Package 'SweepDiscovery'

Title: Selective Sweep Discovery Tool
Description: Selective sweep is a biological phenomenon in which genetic variation between neighboring beneficial mutant alleles is swept away due to the effect of genetic hitchhiking. Detection of selective sweep is not well acquainted as well as it is a laborious job. This package is a user friendly approach for detecting selective sweep in genomic regions. It uses a Random Forest based machine learning approach to predict selective sweep from VCF files as an input. Input of this function, train data and new data, can be computed using the project <https://github.com/AbhikSarkar1999/SweepDiscovery> in 'GitHub'. This package has been developed by using the concept of Pavlidis and Alachiotis (2017) <doi:10.1186/s40709-017-0064-0>.
Authors: Abhik Sarkar [aut, cre], Dwijesh Chandra Mishra [aut], Dipro Sinha [aut], Saikath Das [aut], Md Yeasin [aut]
Maintainer: Abhik Sarkar <[email protected]>
License: GPL-3
Version: 0.1.1
Built: 2025-02-26 03:44:42 UTC
Source: https://github.com/cran/SweepDiscovery

Help Index

SweepPrediction

Description

SweepPrediction

Usage

SweepPrediction(Traindata = NULL, Newdata)

Arguments

Traindata

Dataset for training
Newdata

New data for prediction

Value

  • Prediction: Results

References

  • Pavlidis, P., Alachiotis, N. A survey of methods and tools to detect recent and strong positive selection. J of Biol Res-Thessaloniki 24, 7 (2017). https://doi.org/10.1186/s40709-017-0064-0

Examples

library("SweepDiscovery")
data <- system.file("extdata", "data.csv", package = "SweepDiscovery")
Data<- read.csv(data)
pred<-SweepPrediction(Traindata=NULL,Newdata=Data)