R.Bioinformatics

R language bioinformatics analysis package wrapper for VisualBasic.

This project is aim at provides a high performance distribution and parallel computing environment for bioinformatics data analysis of VisualBasic hybrid programming with R.

Runtime

Require of sciBASIC# computing runtime

PM> Install-Package sciBASIC

Or reference to source code project:

https://github.com/xieguigang/sciBASIC#

Introduction

Folks from project: R.NET https://rdotnet.codeplex.com/

Currently there is a bioconductor GUI installer was included in this project for those beginners in the area of bioinformatics and some of the common used R package wrapper class which written in VisualBasic was developed to extends the biological data analysis ability of GCModeller and Microsoft .NET languages.

VisualBasic & R language hybrids

For example:

Imports RDotNET.Extensions.VisualBasic
Imports RDotNET.Extensions.VisualBasic.API.base
Imports RDotNET.Extensions.VisualBasic.API.utils
Imports RDotNET.Extensions.Bioinformatics.deSolve.API
Imports RDotNET.Extensions.Bioinformatics.deSolve

' Entering Microsoft R language environment by using VisualBasic language syntax specific
' Enable R session runtime
SyncLock R
    With R

        ' Setup variables in R language from VisualBasic
        .call = $"p      <- {p}"
        .call = $"beta   <- {beta}"
        .call = $"c      <- {c}"
        .call = $"delta  <- {delta}"
        .call = $"U0     <- {U0}"
        .call = $"rho    <- {rho}"
        .call = $"lambda <- {lambda}"

        ' For variable initialize like: p <- value
        ' Dim p As var = value, this expression is also working
    End With
End SyncLock

' The initial value for infected cells(I0) is set to zero.
' The best model based on the Akaike Information Criterion(AIC) is presented in Figure3, providing an estimate of 9 ffu/ml for V0.
' The initial number of susceptible cells(U0) can be taken from the experiment in Half mannetal. (2008) as 5 × 10^5.
Dim yini = "c(U=U0, I=0, V=9)"
Dim model = [function](
    {
        "t",
        "y",
        "params"
    },
_
    "with(as.list(y), {

        dU <- lambda - rho * U - beta * U * V
        dI <- beta * U * V - delta * I
        dV <- p * I - c * V

        list(c(dU, dI, dV))
})")

require("deSolve")

' Calling ode{deSolve}
Dim times = seq([from]:=0, [to]:=5.6, by:=0.01)
Dim out = ode(y:=yini,
              times:=times,
              func:=model,
              parms:=NULL,
              method:=integrator.rk4)

' Calling write.csv{utils}
Call write.csv(out, "x:\ebola_test.csv")