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MSigSeg (version 0.2.0)

Multiple SIGnal SEGmentation

Description

Traditional methods typically detect breakpoints from individual signals, which means that when applied separately to multiple signals, the breakpoints are not aligned. However, this package implements a common breakpoint detection approach for multiple piecewise constant signals, resulting in increased detection sensitivity and specificity. By employing various techniques, optimal performance is ensured, and computation is accelerated. We hope that this package will be beneficial for researchers in signal processing, bioinformatics, economy, and other related fields. The segmentation(), lambda_estimator() functions are the main functions of this package.

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Version

Install

install.packages('MSigSeg')

Monthly Downloads

158

Version

0.2.0

License

GPL-3

Maintainer

Xuanyu Liu

Last Published

November 13th, 2023

Functions in MSigSeg (0.2.0)

T16P

A chromosome sequencing data set used as an example.
MSigSeg-class

An S4 class to encapsulation the result of breakpoints analysis.
data.input

Generic Function-data.input.
data.output

Generic Function-data.output.
brkps

Generic Function-brkps.
lambda

Generic Function-lambda.
change

Breakpoints matrix generation.
noisegen

Noisegen.
seg.len

Generic Function-seg.len.
segmentation

Detecting common change points for multiple signals.
summary

Generic Function-summary.
lambda_estimator

Detecting common breakpoints with designated number.
print

Generic Function-print.
multi_plot

Plot function of MSigSeg package.
NCHSData

influenza data set from CDC used as an example.
data_test

A simulated data set used for testing.
stock

A stock data set used as an example.
T16M

A chromosome sequencing data set used as an example.