Title: | Outlier Detection for Multi-Network Data. |
Journal: | Bioinformatics |
Published: | 28 Jun 2022 |
Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35762974/ |
DOI: | https://doi.org/10.1093/bioinformatics/btac431 |
URL: | http://arxiv.org/pdf/2205.06398 |
Title: | Outlier Detection for Multi-Network Data. |
Journal: | Bioinformatics |
Published: | 28 Jun 2022 |
Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35762974/ |
DOI: | https://doi.org/10.1093/bioinformatics/btac431 |
URL: | http://arxiv.org/pdf/2205.06398 |
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RESULTS: ODIN was successful in identifying moderate to extreme outliers. Removing such outliers can significantly change inferences in downstream applications.
AVAILABILITY: ODIN has been implemented in both Python and R and these implementations along with other code are publicly available at github.com/pritamdey/ODIN-python and github.com/pritamdey/ODIN-r respectively.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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