rna_library.processing

Package Contents

Classes

JunctionData

Composite class that represents a collection of JunctionEntry objects in an experiment.

JunctionEntry

Represents a single junction entry from an RNA construct

Functions

process_histos

build_react_df(**kwargs)

Builds the reactivity dataframe from the supplied arguments. Here each row reprsents a construct.

build_motif_df(df)

Function that creates a motif dataframe from a reactivity dataframe. Here each row represents a Motif.

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

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

normalize_coeff_fit(reactivity_df)

class rna_library.processing.JunctionData(**kwargs)

Composite class that represents a collection of JunctionEntry objects in an experiment.

get_active_data(self)
rebuild_data(self)

Method that rebuilds the internal data representation from the JunctionEntry objects.

Return type

NoneType

is_symmetrical(self)

Getter that tells if the current JunctionData object models a symmetrical junction. :rtype: bool

plot(self, plot_dir, overwrite=False)

Method that saves a plot of the JunctionData’s data points to the supplied directory.

Param

str plot_dir: The directory where the plot will be saved. Does not have to exist.

Return type

NoneType

Parameters

plot_dir (str) –

show(self)

Method that brings up a plot of the JunctionData’s data points

Return type

NoneType

bind(self, ax)

Method that binds the JunctionData points to a supplied matplotlib Axes object.

Param

matplotlib.axes.Axes ax: the Axes object which the plot will be bound to

Return type

NoneType

Parameters

ax (matplotlib.axes.Axes) –

measure_variance(self)
Return type

Dict[str, float]

class rna_library.processing.JunctionEntry(**kwargs)

Represents a single junction entry from an RNA construct

validate_arguments_(self)

Helper method that validates arguments in the constructor.

key(self)

Getter that accesses the (sequence, structure) key for the JunctionEntry

Return type

Tuple[str,str]

is_symmetrical(self)

Getter that checks if the JunctionEntry is for a symmetrical unction.

Return type

bool

__getitem__(self, idx)
Parameters

idx (int) –

Return type

float

rna_library.processing.process_histos(mut_hist_file, output_directory, remove_html=True)

Processes a mutational histogram file generated by dreem.

Param

str mut_hist_file: path to the mutational histogram file

Param

str output_directory: the output directory for the analysis files

Param

bool remove_html: flag to remove .html files generated by DREEM, defaults to True

Parameters

  • mut_hist_file (str) –

  • output_directory (str) –

  • remove_html (bool) –

Return type

None

rna_library.processing.build_react_df(**kwargs)
Builds the reactivity dataframe from the supplied arguments. Here each row reprsents a construct.

Note that all arguments are supplied as kwargs.

Params

str out_dir: base output directory where rna_library.process_histos was called :params: str start_seq: common start sequence for the RNA constructs

Params

str end_seq: common end sequence for the RNA constructs

Params

str fasta_file: path to the fast file for the construct

Params

str histos_file: path to histogram file from DREEM analysis :rtype: pd.DataFrame

Return type

pandas.DataFrame

rna_library.processing.build_motif_df(df)

Function that creates a motif dataframe from a reactivity dataframe. Here each row represents a Motif.

Param

pd.DataFrame df: reactivity dataframe which is generated from build_react_df() :rtype: pd.DataFrame

Parameters

df (pandas.DataFrame) –

Return type

pandas.DataFrame

rna_library.processing.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]]

rna_library.processing.normalize_coeff_fit(reactivity_df)