Estimate regions for which a genomic profile deviates from its baseline value. Originally implemented to detect differentially methylated genomic regions between two populations.
This function performs the bumphunting approach described by Jaffe et al. International Journal of Epidemiology (2012). The main output is a table of candidate regions with permutation or bootstrap-based family-wide error rates (FWER) and p-values assigned.
The general idea is that for each genomic location we have a value for several individuals. We also have covariates for each individual and perform regression. This gives us one estimate of the coefficient of interest (a common example is case versus control). These estimates are then (optionally) smoothed. The smoothing occurs in clusters of locations that are ‘close enough’. This gives us an estimate of a genomic profile that is 0 when uninteresting. We then take values above (in absolute value) cutoff as candidate regions. Permutations can then performed to create null distributions for the candidate regions.
AND DMP-finder:
searches for individual differentially methylated positions/probes (DMPs) by regressing the methylation M-value for each sample at a given genomic location against the phenotype data for those samples.
Add BumpHunter (From minfi/R): https://rdrr.io/bioc/bumphunter/man/bumphunter.html
AND DMP-finder: