Screen Large-Scale Data
The analysis of large-scale data sets, where hundreds or thousands of measurements are taken on a part or an organism, requires innovative approaches. But testing many responses for the effects of factors can be challenging, if not misleading, without appropriate methodology.
Response Screening automates the process of conducting tests across a large number of responses. Your test results and summary statistics are presented in data tables, rather than reports, to enable data exploration. A False-Discovery Rate approach guards against incorrect declarations of significance. Plots of p-values are scaled using the LogWorth, making them easily interpretable.
Because large scale data sets are ...