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Smoother

MassSpectInKnime2 version 1.0.1

We use this to denoise inherently noisy MSI datasets, from a choice of 3 different smoothing methods. The smoothing methods supported are Savitzky-Golay, Moving Mean, and Triangular Moving Mean. Once a spectrum is smoothed, we remove negaitves so that all negative values are equal to zero.

Options

Smoothing Method

Savitzky-Golay
If chosen, the intensity of a spectrum will be smoothed using Savitzky-Golay smoothing. This is the industry standard or smoothing in MSI.
Moving Mean
If chosen, the intensity of a spectrum will be smoothed using the Moving Mean.
Triangular Moving Mean
If chosen, the intensity of a spectrum will be smoothed using the Triangular Moving Mean.

Input Ports

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The incoming data should contain rows spectra m/z values.
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The incoming data should contain rows spectra intensity values.

Output Ports

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The outgoing data is exactly equal to the incoming rows of spectra m/z values from incoming port 0.
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The outgoing data consists of the rows of smoothed spectra Intensity values.

Installation

To use this node in KNIME, download the below referenced file, save it to your KNIME's plugin folder and restart KNIME.

KNIME 4.3

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Developers

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