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seqCBS (version 1.2.1)

Copy Number Profiling using Sequencing and CBS

Description

This is a method for DNA Copy Number Profiling using Next-Generation Sequencing. It has new model and test statistics based on non-homogeneous Poisson Processes with change point models. It uses an adaptation of Circular Binary Segmentation. Also included are methods for point-wise Bayesian Confidence Interval and model selection method for the change-point model. A case and a control sample reads (normal and tumor) are required.

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Version

Install

install.packages('seqCBS')

Monthly Downloads

44

Version

1.2.1

License

GPL-2

Maintainer

Jeremy J Shen

Last Published

April 13th, 2019

Functions in seqCBS (1.2.1)

ScanStatNewComp

Main new window scan statistics computation
JSSim_NormalSim2

Simulated normal sample dataset 2
ScanCBSPlot

Main Plotting of the scan statistic segmentation
nhppRateEstimate

Estimate the rate of non-homogeneous PP with data
ScanCBS

Main CBS Algorithm for Change-Point Detection
nhppSimConstWindowAnalysis

Analyze the performance on simulation with constant signal length in each set
SegSeqResProcess

Read and Process result of SegSeq
getAutoGridSize

Get Automatic Grid Sizes
readListInputFile

Read meta file containing list of raw data files
readInput

Manage reading and merging of raw datasets. Main file input
ScanCBSSimPlot

Plotting for CBS results of Simulated Data
readSeq

Wrapper for managing the reading of different raw data formats
ScanIterateGrid

Main Scan with Iterative Grid Search
hppSimulate

Simulate a homogeneous Poisson Process
getCountsInWindow

Get number of reads in fixed-width window
seqCBS-package

Scan Statistics CNV detection using sequencing data
nhppSimConstWindowGen

Simulate a Non-Homogeneous PP with constant window spike
ScanStatRefineComp

Main refining window scan statistics computation
nhppSpikeConstWindow

Spike NHPP rate with constant window width
nhppSpike

Spike rates of NHPP
nhppSimulate

Simulate a non-homogeneous Poisson Process
relCNComp

Compute the Relative Copy Number
readSeqELANDPaired

Read raw data formatted as in paired ELAND output
readSeqChiang

Read data formatted as in Chiang (2009)
BayesCptCI

Bayesian Point-wise Confidence Interval for Change-Point Model
JSSim_SpikeMat

True Signal Spike for the Simulated Dataset
JSSim_NormalSim1

Simulated normal sample dataset 1
CombineCaseControlC

Combine case and control reads
JSSim_TumorSim2

Simulated Tumor sample dataset 2
JSSim_TumorSim1

Simulated Tumor sample dataset 1
ScanBIC

Compute the modified BIC for change-point models
CombineReadsAcrossRuns

Combine multiple read lists
JSSim_Meta

Meta File for Simulated Datasets