Biology subjects

Denisko, D.

Publications and source records attributed to Denisko, D..

5 recordsLinked to original sources

bioRxiv2026

Beyond statistical significance: ranking transcription factor binding motifs by effect size

Chromatin immunoprecipitation-sequencing (ChIP-seq) has wide use in identifying transcription factor binding sites. DNA sequence motifs specific to a targeted transcription factor occur more frequently near ChIP-seq peak centres. The most common approach to quantifying relative motif enrichment ranks motifs by p-value. Because sample sizes can vary substantially across examined motifs, p-value magnitudes may reflect this heterogeneity rather than the biological effect of interest. As alternatives, we considered four ranking methods based on effect sizes: (a) a modified Cliffs delta, (b) the lower bound of a frequentist asymptotic confidence interval, (c) the lower bound of a frequentist finite-sample confidence interval, and (d) the lower bound of a Bayesian credible region. Through extensive simulations, the four alternatives better recovered the simulated central-enrichment ordering under heterogeneous sample sizes. Using published ChIP-seq data for GATA3, the effect size methods ranked the known targeted motif highest, even compared to highly similar motifs for other GATA family members, while p-value ranking did not. In a separate SRF application, all four alternative methods also consistently ranked the known motif highest. We recommend the asymptotic confidence interval lower bound for its simplicity, ease of implementation, and intuitive interpretation. The software is freely available (https://github.com/ScottMastro/motif-ranking).

bioinformatics↗

bioRxiv2025

Inverted Alu repeats in loop-out exon skipping across hominoid evolution

BackgroundChanges in RNA splicing over the course of evolution have profoundly diversified the functional landscape of the human genome. While DNA sequences proximal to intron-exon junctions are known to be critical for RNA splicing, the impact of distal intronic sequences remains underexplored. Emerging evidence suggests that inverted pairs of intronic Alu elements can promote exon skipping by forming RNA stem-loop structures. However, their prevalence and influence throughout evolution remain unknown. ResultsHere, we present a systematic analysis of inverted Alu pairs across the human genome to assess their impact on exon skipping through predicted RNA stem-loop formation and their relevance to hominoid evolution. We found that inverted Alu pairs, particularly pairs of AluY-AluSx1 and AluSz-AluSx, are enriched in the flanking regions of skippable exons genome-wide and are predicted to form stable stem-loop structures. Exons defined by weak 3' acceptor and strong 5' donor splice sites appear especially prone to this skipping mechanism. Through comparative genome analysis across nine primate species, we identified 67,126 hominoid-specific Alu insertions, primarily from AluY and AluS subfamilies, which form inverted pairs enriched across skippable exons in genes of ubiquitination-related pathways. Experimental validation of exon skipping among several hominoid-specific inverted Alu pairs further reinforced their potential evolutionary significance. ConclusionThis work extends our current knowledge of the roles of RNA secondary structure formed by inverted Alu pairs and details a newly emerging mechanism through which transposable elements have contributed to genomic innovation across hominoid evolution at the transcriptomic level.

genomics↗

bioRxiv2024

Chromosomal rearrangements and instability caused by the LINE-1 retrotransposon

LINE-1 (L1) retrotransposition is widespread in many cancers, especially those with a high burden of chromosomal rearrangements. However, whether and to what degree L1 activity directly impacts genome integrity is unclear. Here, we apply whole-genome sequencing to experimental models of L1 expression to comprehensively define the spectrum of genomic changes caused by L1. Combining the analyses of experimental models of L1 induction and of cancer genomes, we demonstrate that L1 retrotransposition can directly generate reciprocal translocations, genomic DNA inversions, and foldback rearrangements resulting from illegitimate recombination of double-strand DNA ends generated by L1-encoded ORF2p. We further show that L1-induced rearrangements can produce unstable chromosomes that fuel the acquisition of complex rearrangements, large segmental copy-number alterations, and genetic heterogeneity through breakage-fusion bridge cycles or DNA fragmentation. Together, these findings suggest L1 as a potent mutagenic force capable of driving genome evolution in cancers.

genomics↗

bioRxiv2022

Assessing and assuring interoperability of a genomics file format

BackgroundBioinformatics software tools operate largely through the use of specialized genomics file formats. Often these formats lack formal specification, and only rarely do the creators of these tools robustly test them for correct handling of input and output. This causes problems in interoperability between different tools that, at best, wastes time and frustrates users. At worst, interoperability issues could lead to undetected errors in scientific results. MethodsWe sought (1) to assess the interoperability of a wide range of bioinformatics software using a shared genomics file format and (2) to provide a simple, reproducible method for enhancing inter-operability. As a focus, we selected the popular Browser Extensible Data (BED) file format for genomic interval data. Based on the file formats original documentation, we created a formal specification. We developed a new verification system, Acidbio (https://github.com/hoffmangroup/acidbio), which tests for correct behavior in bioinformatics software packages. We crafted tests to unify correct behavior when tools encounter various edge cases--potentially unexpected inputs that exemplify the limits of the format. To analyze the performance of existing software, we tested the input validation of 80 Bioconda packages that parsed the BED format. We also used a fuzzing approach to automatically perform additional testing. ResultsOf 80 software packages examined, 75 achieved less than 70% correctness on our test suite. We categorized multiple root causes for the poor performance of different types of software. Fuzzing detected other errors that the manually designed test suite could not. We also created a badge system that developers can use to indicate more precisely which BED variants their software accepts and to advertise the softwares performance on the test suite. DiscussionAcidbio makes it easy to assess interoperability of software using the BED format, and therefore to identify areas for improvement in individual software packages. Applying our approach to other file formats would increase the reliability of bioinformatics software and data.

bioinformatics↗

bioRxiv2019

Motif elucidation in ChIP-seq datasets with a knockout control

Chromatin immunoprecipitation-sequencing (ChIP-seq) is widely used to find transcription factor binding sites, but suffers from various sources of noise. Knocking out the target factor mitigates noise by acting as a negative control. Paired wild-type and knockout experiments can generate improved motifs but require optimal differential analysis. We introduce peaKO--a computational method to automatically optimize motif analyses with knockout controls, which we compare to two other methods. PeaKO often improves elucidation of the target factor and highlights the benefits of knockout controls, which far outperform input controls. It is freely available at https://peako.hoffmanlab.org.

bioinformatics↗