these fragments are bound by XIST-associated proteins. We also highlight the best practice of using RNA-Seq data to evaluate support for lncRNA annotations prior to their in-depth study in cell types of interest. Competing Interest Statement The authors have declared no competing interest.

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