GenoNet.example: Data example for GenoNet (A semi-supervised approach for...
In Ionita-Laza-lab/GenoNet: A Semi-Supervised Approach for Predicting Cell-Type Specific Functional Consequences of Non-Coding Variation
Description
The dataset contains training data, test data, and pre-calculated parameters based on 2 millions genome-wide unlabeled variants and their FunLDA scores (Backenroth D. et al. 2018).
Usage
1
Details
beta.FunLDA: pre-calculated parameters from FunDLA for 127 tissues. See the complete list of tissues at http://www.funlda.com/genonet/help.
training.data: example training data
test.data: example test data
Ionita-Laza-lab/GenoNet documentation built on Nov. 5, 2019, 2:22 p.m.
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Description
The dataset contains training data, test data, and pre-calculated parameters based on 2 millions genome-wide unlabeled variants and their FunLDA scores (Backenroth D. et al. 2018).
Usage
1 |
Details
beta.FunLDA: pre-calculated parameters from FunDLA for 127 tissues. See the complete list of tissues at http://www.funlda.com/genonet/help.
training.data: example training data
test.data: example test data
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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