rnanorm.TPM

class rnanorm.TPM(gtf=None, gene_lengths=None)

Transcripts per kilo-base million (TPM) normalization.

Examples

>>> from rnanorm.datasets import load_toy_data
>>> from rnanorm import TPM
>>> dataset = load_toy_data()
>>> dataset.exp
          Gene_1  Gene_2  Gene_3  Gene_4  Gene_5
Sample_1     200     300     500    2000    7000
Sample_2     400     600    1000    4000   14000
Sample_3     200     300     500    2000   17000
Sample_4     200     300     500    2000    2000
>>> tpm = TPM(gtf=dataset.gtf_path).set_output(transform="pandas")
>>> tpm.fit_transform(dataset.exp)
             Gene_1     Gene_2     Gene_3     Gene_4     Gene_5
Sample_1   83333.33   83333.33   83333.33  166666.66  583333.33
Sample_2   83333.33   83333.33   83333.33  166666.66  583333.33
Sample_3   45454.54   45454.54   45454.54   90909.09  772727.27
Sample_4  142857.14  142857.14  142857.14  285714.28  285714.28

__init__(gtf=None, gene_lengths=None)

Initialize class.

Methods

__init__([gtf, gene_lengths])	Initialize class.
fit(X[, y])	Fit transformer by checking X.
fit_transform(X[, y])	Fit to data, then transform it.
get_feature_names_out([input_features])	Get output feature names for transformation.
get_metadata_routing()	Get metadata routing of this object.
get_params([deep])	Get parameters for this estimator.
inverse_transform(X)	Transform X using the inverse function.
set_output(*[, transform])	Set output container.
set_params(**params)	Set the parameters of this estimator.
transform(X)	Transform X using the forward function.