rstoolbox.analysis.positional_structural_identity¶

rstoolbox.analysis.positional_structural_identity(df, seqID=None, ref_sse=None, key_residues=None)¶

Per position evaluation of how many times the provided data matches the expected reference_structure.

Parameters:

df (Union[DesignFrame, FragmentFrame]) – Data container.
seqID (str) – Identifier of the sequence of interest. Required when input is DesignFrame
ref_sse (str) – Reference sequence. Required when input is FragmentFrame. Will overwrite the reference sequence of DesignFrame if provided.
key_residues (Union[int, list() of int, str, Selection]) – Residues of interest.

Returns:

DataFrame - where rows are sequence positions and columns are sse (expected secondary structure), max_sse (most represented secondary structure) and identity_perc (percentage of matched secondary structure).

Raises:

AttributeError:	if the data passed is not in Union[`DesignFrame`, `FragmentFrame`]. It will not try to cast a provided `DataFrame`, as it would not be possible to know into which of the two possible inputs it needs to be casted.
AttributeError:	if input is `DesignFrame` and `seqID` is not provided.
KeyError:	if there is no structure information for chain `seqID` of the decoys when input is `DesignFrame`.
AttributeError:	if input is `FragmentFrame` and `ref_sse` is not provided.

Example

In [1]: from rstoolbox.io import parse_rosetta_file
   ...: from rstoolbox.analysis import positional_structural_identity
   ...: import pandas as pd
   ...: pd.set_option('display.width', 1000)
   ...: pd.set_option('display.max_columns', 500)
   ...: df = parse_rosetta_file("../rstoolbox/tests/data/input_ssebig.minisilent.gz",
   ...:                         {'scores': ['score'], 'structure': 'C'})
   ...: df.add_reference_structure('C', df.get_structure('C').values[0])
   ...: df = positional_structural_identity(df.iloc[1:], 'C')
   ...: df.head()
   ...: 
Out[1]: 
  sse max_sse  identity_perc
1  L   L       1.000000     
2  E   E       0.212389     
3  E   E       0.985841     
4  E   E       1.000000     
5  E   E       1.000000     