Package data processing
This module provides managing classes and methods for the tool.
Feature
A Feature object represents a locus' feature (currently only CDS) and its properties.
Attributes:
-
feature_id
(str
) –Feature identifier.
-
feature_type
(str
) –Type of element (e.g. CDS or tRNA). Currently only CDS are supported.
-
start
(int
) –1-based start genomic coordinate.
-
end
(int
) –1-based end genomic coordinates
-
strand
(int
) –Genomic strand (1: plus strand, -1: minus strand).
-
name
(str
) –Name of the feature which will be used as a label.
-
sequence
(Seq
) –Feature's sequence.
-
record
(SeqRecord
) –SeqRecord object of corresponding feature sequence.
-
group
(str
) –Feature group that defines feature's colour and meant to represent a set of homologous features. Can be set with Loci.mmseqs_cluster() method that uses mmseqs clustering to define CDS feature groups.
-
group_type
(str
) –Type of feature group that allow to visualise different set of feature groups differently (e.g. plot labels only for features which group_type is "variable" or "labeled").
-
category
(str
) –Feature category which initially is built to handle phrogs category annotation. In visualisation it defines the "category" colour annotation under features. Supposed to represent clusters on locus or any second layer of feature properties.
-
vis_prms
(dict
) –Visualisation parameters that holds colours, label and other info for Drawing methods.
-
overlapping
(bool
) –Whether feature overlaps with visualised region or not.
-
prms
(Parameters
) –Parameters' class object that holds config and cmd arguments.
Source code in lovis4u/DataProcessing.py
__init__(feature_id, feature_type, start, end, strand, name, sequence, group, group_type, category, vis_prms, overlapping, parameters)
Create a Feature object.
Parameters:
-
feature_id
(str
) –Feature identifier.
-
feature_type
(str
) –Type of element (e.g. CDS or tRNA). Currently only CDS are supported.
-
start
(int
) –1-based start genomic coordinate.
-
end
(int
) –1-based end genomic coordinates
-
strand
(int
) –Genomic strand (1: plus strand, -1: minus strand).
-
name
(str
) –Name of the feature which will be used as a label.
-
sequence
(Seq
) –Feature's sequence.
-
group
(str
) –Feature group that defines feature's colour and meant to represent a set of homologous features. Can be set with Loci.mmseqs_cluster() method that uses mmseqs clustering to define CDS feature groups.
-
group_type
(str
) –Type of feature group that allow to visualise different set of feature groups differently (e.g. plot labels only for features which group_type is "variable" or "labeled").
-
category
(str
) –Feature category which initially is built to handle phrogs category annotation. In visualisation it defines the "category" colour annotation under features. Supposed to represent clusters on locus or any second layer of feature properties.
-
vis_prms
(dict
) –Visualisation parameters that holds colours, label and other info for Drawing methods.
-
prms
(Parameters
) –Parameters' class object that holds config and cmd arguments.
Source code in lovis4u/DataProcessing.py
Loci
A Loci object holds information about all loci to be plotted and methods for data preparation.
Attributes:
-
loci
(list
) –List of Locus objects.
-
locus_annotation
(DataFrame
) –Table with information about each locus that defines visualisation (e.g. coordinates for visualisation, description, etc).
-
feature_annotation
(DataFrame
) –Table with information about each feature that defines visualisation (e.g. group, name, category, etc).
-
prms
(Parameters
) –Parameters' class object that holds config and cmd arguments.
Source code in lovis4u/DataProcessing.py
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__init__(parameters=lovis4u.Manager.Parameters)
Create a Loci object.
Parameters:
-
parameters
(Parameters
, default:Parameters
) –Parameters' class object that holds config and cmd arguments.
Source code in lovis4u/DataProcessing.py
__load_annotation_file(file_path, annotation_columns, index_column)
Private method to load an annotation file.
Parameters:
-
file_path
(str
) –File path for an annotation file to be loaded.
-
annotation_columns
(list
) –List of columns that should be considered.
-
index_column
(str
) –Column name to be considered as index.
Returns:
-
DataFrame
–pd.DataFrame: Preprocessed annotation file.
Source code in lovis4u/DataProcessing.py
__update_feature_annotation(feature_id, locus_id, coordinates, feature_type, category, name)
Private method for updating feature annotation.
Parameters:
-
feature_id
(str
) –Feature identifier.
-
locus_id
(str
) –Sequence description.
-
coordinates
(str
) –Feature coordinates.
-
category
(str
) –Feature type.
-
name
(str
) –Feature name.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
__update_locus_annotation(record_id, record_description, record_length)
Private method for updating loci annotation.
Parameters:
-
record_id
(str
) –Sequence identifier.
-
record_description
(str
) –Sequence description.
-
record_length
(int
) –Sequence length.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
cluster_sequences(dataframe, one_cluster)
Define loci order and clusters with proteome similarity based hierarchical clustering. This function changes the order of loci that are plotted and also updates corresponding to each loci group attribute which defines homologues groups of proteomes.
It's designed to use as input mmseqs_cluster() function results. However, if you have obtained homologues groups by other method you can also build pandas dataframe based on that with index corresponding to feature id and column "cluster" corresponding to the group.
Parameters:
-
dataframe
(DataFrame
) –dataframe with feature id - group pairs. Its index column should represent all loci CDS features. one_cluster (bool): consider all sequences to be members of one cluster, but still define the optimal order.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
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define_feature_groups(dataframe, group_column_name='cluster')
Set features attribute "group" based on input dataframe.
By default is designed to use mmseqs_cluster() function results as input. If you already have precomputed feature groups you can set them with feature table.
Parameters:
-
dataframe
(DataFrame
) –dataframe with feature id - group pairs. Its index column should represent all loci CDS features.
-
group_column_name
(str
, default:'cluster'
) –column name of the dataframe that represent corresponding group to each feature.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
define_labels_to_be_shown()
Set feature visaulisation attribute "show_label" based on feature groups.
controlled by feature_labels_to_ignore, feature_group_types_to_show_label, and feature_group_types_to_show_label_on_first_occurrence parameters.
Returns:
-
–
None
Source code in lovis4u/DataProcessing.py
find_variable_feature_groups(mmseqs_results)
Define feature group type attributes (variable or conserved) based on their conservation in corresponding loci group feature.
It's designed to use as input mmseqs_cluster() function results. However, if you have obtained homologues groups by other method you can also build pandas dataframe based on that with index corresponding to feature id and column "cluster" corresponding to the group.
Parameters:
-
mmseqs_results
(DataFrame
) –dataframe with feature id - group pairs. Its index column should represent all loci CDS features.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
get_loci_lengths_and_n_of_regions()
Get loci lengths and number of regions.
Returns:
-
list
(list[list[int]]
) –list each element of each contains locus size and number of breaks for visualisation track.
Source code in lovis4u/DataProcessing.py
load_feature_annotation_file(file_path)
Load features annotation file.
Parameters:
-
file_path
(str
) –File path for a features annotation file to be loaded.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
load_loci_from_extended_gff(input_f, ilund4u_mode=False)
Load loci from the folder with gff files. Each GFF file also should contain corresponding nucleotide sequence. Such files are produced for example by pharokka annotation tool.
All files with extension other than .gff (not case-sensitive) will be ignored.
Parameters:
-
input_folder
–folder name with gff files.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
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load_loci_from_gb(input_folder)
Load loci from the folder with genbank files.
All files with extension other than .gb (not case-sensitive) will be ignored.
Parameters:
-
input_folder
(str
) –folder name with gb files.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
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load_locus_annotation_file(file_path)
Load loci annotation file.
Parameters:
-
file_path
(str
) –File path for a loci annotation file to be loaded.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
mmseqs_cluster()
Cluster all proteins using mmseqs in order to define groups of homologues.
Returns:
-
DataFrame
–pd.DataFrame: parsed mmseqs table (pandas dataframe) with columns: cluster, protein_id; where cluster is defined by representative sequence id within a corresponding cluster.
Source code in lovis4u/DataProcessing.py
remove_non_overlapping_features()
Removes features that are not overlapping with visualisation window.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
reorient_loci(ilund4u_mode=False)
Auto re-orient loci (reset strands) of loci if they are not matched.
Function tries to maximise co-orientation of homologous features.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
save_feature_annotation_table()
Save feature annotation table to the output folder.
Output file name is feature_annotation_table.tsv
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
save_locus_annotation_table()
Save loci annotation table to the output folder.
Output file name is locus_annotation_table.tsv
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
set_category_colours(use_table=True)
Define colours for each category.
Parameters:
-
use_table
(bool
, default:True
) –Bool value whether table with predefined colours should be used or not.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
set_feature_colours_based_on_groups()
Define features fill colour based on corresponding feature group and group types.
Returns:
-
None
–None
Source code in lovis4u/DataProcessing.py
Locus
A Locus object represents a particular locus that will be one of the sequence tracks on final figure.
Attributes:
-
seq_id
(str
) –Sequence identifier. Can be used to label locus.
-
coordinates
(list
) –List of regions to be shown. Each region format: dict with keys: start, end, strand and corresponding 1-based start, end coordinates and strand (1: plus strand, -1: minus strand).
-
size
(int
) –total length of regions to be plotted.
-
description
(str
) –Sequence description that can be used to label locus.
-
length
(int
) –full length of the locus independent on region that should be plotted.
-
circular
(bool
) –Bool value whether locus is circular or not. It defines whether you have gap or not passing 1 value on the final figure.
-
features
(list
) –list of Feature objects that overlapped with coordinates.
-
order
(int
) –index on ordered list of loci visualisation. Can be pre-defined or found based on loci hierarchical clustering with cluster_sequences category.
-
group
(int | str
) –locus group that defines set of closely-related loci.
-
category_colours
(dict
) –colours for locus' features categories.
-
prms
(Parameters
) –Parameters' class object that holds config and cmd arguments.
Source code in lovis4u/DataProcessing.py
__init__(seq_id, coordinates, description, length, circular, features, order, parameters, group=1)
Create a Locus object.
Parameters:
-
seq_id
(str
) –Sequence identifier. Can be used to label locus.
-
coordinates
(list
) –List of regions to be shown. Each region format: dict with keys: start, end, strand and corresponding 1-based start, end coordinates and strand (1: plus strand, -1: minus strand).
-
description
(str
) –Sequence description that can be used to label locus.
-
length
(int
) –full length of the locus independent on region that should be plotted.
-
circular
(bool
) –Bool value whether locus is circular or not. It defines whether you have gap or not passing 1 value on the final figure.
-
features
(list
) –list of Feature objects that overlapped with coordinates.
-
order
(int
) –index on ordered list of loci visualisation. Can be pre-defined or found based on loci
-
parameters
(Parameters
) –Parameters' class object that holds config and cmd arguments.
-
group
(int | str
, default:1
) –locus group that defines set of closely-related loci [1].