bims-fragic 2025-10-26 papers

Issue of 2025–10–26
two papers selected by
Laura Mannarino, Humanitas Research

Genome Biol. 2025 Oct 24. 26(1): 368

ParaMask: a new method to identify multicopy genomic regions, corrects major biases in whole-genome sequencing data.

Bastiaan Tjeng, Male Arimond, Helene Bråten Grindeland, Andrea Dalla Libera, Andrea Fulgione.

Multicopy genomic regions are repeated sequences that can bias genomic analyses. Here, we present a method, ParaMask, to identify and filter multicopy regions in population-level genomic data of any species. The broad applicability of this method stems from a flexible Expectation-Maximization framework to detect excess heterozygosity while simultaneously fitting inbreeding levels. By combining this signature with read-ratio deviations, excess sequencing depth, and a clustering technique, our method attains high recall. We show that multicopy regions create biases that confound evolutionary genomic analyses and that by identifying these regions with our method and filtering them, we can correct these biases.

Keywords: Duplications; Genomics; Multicopy regions; Paralogs; Repetitive sequences; Transposable elements

DOI: https://doi.org/10.1186/s13059-025-03836-8

Brief Bioinform. 2025 Aug 31. pii: bbaf551. [Epub ahead of print]26(5):

Read-level DNA methylation deconvolution enhances circulating tumor DNA detection.

Ting Qi, Lakshmi Narayanan Lakshmanan, Yuwei Yang, Ying Zhou, Min Pan, Anders Jacobsen Skanderup, Qinyu Ge.

DNA methylation is a key epigenetic modification underlying cellular identity. Conventional methods based on CpG site-level data often lack sensitivity in detecting low-frequency methylation signals. Here, we present Alpha, a novel method combining unbiased segmentation with robust read-level identification of low frequency cell-type-specific methylation signals. Methylation markers identified by Alpha exhibited significant enrichment in regulatory genomic elements such as enhancers, active promoters, and transcription factor binding sites. In simulated cell-type admixtures, Alpha-derived markers demonstrated improved deconvolution performance, exhibiting lower error metrics compared to beta-value based methods (DSS), even with limited marker numbers (N < 50). We combined Alpha with a non-negative least squares approach (Alpha-NNLS) to enable sensitive detection of circulating tumor DNA (ctDNA) in simulated cell-free DNA from breast and colon cancers, outperforming existing read-level methylation-based tumor fraction estimation methods (CelFEER and UXM). We applied Alpha-NNLS to targeted bisulfite sequencing data from early-stage colon cancer plasma samples and demonstrated strong concordance with existing approaches (R2 = 0.98), supporting its potential for sensitive detection of ctDNA.

Keywords: DNA methylation; cell-free DNA; circulating tumor DNA; deconvolution

DOI: https://doi.org/10.1093/bib/bbaf551