Note: This page has been translated by MathWorks. Please click here

To view all translated materials including this page, select Japan from the country navigator on the bottom of this page.

To view all translated materials including this page, select Japan from the country navigator on the bottom of this page.

Normalize set of signals with peaks

* Yout* = msnorm(

`X`

`Intensities`

[

`Yout`

`NormParameters`

msnorm(

`X`

`NewY`

`NormParameters`

msnorm(..., 'Quantile',

`QuantileValue`

msnorm(..., 'Limits',

`LimitsValue`

msnorm(..., 'Consensus',

`ConsensusValue`

msnorm(..., 'Method',

`MethodValue`

msnorm(..., 'Max',

`MaxValue`

`X` | Vector of separation-unit values for
a set of signals with peaks. The number of elements in the vector
equals the number of rows in the matrix .
The separation unit can quantify wavelength, frequency, distance,
time, or m/z depending on the instrument that generates the signal
data.`Intensities` |

`Intensities` | Matrix of intensity values for a set
of peaks that share the same separation-unit range. Each row corresponds
to a separation-unit value, and each column corresponds to either
a set of signals with peaks or a retention time. The number of rows
equals the number of elements in vector .`X` |

Use the following syntaxes with data from any separation technique that produces signal data, such as spectroscopy, NMR, electrophoresis, chromatography, or mass spectrometry.

normalizes
a group of signals with peaks by standardizing the area under the
curve (AUC) to the group median.* Yout* = msnorm(

`X`

`Intensities`

`[`

returns a structure containing the parameters
to normalize another group of signals.* Yout*,

`NormParameters`

`msnorm(`

uses
the parameter information from a previous normalization specified
by * X*,

`NewY`

`NormParameters`

`NormParameters`

`NewY`

`NormParameters`

`msnorm`

. If a consensus proportion, `ConsensusValue`

`msnorm(..., '`

calls * PropertyName*',

`PropertyValue`

`msnorm`

with optional properties
that use property name/property value pairs. You can specify one or
more properties in any order. Each `PropertyName`

```
msnorm(..., 'Quantile',
```

specifies a * QuantileValue*,
...)

`1`

-by-`2`

vector
with the quantile limits for reducing the set of separation-unit values
in `X`

`QuantileValue`

is ```
[0.9
1
```

], only the largest `10`

`%`

of
intensities in each signal are used to compute the AUC. When `QuantileValue`

is
a scalar, the scalar value represents the lower quantile limit and
the upper quantile limit is set to `1`

. The default
value is `[0 1]`

(use the whole area under the curve,
AUC).`msnorm(..., 'Limits', `

specifies a * LimitsValue*,
...)

`1`

-by-`2`

vector
with a separation-unit range for picking normalization points. This
parameter is useful to eliminate low-mass noise from the AUC calculation,
for example the matrix noise that appears in the low-mass region of
SELDI mass spectrometers. Default is `[0, max(``X`

)]

.`msnorm(..., 'Consensus', `

sets a consensus rule. To be included in the AUC,
a separation-unit position must have an intensity within the quantile
limits of at least part (specified by * ConsensusValue*,
...)

`ConsensusValue`

`Intensities`

`0`

to `1`

.Use the `'Consensus'`

property to eliminate
low-intensity peaks and noise from the normalization.

`msnorm(..., 'Method', `

selects a method for normalizing the AUC of every
signal. Enter either * MethodValue*,
...)

`'Median'`

(default) or `'Mean'`

.`msnorm(..., 'Max', `

, after individually normalizing each signal, scales
each signal to an overall maximum intensity specified by * MaxValue*,
...)

`MaxValue`

`MaxValue`

`QuantileValue`

```
[1
1]
```

, then a single point (peak height of the tallest peak)
is normalized to `MaxValue`

Was this topic helpful?