Skip to content
DraconiticResearch
Search Sources API
190,851 studies31 sourcesUpdated 16 min ago
PreprintCC BY-NC-NDbioRxiv

inteRelate: flexible and thorough relating of genomic interval datasets through comparative overlap analysis

  1. 1Imperial College London

Abstract

Summary Testing spatial relationships between genome-mapped features is both a common source of hypothesis generation and an additional layer of supporting evidence for experimental findings. Many computational tools automate the statistical association procedures used to assess overlap between pairs of genomic features. However, none provides a dedicated workflow that directly compares multiple features by assessing their overlap with a separate, common feature, first testing for overall heterogeneity and then identifying which overlap rates differ. Such comparative overlap analysis could directly facilitate comparisons of features within the same class across disease states, cell types, experimental perturbations, and other biological contexts. Here, we describe inteRelate, a software package that uses genomic interval datasets to test spatial relationships between genome-mapped features through comparative overlap analysis. The package functions as an end-to-end pipeline that is highly tunable and thorough in its statistical association procedures. We use experimental data to demonstrate the automation, accuracy, and insight inteRelate provides. Availability and implementation inteRelate is available at https://github.com/loggy01/interelate and archived at https://zenodo.org/records/21891072. Example uses are available in the online supplement. Additionally, the example datasets and results are available at https://zenodo.org/records/22012767.

Related

  1. Comparative evaluation of metabolomic, microbial, and integrated features for distinguishing a rat model of heatstroke death from cervical-dislocation controls and estimating postmortem interval across organs
    Jianghuan Lu, Zhiao Duan, Siqi Chen +7
    Frontiers in microbiologyPeer-reviewedCC BYFull textMicrobiologyEurope PMC
  2. The relative psychometric function: A general analysis framework for relating psychological processes.
    Brian Maniscalco, Olenka Graham Castaneda, Brian Odegaard +4
    Psychological ReviewPeer-reviewedLicence not stated15 citedNeuroscienceOpenAlex
  3. Relating smartphone ‘App-journeys’ to mental health: A novel network analysis approach
    Georgia Turner, Maria Concepcion Valdez Gastelum, Ian Anderson +7
    PsyArXivPreprintCC BY 4.0Full textNeurosciencePsychiatry & mental healthOSF
  4. Synchronization properties in C. elegans: Relating behavioral circuits to structural and functional neuronal connectivity
    Gourab Kumar Sar, Andrew Patton, Emma Towlson +1
    PLOS Computational BiologyPeer-reviewedCC BY 4.0Full textNeurosciencePhysiologyPLOS
  5. Mapping the neural basis of the perception of “flow of time”: interval timing and mental time travel in the human brain
    Ryuta Ochi, Mitsuru Kawamura
    Frontiers in NeurologyPeer-reviewedCC BY 4.0Full textNeurosciencePMCCrossrefEurope PMC
BibTeX
@misc{mamanelogsdon2026interelate,
  title = {{inteRelate: flexible and thorough relating of genomic interval datasets through comparative overlap analysis}},
  author = {A. Mamane-Logsdon and M. D. Kalemera and G. N. Maertens},
  howpublished = {bioRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.14.751391},
  url = {https://www.biorxiv.org/content/10.64898/2026.09.14.751391v1},
  note = {CC BY-NC-ND},
}
RIS
TY  - UNPB
TI  - inteRelate: flexible and thorough relating of genomic interval datasets through comparative overlap analysis
AU  - A. Mamane-Logsdon
AU  - M. D. Kalemera
AU  - G. N. Maertens
PY  - 2026
DA  - 2026/09/14
PB  - bioRxiv
DO  - 10.64898/2026.09.14.751391
UR  - https://www.biorxiv.org/content/10.64898/2026.09.14.751391v1
AB  - Summary Testing spatial relationships between genome-mapped features is both a common source of hypothesis generation and an additional layer of supporting evidence for experimental findings. Many computational tools automate the statistical association procedures used to assess overlap between pairs of genomic features. However, none provides a dedicated workflow that directly compares multiple features by assessing their overlap with a separate, common feature, first testing for overall heterogeneity and then identifying which overlap rates differ. Such comparative overlap analysis could directly facilitate comparisons of features within the same class across disease states, cell types, experimental perturbations, and other biological contexts. Here, we describe inteRelate, a software package that uses genomic interval datasets to test spatial relationships between genome-mapped features through comparative overlap analysis. The package functions as an end-to-end pipeline that is highly tunable and thorough in its statistical association procedures. We use experimental data to demonstrate the automation, accuracy, and insight inteRelate provides. Availability and implementation inteRelate is available at https://github.com/loggy01/interelate and archived at https://zenodo.org/records/21891072. Example uses are available in the online supplement. Additionally, the example datasets and results are available at https://zenodo.org/records/22012767.
ER  -