Methylscaper provides an interactive and optimal ordering of individual DNA molecules to discover methylation patterns, nucleosome positioning, and transcription factor binding.
SCnorm first groups genes based on their estimated count-depth relationship. Within each group, a quantile regression is applied to estimate scaling factors which will remove the effect of sequencing depth.
Trendy utilizes segmented regression models to simultaneously characterize each gene’s expression pattern and summarize overall dynamic activity in ordered condition experiments. For each gene, Trendy finds the optimal segmented regression model and provides the location and direction of dynamic changes in expression. The top dynamic genes are then identified as genes that can be well profiled by its gene-specific segmented regression model. The software package also includes an R/Shiny application to view individual gene’s dynamic trends.