NDP {MetCirc} | R Documentation

## Calculate the normalised dot product

### Description

Calculate the normalised dot product (NDP)

### Usage

    NDP(matrow1, matrow2, m = 0.5, n = 2, mass)

### Arguments

`matrow1` | `character` or `numeric` vector, the entries correspond to the mass vector and contain corresponding intensities to the masses, it is the first feature to compare
`matrow2` | `character` or `numeric` vector, the entries correspond to the mass vector and contain corresponding intensities to the masses, it is the second feature to compare
`m` | `numeric`, exponent to calculate peak intensity-based weights
`n` | `numeric`, exponent to calculate peak intensity-based weights
`mass` | `character` or `numeric` vector, vector with all masses which occur in the data set

### Details

The NDP is calculated according to the following formula:

∑(W_{S1, i} \cdot W_{S2, i}) ^ 2 ∑(W_{S1, i} ^ 2) * ∑(W_{S2, i} ^ 2)

, with W = [ peak intensity] ^{m} \cdot [m/z]^n. For further information see Li et al. (2015): Navigating natural variation in herbivory-induced secondary metabolism in coyote tobacco populations using MS/MS structural analysis. PNAS, E4147–E4155. NDP returns a numeric value ranging between 0 and 1, where 0 indicates no similarity between the two MS/MS features, while 1 indicates that the MS/MS features are identical. For the calculation of the NDP only the elements of S1 and S2 that are not equal to 0 will be used.

### Value

NDP returns a numeric similarity coefficient between 0 and 1

### Author(s)

Thomas Naake, thomasnaake@googlemail.com

### Examples

    data("binnedMSP", package = "MetCirc")
    NDP(matrow1 = binnedMSP[1,], matrow2 = binnedMSP[2,], m = 0.5, n = 2,
     mass = colnames(binnedMSP))

[Package MetCirc version 1.10.0 Index]