Introduction | Basic sequence handling | Creating random sequences | Calculating sequence background | Clustering sequences by k-let composition | Shuffling | Shuffling sequences | Local shuffling | Composition-matched backgrounds with match_bkg() | Generating ground-truth positive sequences with implant_motifs() | Motif pair co-occurrence with motif_coocc() | Sequence scanning and enrichment | Choosing a logodds threshold | Logodds thresholds | P-values | Multiple testing-corrected P-values | Regular and higher order scanning | A faster alternative: scan_sequences2() | Speed comparison vs motifmatchr and yamtk | Visualizing motif hits across sequences | Enrichment analyses | A faster alternative: enrich_motifs2() | De novo motif discovery | Positional enrichment with motif_peaks() | Proximity enrichment with motif_proximity() | Fixed and variable-length gapped motifs | Detecting low complexity regions and sequence masking | Motif discovery with MEME | Miscellaneous string utilities | Session info | References

Introduction | Loading motifs from several sources | Sidebar: importing raw files directly | Inspecting cross-source redundancy | Deduplicating via graph clustering | Visualising the cluster structure | Trimming uninformative flanks | Adding the metadata back | Export as a single MEME file | Session info | References

Introduction | Motif comparisons | An overview of available comparison metrics | Comparison parameters | Comparison P-values | A faster alternative: compare_motifs2() | Speed comparison vs compare_motifs() and yamtk cmp | Merging motifs | A faster alternative: merge_motifs2() / merge_similar2() | Motif trees with ggtree | Using motif_tree() | Using compare_motifs() and ggtree() | Plotting motifs alongside trees | Motif P-values | The dynamic programming algorithm for calculating P-values and scores | The branch-and-bound algorithm for calculating P-values from scores | The random subsetting algorithm for calculating scores from P-values | Session info | References

Introduction | Loading peaks from a BED file | Extracting peak sequences and building a matched background | De novo motif discovery | Deduplicating the discovered set | Comparing against JASPAR via MotifDb | Validating enrichment against a composition-matched background | Scanning all peaks and testing positional bias | Motif clustering with motif_coocc() | Summary table | Session info | References

Introduction | The universalmotif class and conversion utilities | The universalmotif class | Converting to and from another package's class | Importing and exporting motifs | Importing | Exporting | Modifying motifs and related functions | Converting motif type | Merging motifs | Motif reverse complement | Switching between DNA and RNA alphabets | Motif trimming | Rounding motifs | Motif creation | From a PCM/PPM/PWM/ICM matrix | From sequences or character strings | Generating random motifs | Motif visualisation | Motif logos | Stacked motif logos | Plot arbitrary text logos | Higher-order motifs | | Sequence | Tidy motif manipulation with the universalmotif_df data structure | Miscellaneous motif utilities | DNA/RNA/AA consensus functions | Filter through lists of motifs | Generate random motif matches | Motif shuffling | Scoring and match functions | Type conversion functions | Session info | References

Position count matrices | | Sequence | Position probability matrices | Position weight matrices | Information content matrices | References

Installation | Overview