Package index • utanos

All functions

ACNDiversityPlot(): Absolute Copy-Number Diversity Heatmap

AbsoluteCopyNumberDistance(): Compute distance function for fitting relative copy numbers to absolute

AbsoluteCopyNumberDistanceGrid(): Compute distance function for fitting relative copy numbers for a grid of ploidies and cellularities

AddChromosomeArm(): Adds a column for the chromosome arm in which each segment is in.

AddChromosomeArmHelper(): Adds a chromosome arm column to df at the respective positions for each chromosome.

AddGenesToPlot(): Label genes of interest on an absolute copy-number plot.

AssignLevels(): Gather big segments and assign levels iteratively

BreakSmoothToLGA(): Preps segments for LGA call.

BuildWxQdnaObject(): Build a QDNAseq object from the WisecondorX output files

CNSegmentsPlot(): Segment Copy Number Plot across the Genome

CalculateACNs(): Calculate Absolute Copy Numbers

CallLGA(): Determines number of large genomic alterations (LGAs) for sizes 3:11

CallSignatureExposures(): Wrapper to find Signature Exposures for a set of samples

ChooseNumberSignatures(): Choose an Optimal Number of Signatures

ChromosomeSplitPos(): Split Chromosome Name

CleanBamRatiosFrame(): Performs some cleaning operations.

CollapseTableToSegments(): Collapses down table to segmented copy numbers

CollapsedSegs(): Collapse segments

ComponentSignaturesHeatmap(): Create Heatmap of Component loadings per Signature

CopyNumberSegments(): Collapses relative copy-number calls to segment tables

CopySegFlat(): Make a DF of CNs and Segments from S4 QDNAseq object

CorrectLeftovers(): Adds 'leftsovers' to the segment frame after re-inserting small segments.

DetermineNumberOfLGAs(): Determines if the given segments are LGAs of the given size

DlpToQDNAseq(): Build a QDNAseq object from the DLP output files

ExcludeShortArms(): Removes the short chromosome arms (21, 22, 24) & keeps segments with size >= 3Mb

ExportBinsQDNAObj(): Export the CN bins of a QDNAseq Object to a wide dataframe

ExtractCopyNumberFeatures(): Extract Absolute Copy-Number Features

ExtractRelativeCopyNumberFeatures(): Extract Relative Copy-Number Features

FilterCNs(): Remove or set a mask for relative CN bins (QDNAseq object)

FinalizeSmallSegments(): Re-inserts small segments in between the large ones.

FindBestFitSolutions(): Find best fit solutions for fitting copy numbers through grid-based search

FindBigSegmentsIndices(): Finds the indices of big segments that are close ratio_median-wise

FindRascalSolutions(): Find best fitting solutions for each sample

FindThreshold(): Determines threshold for ratio_median difference via KDE.

FitComponent(): Fit a Mixture Model for a provided CN-Feature

FitMixtureModels(): Fit Mixture Models for each CN-Feature

GatherSegmentsByLevels(): Merges segments by level.

GatherSegmentsByRatioMedian(): Merges segments that are in the same chromosome arm AND have the same ratio_median.

GatherSegmentsByRatioMedianHelper(): Merges segments that have the same ratio_median and are in the same chromosome arm.

GaussiansMixturePlot(): Plot a Mixture of Gaussians

GenHumanReadableAcnProfile(): Generate Human Readable Absolute Copy-Number Profiles

GenHumanReadableRcnProfile(): Generate Human Readable Relative Copy-Number Profiles

GenerateSampleByComponentMatrix(): Generate sum-of-posteriors probability matrix

GenerateSignatures(): Create CN-Signatures

GetCNTally(): Extract Copy Number Tally Matrix

GetCriticalPoints(): Finds critical points (minima or maxima) of the differences between segments ratios.

GetGRangesObject(): Returns a GRanges object used to obtain data from specified genomic regions.

GetHRDStatus(): Returns the HRD status of a sample

GetInfoSegm(): TODO: write docs

GetLGAOfSize(): Returns the segments that are LGAs of the given size

GetLargeSegments(): Returns segments with a size >= 3Mb.

GetSampleQualityDecision(): Calculate and make a quality call for relative copy number profiles

GetSegCounts(): Calculate segment sizes

GetSegmentID(): Re-assigns level column values for all segments.

GetSegmentationBeforeLGACall(): Final segmentation before LGA call

GetSmallSegments(): Returns the segments with 3Mb >= size >= 0.1Mb

InitalizeSmallSegments(): Initializes the process of re-inserting the small segments in between the large ones.

InsertSmallSegments(): Adds small segments in small_segments that meet certain criteria (position wise w.r.t large segments) into the large_segments data frame. Merges if necessary (i.e. if ratio_median difference < threshold).

IsAcceptablePloidyAndCellularity(): Determine if a given ploidy and cellularity for fitting copy numbers is acceptable

LargeMissingChrArms(): Deals with missing chromosome arm values in the given data frame of large segments.

MakeSummaryTable(): Makes Relative Copy-Number Gain/Loss Summary Tables

MedSegVar(): Calculate median segment-level variance per sample

MergeSegmentsFiveLargeSmall(): Deals with merging large segment to small segment.

MergeSegmentsFiveSmallNextLarge(): Deals with merging small segment to next_large segment.

MergeSegmentsFour(): Handles merging step for the fourth case of FinalizeSmallSegments.

MergeSegmentsTwo(): Helper for merging segments in the second case of FinalizeSmallSegments. Returns the updated large_segments data frame with segments appropriately merged (or not... depending on parameters).

MixtureModelPlots(): Plot Mixture Model Components by Signature

NullListOfThresholds(): This function is ran in case that no possible thresholds were found.

PlotAnnotationBars(): Create annotation bars

PlotCNTallySig(): Plot Copy Number Tally Signature Contributions

PlotSegmentChanges(): A plot illustrating the merging of segments by the SHRD algorithm.

PoissonsMixturePlot(): Plot a Mixture of Poissons

PrepFirstRound(): Preps the segment data frame for use in the first round of threshold estimation.

PrepForLevelsInitialization(): Calls some helpers to do something to gathered by ratio medians.... gotta check this Also adds a Level and an Index column to the data frame

PrepSecondRound(): Preps the segment data frame for use in the second round of threshold estimation.

QualityPlot(): Plot sample quality according to a specified metric.

QuantifySignatures(): Quantify Signature Exposures

RCNDiversityPlot(): Plot relative CN diversity heatmap

RatioDiffBelowThreshold(): Determines if absolute ratio_median difference is less than or equal to the given threshold.

RelativeToAbsoluteCopyNumber(): Convert relative copy numbers to absolute copy numbers

RemoveCentromereTelomeres(): Removes centromeres and telomeres from 22 chromosomes (23rd if specified)

RemoveSpuriousRegions(): Removes specific genomic regions (centromeres and telomeres) of all chromosomes

ReplaceQDNAseqAssaySlots(): Replacethe QDNAseq Assay Slots

RunShallowHRD(): Run shallowHRD on a dataframe or file containing segmented relative copy-number data.

RunShallowHRDFromQDNA(): Run ShallowHRD on a QDNAseq object.

RunThresholdSimulations(): Runs simulations to obtain a list of possible thresholds from the segment ratio differences

SEAlluvialPlot(): Make an Alluvial Plot based on maximum signature exposure

SegmentsToCopyNumber(): Transforms segment tables into per-bin copy-number tables.

ShrinkReprTMP(): (Kind of) merges segments that lie on the same level.

SignatureExposuresPlot(): Create Heatmap of Signature Exposures

SmallMissingChrArms(): Deals with missing chromosome arm values in the given data frame of small segments.

StackedExposuresPlot(): Create a Stacked Bar-plot of Signature Exposures

SummaryCNPlot(): Generate Summary Copy-Number Aberrations Plot

TumourFraction(): Compute tumour DNA fraction for the given absolute copy number and cellularity

WassDistancePlot(): Plot a Heatmap of Component-wise Wasserstein Distances