FastQTLmapping: an ultra-fast and memory efficient package for mQTL-like analysis
FastQTLmapping effectively expedites comprehensive mQTL analyses by providing a robust and generic approach that accommodates large-scale genomic datasets with covariates. This solution has the potential to streamline mQTL-like studies and inform future method development for efficient computational genomics.
Authors
- Xinxuan Liu (ORCID: https://orcid.org/0000-0002-1653-1434)
- Xingjian Gao (ORCID: https://orcid.org/0000-0002-6142-8102)
- Han Jing (ORCID: https://orcid.org/0000-0003-4211-1975)
- Qianqian Peng (ORCID: https://orcid.org/0000-0002-2018-5706)
- Andrew E. Teschendorff (ORCID: https://orcid.org/0000-0001-7410-6527)
- Sibte Hadi (ORCID: https://orcid.org/0000-0002-2994-3083)
- Fan Liu (ORCID: https://orcid.org/0000-0001-9241-8161)
- Sijia Wang (ORCID: https://orcid.org/0000-0003-2573-5030)
- Jiarui Li (ORCID: https://orcid.org/0000-0003-0581-5850)
Institutions
- Chinese Academy of Sciences (CN)
- Fudan University (CN)
- Nanjing General Hospital of Nanjing Military Command (CN)
- Beijing Institute of Genomics (CN)
- Shanghai Institute of Nutrition and Health (CN)
- Naif Arab University for Security Sciences (SA)
- University of Chinese Academy of Sciences (CN)
- Taizhou University (CN)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-04-27
- DOI
- https://doi.org/10.1186/s12859-025-06130-3
- Primary Topic
- Genomics and Chromatin Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Naif Arab University for Security Sciences
- National Natural Science Foundation of China
- Jiangsu Provincial Department of Human Resources and Social Security
- National Key Research and Development Program of China