fitMixtureModel
(Package: wavClusteR) :
Fit a non-parametric mixture model from all identified substitutions
Estimates the two-component mixture model consisting of the mixing coefficients and the density functions.
● Data Source:
BioConductor
● Keywords: core, model
● Alias: fitMixtureModel
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annotateClusters
(Package: wavClusteR) :
Annotate clusters with respect to transcript features
Carries out strand-specific annotation of clusters with respect to distinct transcript features, particularly introns, coding sequences, 3'-UTRs, 5'-UTRs. Mapping to multiple features and to those outside the above mentioned ones are reported. Unmapped clusters are then futher further analyzed and annotated with respect to features localizing on the anti-sense strand. Results can be plotted as dotchart and annotations are returned as clusters metadata.
● Data Source:
BioConductor
● Keywords: graphics, postprocessing
● Alias: annotateClusters
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estimateFDR
(Package: wavClusteR) :
Estimate False Discovery Rate within the relative substitution frequency
Estimate upper and lower bounds for the False Discovery Rate within the relative substitution frequency (RSF) support by integrating PAR-CLIP data and RNA-Seq data (current version makes use of unstranded RNA-Seq)
● Data Source:
BioConductor
● Keywords: core, graphics
● Alias: estimateFDR
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Export clusters as BED track, compatible with the UCSC genome browser
● Data Source:
BioConductor
● Keywords: postprocessing
● Alias: exportClusters
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Export coverage as BigWig track, compatible with the UCSC genome browser
● Data Source:
BioConductor
● Keywords: postprocessing
● Alias: exportCoverage
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exportHighConfSub
(Package: wavClusteR) :
Export high-confidence substitutions as BED track
Export high-confidence substitutions as BED track, compatible with the UCSC genome browser
● Data Source:
BioConductor
● Keywords: postprocessing
● Alias: exportHighConfSub
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exportSequences
(Package: wavClusteR) :
Export cluster sequences for motif search analysis
Export cluster sequences for motif search analysis (FASTA format), e.g. using MEME-ChIP
● Data Source:
BioConductor
● Keywords: postprocessing
● Alias: exportSequences
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filterClusters
(Package: wavClusteR) :
Merge clusters and compute all relevant cluster statistics
If clusters have been identified using the mini-rank norm algorithm, cluster statistics are computed. In contrast, if the CWT-based cluster identification algorithm was used, clusters are first filtered to retain only those instances containing a wavelet peak and a high-confidence substitution site within their cluster boundaries.
● Data Source:
BioConductor
● Keywords: core
● Alias: filterClusters
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getAllSub
(Package: wavClusteR) :
Identify all substitutions observed across genomic positions exhibiting a
All substitutions observed across genomic positions exhibiting user-defined minimum coverage are extracted and a count table is returned. This function supports parallel computing.
● Data Source:
BioConductor
● Keywords: core
● Alias: getAllSub
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getClusters
(Package: wavClusteR) :
Identify clusters containing high-confidence substitutions and resolve
Identifies clusters using either the mini-rank norm (MRN) algorithm (default and recommended to achieve highest sensitivity) or via a continuous wavelet transform (CWT) based approach. The former employs thresholding of background coverage differences and finds the optimal cluster boundaries by exhaustively evaluating all putative clusters using a rank-based approach. This method has higher sensitivity and an approximately 10-fold faster running time than the CWT-based cluster identification algorithm. The latter, maintained for compatibility with wavClusteR, computes the CWT on a 1 kb window of the coverage function centered at a high-confidence substitution site, and identifies cluster boundaries by extending away from peak positions.
● Data Source:
BioConductor
● Keywords: core
● Alias: getClusters
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