API reference / NMR and preprocessing

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metbit.spec_norm

NMR and preprocessing module in metbit 7.3.0.

import metbit.spec_norm

Classes

Normalization

A class for performing various normalization methods, including Probabilistic Quotient Normalization (PQN), Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), and their combinations.

Methods:

pqn_normalization(df): Applies Probabilistic Quotient Normalization (PQN) to the input dataframe.

snv_normalization(df): Applies Standard Normal Variate (SNV) normalization to the input dataframe.

msc_normalization(df): Applies Multiplicative Scatter Correction (MSC) normalization to the input dataframe.

snv_msc_normalization(df): Applies SNV followed by MSC normalization to the input dataframe.

snv_pqn_normalization(df): Applies SNV followed by PQN normalization to the input dataframe.

snv_msc_pqn_normalization(df): Applies SNV followed by MSC and then PQN normalization to the input dataframe.

Methods

__init__(self)

Initializes the Normalization class.

pqn_normalization(df)

Perform Probabilistic Quotient Normalization (PQN) on a dataframe.

Parameters:

dfpandas.DataFrame or numpy.ndarray

The input data to normalize. Each column represents a feature.

Returns:

df_normpandas.DataFrame

The PQN normalized dataframe.

Raises:

TypeError: If input is not a pandas DataFrame or cannot be converted to one.

snv_normalization(df)

Apply Standard Normal Variate (SNV) normalization to a dataframe.

Parameters:

dfpandas.DataFrame or numpy.ndarray

The input data to normalize. Each column represents a feature.

Returns:

df_normpandas.DataFrame

The SNV normalized dataframe.

Raises:

TypeError: If input is not a pandas DataFrame or cannot be converted to one.

msc_normalization(df)

Apply Multiplicative Scatter Correction (MSC) normalization to a dataframe.

Parameters:

dfpandas.DataFrame or numpy.ndarray

The input data to normalize. Each column represents a feature.

Returns:

df_normpandas.DataFrame

The MSC normalized dataframe.

Raises:

TypeError: If input is not a pandas DataFrame or cannot be converted to one.

snv_msc_normalization(df)

Apply SNV followed by MSC normalization to a dataframe.

Parameters:

dfpandas.DataFrame or numpy.ndarray

The input data to normalize. Each column represents a feature.

Returns:

df_normpandas.DataFrame

The SNV-MSC normalized dataframe.

Raises:

TypeError: If input is not a pandas DataFrame or cannot be converted to one.

snv_pqn_normalization(df)

Apply SNV followed by PQN normalization to a dataframe.

Parameters:

dfpandas.DataFrame or numpy.ndarray

The input data to normalize. Each column represents a feature.

Returns:

df_normpandas.DataFrame

The SNV-PQN normalized dataframe.

Raises:

TypeError: If input is not a pandas DataFrame or cannot be converted to one.

snv_msc_pqn_normalization(df)

Apply SNV followed by MSC and then PQN normalization to a dataframe.

Parameters:

dfpandas.DataFrame or numpy.ndarray

The input data to normalize. Each column represents a feature.

Returns:

df_normpandas.DataFrame

The SNV-MSC-PQN normalized dataframe.

Raises:

TypeError: If input is not a pandas DataFrame or cannot be converted to one. ValueError: If an error occurs during the normalization process.

Source

metbit/spec_norm.py at v7.3.0