GMSimpute - Generalized Mass Spectrum Missing Peaks Abundance Imputation
GMSimpute implements the Two-Step Lasso (TS-Lasso) and compound minimum to recover the abundance of missing peaks in mass spectrum analysis. TS-Lasso is a label-free imputation method that handles various types of missing peaks simultaneously. This package provides the procedure to generate missing peaks (or data) for simulation study, as well as a tool to estimate and visualize the proportion of missing at random.
Last updated 6 years ago
3.06 score 23 scripts 205 downloadsNB.MClust - Negative Binomial Model-Based Clustering
Model-based clustering of high-dimensional non-negative data that follow Generalized Negative Binomial distribution. All functions in this package applies to either continuous or integer data. Correlation between variables are allowed, while samples are assumed to be independent.
Last updated 8 years ago
2.30 score 2 stars 5 scripts 195 downloadslncDIFF - Long Non-Coding RNA Differential Expression Analysis
We developed an approach to detect differential expression features in long non-coding RNA low counts, using generalized linear model with zero-inflated exponential quasi likelihood ratio test. Methods implemented in this package are described in Li (2019) <doi:10.1186/s12864-019-5926-4>.
Last updated 5 years ago
2.00 score 1 scripts 142 downloads