Relationship between gene regulation network structure and prediction accuracy in high dimensional regression
Abstract The least absolute shrinkage and selection operator (lasso) and principal component regression (PCR) are popular methods of estimating traits from high-dimensional omics data, such as transcriptomes. The prediction accuracy of these estimation methods is highly dependent on the covariance s...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-06-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-90791-6 |