Replication Timing Profiling using DNA Copy Number

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Documentation for package ‘Repliscope’ version 1.1.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

calcTrep	A function to calculate Trep values from a sync-seq experiment calcTrep function fits a Boltzman sigmoid function into relative copy number datapoints for every genomic bin of the provided sync-seq merged dataframe. It then extracts time at which half of the cells have this genomic bin replicated (Trep). The output of the function is a dataframe containing Trep and TrepErr data for every genomic bin in a BED-like format.
compareRatios	A function to compare two replication profiles
Dbf4myc	Sequence read coverage ratios for S.cerevisiae Dbf4-9myc sample.
guide	Guide dataframe for plotting smoothed sortSeq data
loadBed	Load a BED formatted file.
makeGenome	A helper function to create a gemome dataframe
makeLabels	A helper function to create axis ticks and human readable labels.
makeRatio	A function to calculate 'score' ratio between two bed dataframes makeRatio merges two supplied bed dataframes, calculates ratio of their "score" values normalises the ratio by the 'score' sums.
MFAseq	Replication profile for wild type DS2 H.volcanii
normaliseRatio	A function to normalise ratio values from 'ratio' column of the provided dataframe to fit biologically-relevant scale. It scales values either using supplied 'rFactor' value or automatically to best fit 1 to 2 scale (the upper limit of the scale may be adjusted with the upperLimit parameter). Normalisation factor used is stored in 'ratioFactor' column and also passed as the dataframe comment. To extract it, use 'attributes(mergedBed)$comment'
normalizeRatio	A function to normalise ratio values from 'ratio' column of the provided dataframe to fit biologically-relevant scale. It scales values either using supplied 'rFactor' value or automatically to best fit 1 to 2 scale (the upper limit of the scale may be adjusted with the upperLimit parameter). Normalisation factor used is stored in 'ratioFactor' column and also passed as the dataframe comment. To extract it, use 'attributes(mergedBed)$comment'
plotBed	A function to boxplot 'score' column of a BED dataframe, per unique chromosome name in the 'chrom' column. The resulting plot also highlights outliers based on the inter quartile range (IQR). The genome wide median is plotted as a pink line through the boxplots.
plotCoverage	A function to scatterplot 'score' column of a BED dataframe plotCoverage function plots values in the 'score' column of the supplied bed dataframe as a function of chromosome coordinates. The genome wide median is plotted as a pink line.
plotGenome	plotGenome: plot replication profile.
plotRatio	A function to plot a histogram of supplied ratio vector plotRatio plots histogram of values in a supplied vector using ggplot2 and highlights interval between 1 and 2 in green.
plotTrep	A function to scatterplot 'Trep' column of a Trep dataframe plotTrep function plots values in the 'Trep' column of the supplied dataframe as a function of chromosome coordinates. The genome wide median is plotted as a pink line.
rmChr	A function to remove single chromosome data from a bed dataframe
rmOutliers	A function to remove outliers from the "score" column of a supplied bed dataframe There are three methods: max, IQR and median. Max is used to remove 1 or more maximum values; IQR uses interquartile range to detect outliers, while median method can be used to remove data based on genome-wide median.
runGUI	A function to launch Repliscope in interactive mode (Shiny app).
sacCer3	S.cerevisiae genome information
smoothRatio	A function to smooth ratio values using cubic smoothing spline smoothRatio function splits values from 'ratio' column by chromosome and based the supplied 'groupMin' and 'split' parameters and then applies smooth.spline() function from R stats package. The supplied dataframe may contain multiple ratios, i.e. ratios produced using multiple replicating samples and/or multiple non-replicating samples. This must be reflected in 'name.rep' and 'name.nonRep' columns. In other words, different ratio dataframes may be merged using rbind() function before calling smoothRatio() function.
sortSeq	Replication profiles for wild type and Dbf4-9myc S.cerevisiae samples
syncSeq	Replication profiles budding yeast arrest-release samples
TrepDF	Trep data calculated from syncSeq[["data"]]
trimRatio	A function to remove outliers from the "ratio" column of a supplied ratio dataframe trimRatio is applied to the calculated ratio of read counts from a replicating to a non-replicating samples.
W303	Sequence read coverage ratios for wild type S.cerevisiae W303
W303norm	Normalised sequence read coverage ratios for wild type S.cerevisiae W303
W303_G2	Sequence read coverage for wild type S.cerevisiae W303 non-replicating sample.
W303_S	Sequence read coverage for wild type S.cerevisiae W303 replicating sample