diChIPMunk

[…] done using macs2 () (https://github.com/taoliu/macs) against preimmune and input control data. peak sets obtained with the preimmune control were smaller and were utilized for motif discovery with dichipmunk (,). resulting dinucleotide position weight matrices were used for motif finding in peaks obtained with the input control. to detect peaks with strong motif occurrences, we estimated […]

[…] 25 binding peaks (kwwgttacat) was consistent with the previously characterized repeat sequence of the ompr-binding site (tttgttacat) (fig. ). in addition, we used two other methods, chipmunk and dichipmunk, to identify dna sequence motifs of ompr–. the identified sequence motifs were similar to that from the meme software tool in that these two methods generated the previously known repeat […]

[…] have been shown to outperform simpler motif models like the pwm model [–]. examples for highly popular tools that model intra-motif dependencies are dimont [], meme-chip [], deepbind [], and dichipmunk []., in contrast, the second group of de-novo motif discovery approaches known as phylogenetic footprinting incorporates orthologous sequences of at least two phylogenetically related […]

[…] available chip data and existing binding motif models (positional weight matrices [pwms]) for oct4, sox2, and nanog were collected from available sources (; ; ). the chipmunk for classic pwms () and dichipmunk () programs were used for de novo motif discovery. raw published chip data were processed, and receiver operating characteristic (roc) curves were constructed as described earlier (). […]

[…] four computational models of two fundamental classes: pattern matching based on existing training set of experimentally confirmed tfbss (opwm and sitega) and de novo motif discovery (chipmunk and dichipmunk). to properly select prediction thresholds for the models, we experimentally evaluated affinity of 64 predicted foxa bss using emsa that allows safely distinguishing sequences able to bind […]

[…] order 1 than for motif order 0 for at least one combination of training and test data sets in supplementary figure s5–s13, and we compare the dependencies detected by dimont to those detected by dichipmunk () in section 6 of the supplementary material., new high-throughput techniques including chip-seq, chip-exo and pbms have greatly increased the quality and amount of data […]