Changes in version 4.5.1 o Convert log(P-values) back to P-values for human using a chi-sq distribution Version 4: o New algorithm for human backgrounds o New function: toPWM() that takes both PFMs and PPMs Changes in version 3.5 o After further testing revert back to PWMEnrich 2.x group P-value algorithm o Introduced group sorting by top motifs Changes in version 3.1.4 o New way of estimating P-value for groups of sequences. Note this will produce different P-values for groups of sequences than PWMEnrich 2.x ! Changes in version 2.4.4 o Vignette update and fix naming of columns in the motif enrichment report Changes in version 2.4.2 o Improve promoter selection for human and mouse genomes (duplicates are now disregarded) Changes in version 2.4.0 o Major update with more functions and small bugfixes o Added sequenceReport() and groupReport() for easier report generation o Visualise motif scores along a sequence with plotMotifScores() o Creation of empirical CDFs for motif scores o Almost complete rewrite of the vignette to emphasize the main use cases o Converted documenation to roxygen2 Changes in version 2.3.2 o Subsetting functions for backgrounds from Diego Diez Changes in version 2.3.1 o Fix a bug with plotTopMotifsSequence() with calling an unknown function o Implement group.only for all background, not only pval in motifEnrichment() o New default to plotMultipleMotifs() so the margins are better Changes in version 2.2 o Bioconductor 2.12 release version (same as 2.0.0) Changes in version 2.0.0 o General cleanup of the code with various small optimisations o A FASTA file name is now also taken as input to motifEnrichment() o The output of motifEnrichment() is now wrapped into a class MotifEnrichmentResults that provides a number of convenience methods for common tasks like ranking and plotting motifs o Functions makeBackground() and getBackgroundFrequencies() can now take BSgenome objects as input. Thanks to Diego Diez for suggesting this and providing the code. o Another version of motifScores() has been implemented that requires large amounts of memory, but is at least 2 times faster than the old motifScores() implementation. Use a new option useBigMemoryPWMEnrich() to switch to this implementation. o PFMtoPWM now accepts a new parameter seq.count so that MotifDb motifs that are expressed as probabilities instead of frequencies can be easily used. Changes in version 1.3.0 o Bioconductor 2.11 release version Changes in version 1.0.2 o Use core package parallel instead of doMC Changes in version 1.0.1 o Fix a typo in test cases and remove doMC as build dependency Changes in version 1.0.0 o Initial release of the package