Biology subjects

Kübler, K.

Publications and source records attributed to Kübler, K..

2 recordsLinked to original sources

bioRxiv2026

commonPeak: Equivalence testing to identify common ChIP-seq peaks across conditions and protocols

BackgroundNew ChIP-seq protocols are increasingly adopted alongside established workflows. However, dedicated methods are lacking to quantify the agreement of peak location and intensity across datasets, including comparisons across protocols and biological conditions. ObjectivesWe present commonPeak, a statistical framework that identifies shared peaks across samples and tests whether their enrichment is similar across conditions, thereby supporting bench-marking of ChIP-seq protocols and cross-condition comparisons. ResultscommonPeak operates on BED peak sets and BAM files. As a use case, we applied it to an estrogen receptor alpha (ER) ChIP-seq dataset from tamoxifen-sensitive and -resistant breast cancer cell line MCF-7 cells and identified 225 shared peaks with significantly similar enrichment. These peaks were largely distinct from differentially bound sites and enriched for estrogen signaling. This illustrates how equivalence-based peak selection can help separate conserved ER-driven programs from condition-specific changes in ER-targeting endocrine drugs such as tamoxifen. Availability and implementationcommonPeak is freely available for non-commercial use via GitHub, with documentation and usage examples.

genomics↗

bioRxiv2019

Tumor mutational landscape is a record of the pre-malignant state

Chromatin structure has a major influence on the cell-specific density of somatic mutations along the cancer genome. Here, we present a pan-cancer study in which we searched for the putative cancer cell-of-origin of 2,550 whole genomes, representing 32 cancer types by matching their mutational landscape to the regional patterns of chromatin modifications ascertained in 104 normal tissue types. We found that, in almost all cancer types, the cell-of-origin can be predicted solely from their DNA sequences. Our analysis validated the hypothesis that high-grade serous ovarian cancer originates in the fallopian tube and identified distinct origins of breast cancer subtypes. We also demonstrated that the technique is equally capable of identifying the cell-of-origin for a series of 2,044 metastatic samples from 22 of the tumor types available as primaries. Moreover, cancer drivers, whether inherited or acquired, reside in active chromatin regions in the respective cell-of-origin. Taken together, our findings highlight that many somatic mutations accumulate while the chromatin structure of the cell-of-origin is maintained and that this historical record, captured in the DNA, can be used to identify the often elusive cancer cell-of-origin.

genomics↗