JAMIE (Joint Analysis of Multiple IP Experiments) is a R package to perform the joint analysis. The genome is assumed to consist of background and potential binding regions (PBRs). PBRs have context-dependent probabilities to become bona fide binding sites in individual datasets. This model captures the correlation among datasets, which provides basis for sharing information across experiments. Real data tests illustrate the advantage of JAMIE over a strategy that analyzes individual datasets separately.
Bayesian Joint Analysis is an approach to address the two key questions in parallel, which incorporates the information of functional annotations into expression data analysis and meanwhile infer the enrichment of functional groups.
DLMM (Double-layered Mixture Model) is a software to select copy number-associated gene expression changes in high-throughput genomics data. Copy number segmentation results and criterion-based gene selection are separately reported.
AIS (ALLELES IN SPACE) is a computer program for the joint analysis of inter-individual spatial and genetic information. This program performs a variety of spatial analyses with genetic data including: Mantel Tests, Spatial Autocorrelation Analyses, Allelic Aggregation Index Analyses (AAIA), Mommonier’s Algorithm, and “Genetic Landscape Shape” interpolations