Nothing
NEW FEATURES
NEW FEATURES
outlier_detect()
to using basilisk
for interfacing into python replacing reticulate
.NEW FEATURES
dasper
into a Bioconductor-friendly format using biocthis.junction_load()
, which loads raw junction data from RNA-sequencing into an RangedSummarizedExperiment
object. Includes an option to allow download of user-specified control junctions.junction_annot()
, which uses information from reference annotation and the strand of a junction to classify junctions as "annotated", "novel_acceptor", "novel_donor", "novel_exon_skip", "novel_combo", "ambig_gene" and "unannotated".junction_filter()
, which filters junctions by their count, width, annotation or if they overlap a set of user-defined regions.junction_norm()
, which normalises raw junction counts (into a proportion-spliced-in) by dividing the counts of each junction by the total number of counts in it's associated cluster.junction_process()
, a wrapper function for all "junction_" prefixed functions except junction_load()
. junction_score()
, which scores patient junctions based on the extent their counts deviate from a control count distribution.coverage_norm()
, which will load and normalise coverage for exonic/intronic regions corresponding to each junction.coverage_score()
, which scores coverage associated with each junction based on it's deviation from control coverage distributions. coverage_process()
, a wrapper function for all "coverage_" prefixed functions. outlier_detect()
, which uses the junction scores and coverage scores as input into an unsupervised outlier detection algorithm to find the most outlier-looking junctions in each sample. outlier_aggregate()
, which aggregates the junction-level outlier data to a cluster-level. outlier_process()
, a wrapper function for all "outlier_" prefixed functions. plot_sashimi()
, which enables the visualisation of junction data across genes/transcripts or regions of interest.Any scripts or data that you put into this service are public.
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