XeroGraph: enhancing data integrity in the presence of missing values with statistical and predictive analysis
XeroGraph is compatible with all operating systems and requires Python version 3.9 or higher. It can be freely downloaded from PyPI (https://pypi.org/project/XeroGraph). The source code is accessible on GitHub (https://github.com/kazilab/XeroGraph), and comprehensive documentation is available at Read the Docs (https://xerograph.readthedocs.io). This software is distributed under the Apache License 2.0.
Authors
- Julhash Uddin Kazi (ORCID: https://orcid.org/0000-0002-0719-5336)
- Lars Rönnstrand (ORCID: https://orcid.org/0000-0003-1275-5809)
- Emma U. Hammarlund (ORCID: https://orcid.org/0000-0001-7625-4793)
- Kenneth J. Pienta (ORCID: https://orcid.org/0000-0002-4138-2186)
- Laila Mousafi Alasal
Institutions
- Johns Hopkins University (US)
- Lund University (SE)
- Skåne University Hospital (SE)
Publication Details
- Journal
- Bioinformatics Advances
- Published
- 2024-12-26
- DOI
- https://doi.org/10.1093/bioadv/vbaf035
- Citations
- 5
- Primary Topic
- Data Quality and Management
- Type
- article
- Field-Weighted Citation Impact
- 2.45
Funders
- Cancerfonden
- Crafoordska Stiftelsen
- Lunds Universitet
- Vetenskapsrådet
- Barncancerfonden