Ionita-Laza-lab/GenoNet: A Semi-Supervised Approach for Predicting Cell-Type Specific Functional Consequences of Non-Coding Variation
Functions for predicting functional consequences of non-coding variation, allowing for the incorperation of unlabeled data. Parameters from unlabeled data were pre-calculated based on 2 millions genome-wide unlabeled variants and their FunLDA scores (Backenroth D. et al. 2018).
Getting started
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Package details |
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| Author | Zihuai He |
| Maintainer | Zihuai He <zihuai@umich.edu> |
| License | GPL-3 |
| Version | 0.1.0 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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