rstoolbox.components.FragmentFrame(*args, **kw)¶Data container for Fragment data.
Extends pandas.DataFrame adding some functionalities in order
to facilitate analysis, plotting and comparisson.
Filled through the functions provided through this library, each row represents a position of a fragment, while columns describe the properties.
. rubric:: Example
In [1]: from rstoolbox.io import parse_rosetta_fragments
...: import pandas as pd
...: pd.set_option('display.width', 1000)
...: pd.set_option('display.max_columns', 500)
...: df = parse_rosetta_fragments("../rstoolbox/tests/data/wauto.200.3mers.gz")
...: df.head()
...:
Out[1]:
pdb frame neighbors neighbor position size aa sse phi psi omega
0 2hox 1 200 1 1 3 S L -154.974 117.297 176.201
1 2hox 1 200 1 2 3 E E -133.145 153.460 177.064
2 2hox 1 200 1 3 3 Y E -77.588 132.516 177.184
3 1ihu 1 200 2 1 3 I L -60.621 119.545 -179.669
4 1ihu 1 200 2 2 3 Q E -130.878 145.002 -179.783
Methods
add_quality_measure(filename[, pdbfile]) |
Add RMSD quality measure to the fragment data. |
add_source_file(file) |
Adds a source file to the FragmentFrame. |
has_source_file() |
Checks if there is a source file added. |
slice_region(ini, end) |
Retrieve only fragments within certain positions. |
top_limit(limit) |
Remove all frames whose position puts the frames over a given limit. |
is_comparable(df) |
Evaluate if the current FragmentFrame is comparable to the provided one. |
renumber([ini]) |
Make the fragment set start at the given position. |
sample_top_neighbors([max_count]) |
Limit to the top selected neighbors for each frame. |
coerce() |
Make fragment data coherent. |
order() |
Properly reorder the FragmentFrame. |
add_fragments(fragments, ini[, how]) |
Add to a given position a set of fragments more fragments. |
renumber([ini]) |
Make the fragment set start at the given position. |
sample_top_neighbors([max_count]) |
Limit to the top selected neighbors for each frame. |
select_quantile([quantile]) |
Returns fragments under the rmsd threshold of the specified uantile. |
make_sequence_matrix([frequency, round_data]) |
Generate a PSSM-like matrix from the fragments. |
make_per_position_frequency_network() |
Generate a graph representation of the per-residue frequency. |
make_frequency_network([use_rmsd]) |
Generate a graph with per-position frequency between residue types at each position. |
quick_consensus_sequence() |
Consensus sequence with the highest representative per position. |
quick_consensus_secondary_structure() |
Consensus secondary structure with the highest representative per position. |