Description Usage Arguments Details Value Note Author(s) References See Also Examples

The denaturation of double-stranded DNA occurs over a range of temperatures. Beginning from a helical state, DNA will transition to a random-coil state as temperature is increased. `MeltDNA`

predicts the positional helicity, melt curve, or its negative derivate at different temperatures.

1 2 3 4 |

`myDNAStringSet` |
A |

`type` |
Character string indicating the type of results desired. This should be (an abbreviation of) one of |

`temps` |
Numeric vector of temperatures (in degrees Celsius). |

`ions` |
Numeric giving the molar sodium equivalent ionic concentration. Values must be at least 0.01M. |

When designing a high resolution melt (HRM) assay, it is useful to be able to predict the results before performing the experiment. Multi-state models of DNA melting can provide near-qualitative agreement with experimental DNA melt curves obtained with quantitative PCR (qPCR). `MeltDNA`

employs the algorithm of Tostesen et al. (2003) with an approximation for loop entropy that runs in nearly linear time and memory, which allows very long DNA sequences (up to 100,000 base pairs) to be analyzed.

Denaturation is a highly cooperative process whereby regions of double-stranded DNA tend to melt together. For short sequences (< 100 base pairs) there is typically a single transition from a helical to random-coil state. Longer sequences may exhibit more complex melting behavior with multiple peaks, as domains of the DNA melt at different temperatures. The melting curve represents the average fractional helicity (Theta) at each temperature, and can be used for genotyping with high resolution melt analysis.

`MeltDNA`

can return three `type`

s of results: positional helicity, melting curves, or the negative derivative of the melting curves. If `type`

is `"position"`

, then a list is returned with one component for each sequence in `myDNAStringSet`

. Each list component contains a matrix with the probability of helicity (Theta) at each temperature (rows) and every position in the sequence (columns).

If `type`

is `"melt"`

, then a matrix with the average Theta across the entire sequence is returned. This matrix has a row for each input temperature (`temps`

), and a column for each sequence in `myDNAStringSet`

. For example, the value in element `[3, 4]`

is the average helicity of the fourth input sequence at the third input temperature. If `type`

is `"derivative"`

then the values in the matrix are the derivative of the melt curve at each temperature.

`MeltDNA`

uses nearest neighbor parameters from SantaLucia (1998).

Erik Wright [email protected]

SantaLucia, J. (1998). A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbor thermodynamics. Proceedings of the National Academy of Sciences, 95(4), 1460-1465.

Tostesen, E., et al. (2003). Speed-up of DNA melting algorithm with complete nearest neighbor properties. Biopolymers, 70(3), 364-376. doi:10.1002/bip.10495.

`AmplifyDNA`

, `CalculateEfficiencyPCR`

, `DesignSignatures`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ```
fas <- system.file("extdata", "IDH2.fas", package="DECIPHER")
dna <- readDNAStringSet(fas)
# plot the melt curve for the two alleles
temps <- seq(85, 100, 0.2)
m <- MeltDNA(dna,
type="melt", temps=temps, ions=0.1)
matplot(temps, m,
type="l", xlab="Temperature (\u00B0C)", ylab="Average Theta")
legend("topright", names(dna), lty=seq_along(dna), col=seq_along(dna))
# plot the negative derivative curve for a subsequence of the two alleles
temps <- seq(80, 95, 0.25)
m <- MeltDNA(subseq(dna, 492, 542),
type="derivative", temps=temps)
matplot(temps, m,
type="l", xlab="Temperature (\u00B0C)", ylab="-d(Theta)/dTemp")
legend("topright", names(dna), lty=seq_along(dna), col=seq_along(dna))
# plot the positional helicity profile for the IDH2 allele
temps <- seq(90.1, 90.5, 0.1)
m <- MeltDNA(dna[1],
type="position", temps=temps, ions=0.1)
matplot(seq_len(dim(m[[1]])[2]), t(m[[1]]),
type="l", xlab="Nucleotide Position", ylab="Theta")
temps <- formatC(temps, digits=1, format="f")
legend("topright", legend=paste(temps, "\u00B0C", sep=""),
col=seq_along(temps), lty=seq_along(temps), bg="white")
``` |

```
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, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colMeans, colSums, 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, rowMeans, rowSums, rownames, sapply,
setdiff, sort, table, tapply, union, unique, unsplit, which,
which.max, which.min
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
Loading required package: IRanges
Loading required package: XVector
Attaching package: 'Biostrings'
The following object is masked from 'package:base':
strsplit
Loading required package: RSQLite
```

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