Bias-corrected estimators for proportion of true null hypotheses: application of adaptive FDR-controlling in segmented failure data.

Two recently introduced model-based bias-corrected estimators for proportion of true null hypotheses ( ) under multiple hypotheses testing scenario have been restructured for random observations under a suitable failure model, available for each of the common hypotheses. Based on stochastic ordering, a new motivation behind formulation of some related estimators for is given. The reduction of bias for the model-based estimators are theoretically justified and algorithms for computing the estimators are also presented.

An analysis of COVID-19 clusters in India : Two case studies on Nizamuddin and Dharavi.

Background: In this study we cluster the districts of India in terms of the spread of COVID-19 and related variables such as population density and the number of specialty hospitals. Simulation using a compartment model is used to provide insight into differences in response to public health interventions. Two case studies of interest from Nizamuddin and Dharavi provide contrasting pictures of the success in curbing spread.

A powerful method to integrate genotype and gene expression data for dissecting the genetic architecture of a disease.

To decipher the genetic architecture of human disease, various types of omics data are generated. Two common omics data are genotypes and gene expression. Often genotype data for a large number of individuals and gene expression data for a few individuals are generated due to biological and technical reasons, leading to unequal sample sizes for different omics data.