rna_library.processing.normalize

Tools for normalizing reactivity

Module Contents

Functions

normalize_hairpin(df, seq, ss, **kwargs)

Normalizes a reactivity pattern to a normalization hairpin. Creates fully normalize values

normalize_coeff_fit(reactivity_df)

Attributes

NormJob

rna_library.processing.normalize.normalize_hairpin(df, seq, ss, **kwargs)

Normalizes a reactivity pattern to a normalization hairpin. Creates fully normalize values for an entire pd.DataFrame

Param

pd.DataFrame df: reactivity_df created from rna_library.build_react_df

Param

str seq: reference hairpin sequence

Param

str ss: reference hairpin structure

Param

float factor: factor to set the hairpin values to, is a keyword argument

Param

str nts: string of nucleotide’s to be used for calc, is a keywrod argument

Parameters

  • df (pandas.DataFrame) –

  • seq (str) –

  • ss (str) –

Return type

List[List[float]]

class rna_library.processing.normalize.OptimizeJunction(sequence, n_data)
add_data(self, row, data_idx)
spread(self, how)
rna_library.processing.normalize.NormJob
rna_library.processing.normalize.normalize_coeff_fit(reactivity_df)