A method for performing epigenetic analysis comprising calculating an epigenetic potential energy landscape, or the corresponding joint probability distribution, of a genomic region within one or more genomic samples, wherein the PEL is defined by V X x = φ 0 − log P X x, wherein: ▪ V x ( x) is the PEL within a genomic region, ▪ P x ( x)is the joint probability of the random variable X, representing the methylation state of the modeled methylation sites, taking a value x within the genomic region, and ▪ Φ 0 is a constant; and wherein the joint probability distribution of a genomic region is computed by: P X x = 1 Z exp − V X x, wherein: ▪ P x ( x) is the joint probability of the random variable X, representing the methylation state of the modeled methylation sites, taking a value x within the genomic region, ▪ V X ( x) is the PEL within the genomic region, and ▪ Z is the partition function computed by a recursive method; wherein calculating the PEL comprises: a) partitioning a genome into discrete genomic regions; b) analyzing the methylation status within a genomic region by fitting a parametric statistical model (The Model) to methylation data that takes into account dependence among the methylation states at individual methylation sites and has the number of parameters growing slower than geometrically in the number of methylation sites inside the region; and c) computing and analyzing a PEL, or the corresponding joint probability distribution, within the genomic region and/or its subregions and/or merged super-regions, thereby performing epigenetic analysis, wherein the PEL is calculated as follows: V X x = − ∑ n = 1 N a n 2 x n − 1 − ∑ n = 2 N c n 2 x n − 1 2 x n − 1 − 1, wherein: ▪ V X ( x) is the PEL within a genomic region, ▪ N is the number of modeled methylation sites within the genomic region, and ▪ { a 1,...,a N} and { c 2,...,c N} are parameters of the model, wherein the PEL parameters { a 1,...,a N} and { c 2,...,c N} are specified by setting a n = α +βρ n and c n = γ / d n, wherein ρ n is the CpG density of the n -th modeled methylation site and d n is the distance of the n -th modeled methylation site from its "nearest-neighbor" modeled methylation site n -1; and wherein the method is implemented using a computer program operating on a computer system. ▪ V x ( x) is the PEL within a genomic region, ▪ P x ( x)is the joint probability of the random variable X, representing the methylation state of the modeled methylation sites, taking a value x within the genomic region, and ▪ Φ 0 is a constant; ▪ P x ( x) is the joint probability of the random variable X, representing the methylation state of the modeled methylation sites, taking a value x within the genomic region, ▪ V X ( x) is the PEL within the genomic region, and ▪ Z is the partition function computed by a recursive method; a) partitioning a genome into discrete genomic regions; b) analyzing the methylation status within a genomic region by fitting a parametric statistical model (The Model) to methylation data that takes into account dependence among the methylation states at individual methylation sites and has the number of parameters growing slower than geometrically in the number of methylation sites inside the region; and c) computing and analyzing a PEL, or the corresponding joint probability distribution, within the genomic region and/or its subregions and/or merged super-regions, thereby performing epigenetic analysis, wherein the PEL is calculated as follows: V X x = − ∑ n = 1 N a n 2 x n − 1 − ∑ n = 2 N c n 2 x n − 1 2 x n − 1 − 1, ▪ V X ( x) is the PEL within a genomic region, ▪ N is the number of modeled methylation sites within the genomic region, and ▪ { a 1,...,a N} and { c 2,...,c N} are parameters of the model, wherein the PEL parameters { a 1,...,a N} and { c 2,...,c N} are specified by setting a n = α +βρ n and c n = γ / d n, wherein ρ n is the CpG density of the n -th modeled methylation site and d n is the distance of the n -th modeled methylation site from its "nearest-neighbor" modeled methylation site n -1;