itpseq.Sample.subset_logo

Sample.subset_logo(pos, *, how='aax', query='', motif=None, logo_type='extra_counts_bits', ax=None, logo_kwargs=None, return_matrix=False, **kwargs)

Creates a logo from a subset of the Differential Expression data.

This first runs the DE method with pos, then uses the query and motif parameters to filter the output, and uses the filtered table to produce a logo. Each motif is weighted using the average normalized counts from get_counts_ratio.

Parameters:

• pos (str) – Ribosome positions to consider to compute the differential expression. Passed to DE.

• how (str, optional) – Type of inverse toeprints to analyze (see Replicate.load_data).

• query (str, optional) – Query used to select rows in the DE output.

• motif (regex, optional) – Regex used to select motifs (e.g., ‘.QK.’ in a 4 amino-acid motif would fix the central QK).

• logo_type (str, optional) –

  Type of logo to compute:

  • ”raw_freq”: unweighted frequencies of the amino-acids for all present motifs

  • ”extra_counts”: Computes the sum of extra counts (sample - reference) for each residue per position

  • ”sum_log2FC”: sum of the log2FoldChange for each residue per position

  • ”<logo_type>_bits”: If any of the above has a “_bits” suffix, an extra conversion to bits is performed.

• ax (matplotlib Axes, optional) – If passed, the figure will be drawn on the given Axes. A new Axes is created otherwise.

• logo_kwargs (dict, optional) – Additional parameters passed to logomaker.Logo.

• return_matrix (bool, optional) – If True, the logo matrix is returned as together with the logo as (logo, matrix).

• kwargs (optional) – Additional parameters passed to the DE method.

Return type:

logomaker.Logo

Examples

>>> sample.subset_logo('-2:A', query='(log2FoldChange > 2) & (log10pvalue > 2)')