Package RAPIDR. R topics documented: February 19, 2015
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1 Package RAPIDR February 19, 2015 Title Reliable Accurate Prenatal non-invasive Diagnosis R package Package to perform non-invasive fetal testing for aneuploidies using sequencing count data from cell-free DNA Version Author Kitty Lo <kitty.lo@ucl.ac.uk> Maintainer Kitty Lo <kitty.lo@ucl.ac.uk> Depends R (>= 3.1.1) Imports data.table, Biostrings, Rsamtools, GenomicRanges, GenomicAlignments, PropCIs Suggests BSgenome.Hsapiens.UCSC.hg19 License GPL-3 LazyData false NeedsCompilation no Repository CRAN Date/Publication :16:37 R topics documented: BinBam createreferencesetfromcounts evalperformance gccontent makebinnedcountsfile makegccontentdata makegccontentperpos outcomes plottestsample print.rapidr.ref print.rapidr.test ReadBed testunknowns writecleanedcountsfile writeresultstofile
2 2 createreferencesetfromcounts Index 10 BinBam BinBam Given a list of bam files, this function writes the output to a text file after binning and doing gc Correction BinBam(bam.file, index = bam.file, mask = NULL, k = 20000) bam.file index mask k name of bamfile index of bam file mask file in the bed format bin size in kilobases createreferencesetfromcounts createreferencesetfromcounts This function creates a reference set from a binned counts file createreferencesetfromcounts(binned.counts.file, outcomes, combined.counts.fname = NULL, method = "zscore", gccorrect = FALSE, gccontentfile = NULL, filterbin = TRUE, removeoutliersamples = FALSE, PCA = FALSE, numpc = 10, masked.counts.file = NULL, cleaned.binned.counts.fname = NULL) binned.counts.file file name of the binned counts. The binned counts file should be comma delimited, and the first line need to be the chromosome names of each bin outcomes data.frame with column names: Dx, Gender, SampleID combined.counts.fname file name to write to for the combined counts per chromosomes, default is not to write result to file
3 evalperformance 3 Value method gccorrect gccontentfile either "zscore", "NCV" or "MAD", default is zscore whether to do gc correction or not (True = do the correction) file name of a Rdata object with the gccontent data filterbin whether to filter bins based on unusually high counts and high variance, default is to filter removeoutliersamples whether to remove samples which has a low correlation value to the rest of the reference set, default is FALSE PCA whether to do PCA correction or not (True = do the correction) numpc number of principal components to discard (default = 10) masked.counts.file file name of the masked counts file cleaned.binned.counts.fname file name to write to for the corrected binned counts, default is not to write to file class of rapidr.ref which can then be used to test unknown samples evalperformance evalperformance This function takes in the summed counts, the baseline and an outcomes table and calculates the overall performance on the dataset evalperformance(refset.calls, sample.outcomes) refset.calls is the data.frame returned by the testunknowns function. It contains column with sampleids, z-scores and calls for T21, T18, T13 and the fetal sex sample.outcomes data.frame with column names: Dx, Gender, SampleID See Also testunknowns
4 4 makebinnedcountsfile gccontent gccontent in 20kb bins This is an example output from running makegccontentdata() makebinnedcountsfile makebinnedcountsfile This function takes in a list of bam files and creates a binned counts file. If a mask file is provided, it will also create a masked binned counts file. The output file is comma separated and the first column is the sampleid, the header is the chromosome name of each bin. makebinnedcountsfile(bam.file.list, sampleids, binned.counts.fname, mask = NULL, k = 20000) bam.file.list sampleids list of bam file names list of sampleids, assumed to be in the same order as the bam files in bam.file.list binned.counts.fname file name of the output binned counts file mask k file name of a bed file with the regions to be masked out. Default is no mask file bin size in number of bases. Default is 20,000 bp See Also createreferencesetfromcounts
5 makegccontentdata 5 makegccontentdata makegccontentdata This function calculates the GC content using the hg19 reference genome in bins of user-defined size makegccontentdata(gc.fname, k = 20000) gc.fname k file name of the output file. The file will be written as a.rdata object bin size, default is 20,000 bp makegccontentperpos makegccontentperpos This function calculates the GC content using the hg19 reference genome for each position in the chromosome makegccontentperpos(gc.fname, k = 200) gc.fname k file name of the output file. The file will be written as a.rdata object bin size, default is 200 bp outcomes set of simulated outcomes data This is just a simulated data set for testing purpose
6 6 print.rapidr.ref plottestsample plottestsample This function plots the QC information. Note that it can only plot one sample at a time plottestsample(rapidr.test, input.sampleid, ordering = "normal") rapidr.test rapidr.test object which contains the results from testing a sample input.sampleid the sampleid that you like to plot ordering normal or gc, default is normal, when set to GC, the chromosomes are ordered according to GC content print.rapidr.ref print.rapidr.ref Pretty print the rapidr.ref object ## S3 method for class rapidr.ref print(x,...) x... other options rapidr.ref object which contains the baselines and the type of correction used to create the baselines
7 print.rapidr.test 7 print.rapidr.test print.rapidr.test Pretty print the rapidr.test object ## S3 method for class rapidr.test print(x,...) x rapidr.test object which contains the results of the test samples... other options ReadBed ReadBed This function loads a bed file ReadBed(bedfile) bedfile name of the bed file
8 8 writecleanedcountsfile testunknowns testunknowns This function uses a reference set to test the unknown samples The unknown samples needs to be a binned counts file which can be created using the makebinnedcountsfile function. testunknowns(ref.data.set, unknowns.counts.file, gccontentfile = NULL, masked.counts.file = NULL, combined.counts.fname = NULL) Value ref.data.set rapidr.ref object which contains the baselines and the corrections used to create the baselines unknowns.counts.file file name of the file with the binned counts of the unknowns, first column needs to be the sampleid, first row needs to be the chromosome names of each bin gccontentfile file name of a.rdata object which contains information on GC content in the genome masked.counts.file optional file of the binned counts after masking combined.counts.fname file name to write to for the combined counts per chromosome data.frame with z-scores for chr21, chr18, chr13, and the fetal sex which can be male, female or monosomy X. For males, there is also an estimate of the fetal fraction using the deficit of chrx writecleanedcountsfile writecleanedcountsfiles This function takes a binned.counts.file and applies GC correction or PCA correction and writes out the resulting binned counts as a a new file writecleanedcountsfile(binned.counts.file, cleaned.binned.counts.fname, gccontentfile, gccorrect = FALSE, PCA = FALSE)
9 writeresultstofile 9 binned.counts.file file name of the binned counts. The binned counts file should be comma delimited, and the first line need to be the chromosome names of each bin cleaned.binned.counts.fname file name to write to for the corrected binned counts, default is not to write to file gccontentfile gccorrect PCA file name of a Rdata object with the gccontent data whether to do gc correction or not (True = do the correction) whether to do PCA correction or not (True = do the correction) writeresultstofile writeresultstofile This function writes the rapidr.test object to a file writeresultstofile(rapidr.test, output.fname) rapidr.test output.fname rapidr.test object which contains the results from testing a sample file name of the output file (it will be tab delimited)
10 Index BinBam, 2 createreferencesetfromcounts, 2, 4 evalperformance, 3 gccontent, 4 makebinnedcountsfile, 4, 8 makegccontentdata, 5 makegccontentperpos, 5 outcomes, 5 plottestsample, 6 print.rapidr.ref, 6 print.rapidr.test, 7 ReadBed, 7 testunknowns, 3, 8 writecleanedcountsfile, 8 writeresultstofile, 9 10
RAPIDR. Kitty Lo. November 20, Intended use of RAPIDR 1. 2 Create binned counts file from BAMs Masking... 1
RAPIDR Kitty Lo November 20, 2014 Contents 1 Intended use of RAPIDR 1 2 Create binned counts file from BAMs 1 2.1 Masking.................................................... 1 3 Build the reference 2 3.1
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Type Package Title A LazyData Facility Version 1.1.0 Date 2016-12-05 Author Bill Venables Package lazydata December 4, 2016 Maintainer Bill Venables Description Supplies a LazyData
Package MethylSeekR. January 26, 2019
Type Package Title Segmentation of Bis-seq data Version 1.22.0 Date 2014-7-1 Package MethylSeekR January 26, 2019 Author Lukas Burger, Dimos Gaidatzis, Dirk Schubeler and Michael Stadler Maintainer Lukas
Package bayeslongitudinal
Type Package Package bayeslongitudinal July 25, 2017 Title Adjust Longitudinal Regression Models Using Bayesian Methodology Version 0.1.0 Date 2017-07-18 Author Edwin Javier Castillo Carreño, Edilberto
Package GUIDEseq. October 12, 2016
Type Package Title GUIDE-seq analysis pipeline Version 1.2.1 Date 2015-02-10 Package GUIDEseq October 12, 2016 Author Lihua Julie Zhu, Michael Lawrence, Ankit Gupta, Alper Kucukural, Manuel Garber, Scot
Package spark. July 21, 2017
Title 'Sparklines' in the 'R' Terminal Version 2.0.0 Author Gábor Csárdi Package spark July 21, 2017 Maintainer Gábor Csárdi A 'sparkline' is a line chart, without axes and labels.