Predict the Hybridization Efficiency of Probe/Target Sequence Pairs

Description

Calculates the Gibbs free energy and hybridization efficiency of probe/target pairs at varying concentrations of the denaturant formamide.

Usage

CalculateEfficiencyArray(probe,
                         target,
                         FA = 0,
                         dGini = 1.96,
                         Po = 10^-2.0021,
                         m = 0.1731,
                         temp = 42,
                         deltaGrules = NULL)

Arguments

Details

This function calculates the free energy and hybridization efficiency (HE) for a given formamide concentration ([FA]) using the linear free energy model given by:

HE = Po*exp[-(dG_0 + m*FA)/RT]/(1+Po*exp[-(dG_0 + m*FA)/RT])

The probe and target input sequences must be aligned in pairs, such that the first probe is aligned to the first target, second-to-second, and so on. Ambiguity codes in the IUPAC_CODE_MAP are accepted in probe and target sequences. Any ambiguities will default to perfect match pairings by inheriting the nucleotide in the same position on the opposite sequence whenever possible. If the ambiguity results in a mismatch then “T”, “G”, “C”, and “A” are substituted, in that order. For example, if a probe nucleotide is “S” (“C” or “G”) then it will be considered a “C” if the target nucleotide in the same position is a “C”, otherwise the ambiguity will be interpreted as a “G”.

If deltaGrules is NULL then the rules defined in data(deltaGrules) will be used. Note that deltaGrules of the same format may be customized for any application and specified as an input.

Value

A matrix with the predicted Gibbs free energy (dG) and hybridization efficiency (HE) at each concentration of formamide ([FA]).

Author(s)

Erik Wright DECIPHER@cae.wisc.edu

References

Yilmaz LS, Loy A, Wright ES, Wagner M, Noguera DR (2012) Modeling Formamide Denaturation of Probe-Target Hybrids for Improved Microarray Probe Design in Microbial Diagnostics. PLoS ONE 7(8): e43862. doi:10.1371/journal.pone.0043862.

See Also

deltaGrules

Examples

probes <- c("AAAAACGGGGAGCGGGGGGATACTG", "AAAAACTCAACCCGAGGAGCGGGGG")
targets <- c("CAACCCGGGGAGCGGGGGGATACTG", "TCGGGCTCAACCCGAGGAGCGGGGG")
result <- CalculateEfficiencyArray(probes, targets, FA=0:40)
dG0 <- result[, "dG_0"]
HE0 <- result[, "HybEff_0"]
plot(result[1, 1:40], xlab="[FA]", ylab="HE", main="Probe/Target # 1", type="l")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(DECIPHER)
Loading required package: Biostrings
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: XVector
Loading required package: RSQLite
Loading required package: DBI
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/DECIPHER/CalculateEfficiencyArray.Rd_%03d_medium.png", width=480, height=480)
> ### Name: CalculateEfficiencyArray
> ### Title: Predict the Hybridization Efficiency of Probe/Target Sequence
> ###   Pairs
> ### Aliases: CalculateEfficiencyArray
> 
> ### ** Examples
> 
> probes <- c("AAAAACGGGGAGCGGGGGGATACTG", "AAAAACTCAACCCGAGGAGCGGGGG")
> targets <- c("CAACCCGGGGAGCGGGGGGATACTG", "TCGGGCTCAACCCGAGGAGCGGGGG")
> result <- CalculateEfficiencyArray(probes, targets, FA=0:40)
> dG0 <- result[, "dG_0"]
> HE0 <- result[, "HybEff_0"]
> plot(result[1, 1:40], xlab="[FA]", ylab="HE", main="Probe/Target # 1", type="l")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>