• Genomics & Informatics
• /
• v.20 no.4
• /
• pp.48.1-48.7
• /
• 2022

Penalized regression has been widely used in genome-wide association studies for joint analyses to find genetic associations. Among penalized regression models, the least absolute shrinkage and selection operator (Lasso) method effectively removes some coefficients from the model by shrinking them to zero. To handle group structures, such as genes and pathways, several modified Lasso penalties have been proposed, including group Lasso and sparse group Lasso. Group Lasso ensures sparsity at the level of pre-defined groups, eliminating unimportant groups. Sparse group Lasso performs group selection as in group Lasso, but also performs individual selection as in Lasso. While these sparse methods are useful in high-dimensional genetic studies, interpreting the results with many groups and coefficients is not straightforward. Lasso's results are often expressed as trace plots of regression coefficients. However, few studies have explored the systematic visualization of group information. In this study, we propose a multi-level polar Lasso (MP-Lasso) chart, which can effectively represent the results from group Lasso and sparse group Lasso analyses. An R package to draw MP-Lasso charts was developed. Through a real-world genetic data application, we demonstrated that our MP-Lasso chart package effectively visualizes the results of Lasso, group Lasso, and sparse group Lasso.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39A no.3
• /
• pp.127-139
• /
• 2014

In this paper, we present two signal processing techniques for designing binary error correction codes for Multi-Level Cell(MLC) NAND flash memory. MLC NAND flash memory saves the non-binary symbol at each cell and shows asymmetric channel LLR l-density which makes it difficult to design soft-decision binary error correction codes such as LDPC codes and Polar codes. Therefore, we apply density mirroring and EM algorithm for approximating the MLC NAND flash memory channel to the binary-input memoryless channel. The density mirroring processes channel LLRs to satisfy roughly all-zero codeword assumption, and then EM algorithm is applied to l-density after density mirroring for approximating it to mixture of symmetric Gaussian densities. These two signal processing techniques make it possible to use conventional code design algorithms, such as density evolution and EXIT chart, for MLC NAND flash memory channel.