sugar.imaging package

sugar.imaging – Plotting alignments

sugar.imaging.alignment.plot_alignment(seqs, fname=None, *, ax=None, figsize=None, extent=None, aspect=None, gap='- ', color='gray', gap_color='white', symbols=False, symbol_color='black', symbol_gap_color='black', symbol_size=None, scale_symbol_size=1, symbol_kw=None, fts=None, fts_display='facecolor', fts_colorby='type', fts_color=None, fts_color_gap_alpha=1, fts_alpha=None, fts_box_groups='type', fts_box_lw=5, fts_box_kw=None, show_spines=False, spine_offset=None, xticks=True, dpi=None, transparent=None, bbox_inches=None, show=False, **kw)

Plot an alignment

Parameters:

• seqs – sequences

• fname – The filename if saving the plot, the figure will be closed afterwards, default: do not save the plot and return figure

• ax – The ax to plot in, default: create a new ax

• figsize – The size of the created figure, only applies for ax=None

• extent – The extent of the plotted alignment in data coordinates [xmin, xmax, ymin, ymax], the default plots each symbol and sequence at integer coordinates

• aspect – Wether to shrink the axis to guarantee the given aspect ratio, default no shrinkage, aspect=2 gives visually appealing plots if symbols are also plotted.

• gap – The characters recognized as gaps, default is '- '

• color – The background color, might be any constant color (defaults to 'gray'), a list of colors, or None for the default matplotlib color cycle, a dictionary mapping the alphabet to colors, or a supported color scheme, see get_color_scheme(), e.g. 'flower'.

• gap_color – The color of gaps, default is 'white'

• symbols – Wether to plot symbols (letters), default False

• symbol_color – The color of the symbols, takes the same values as the color parameter, default is 'black'

• symbol_gap_color – the color of the gap symbol, default is 'black'

• symbol_size – The font size of the symbols, by default a visually appealing size is calculated

• scale_symbol_size – Scale factor for the automatically calculated symbol size, default is 1

• symbol_kw – A dictionary of additional parameters passed to matplotlib’s annotate()

• fts – Wether to highlight features, defaults to no highlighting, might be a FeatureList object or just True to use the features which are attached to the sequences object.

• fts_display – How to display the features, one of 'facecolor' (default) and 'box', boxes will range over all sequences

• fts_colorby – How to define the color of the features, might be any key in the metadata, defaults to 'type', but can also be a function taking a Feature and returning an identifier

• fts_color – The color of the features, similarly as with the color parameter, this might be a constant color, a list of colors, or None for the default matplotlib color cycle (the default), or a dictionary mapping the feature identifiers to colors.

• fts_color_gap_alpha – The alpha value of the feature color for gaps (default: 1)

• fts_alpha – Transparency of the features

• fts_box_groups – For the fts_display='box' option, we need to specify which features belong into the same box, this parameter can be a list of FeatureList objects, alternatively this parameter is passed to FeatureList.groupby() to define the groups, defaults to 'type'

• fts_box_lw – linewidth of the the boxes, default: 5

• fts_box_kw – Dictionary of additional parameters passed to matplotlib’s Rectangle to create the feature boxes

• show_spines,despine_offset – Parameters passed to seaborn’s despine function, the default show_spines=False removes axes spines

• xticks – True leaves the xticks (default), False turns them off, can also be a list of xticks

• dpi,transparent,bbox_inches – Parameters passed to savefig() if the figure is saved

• show – True shows the figure, default: False

• **kw – Other kwargs are passed to matplotlib’s pcolormesh()

Returns:

Axes object if fname=None, otherwise the figure is saved and closed

Example

>>> from sugar import read
>>> seqs = read('https://osf.io/download/j2wyv')
>>> seqs.plot_alignment(show=True, figsize=(10, 4))

>>> seqs[:, 70:120].plot_alignment(show=True, color=None, figsize=(10,8),
...                                symbols=True, aspect=2, alpha=0.5)

>>> seqs2 = seqs[:5, :150].copy()
>>> seqs2.translate(complete=True).plot_alignment(
...     show=True, color='flower', figsize=(10,8),  symbols=True,
...     aspect=2, alpha=0.5, edgecolors='w')

sugar.imaging.ftsviewer.plot_ftsviewer(fts: FeatureList, fname=None, *, seqs=None, groupby='seqid', align=None, crop=False, figsize=None, ncols=1, sharex=False, sharey=False, fig_kw={}, ax=None, xticks=False, axlabel=True, axlabel_kw={}, same_colors=True, colorby='type', color=None, dpi=None, transparent=None, bbox_inches=None, show=False, seqlen=None, first_index=None, **kw)

Plot features using DNAFeaturesViewer and toftsviewer()

Parameters:

• fts – features

• fname – The filename if saving the plot, the figure will be closed afterwards, default: do not save the plot and return figure

• seqs – The corresponding sequences, instance of BioBasket, will be used to extract the length of each sequence, they are also needed when the plot_sequence option is used.

• groupby – Features are grouped by this key, see groupby(), and each group is plotted in a separate ax, defaults to 'seqid'.

• align – Align features by this method or list of features, can be one of the strings 'center', 'first', 'last', or a list or BioBasket of features to align each group to the the first found feature in the list. By default no alignment is done. If align is used, you should set sharex=True.

• crop – If align is used, crop the sequence lines to the first and last feature in each group, can be True to crop to the minimal region including all features, or an integer to add some extra space before the first features.

• figsize – The size of the created figure, by default a reasonable value is calculated with (6 * ncols, 2 * nrows), has to be tuned for non-usual cases.

• ncols – Number of columns in the figure, by default all groups are plotted in a single column

• sharex,sharey – parameters passed to plt.subplots

• fig_kw – dict of other parameters passed to plt.subplots

• ax – Instead of specifying the figure with figsize, etc. one may pass an axes instance to draw the annotation in, make sure to only have a single annotation group

• axlabel – Plot the name of each group in the axis, default: True

• axlabel_kw – Dict of corresponding options passed to annotate()

• same_colors – Wether to use the same color mapping in all subplots, default True.

• dpi,transparent,bbox_inches – Parameters passed to savefig() if the figure is saved

• show – True shows the figure, default: False

• seqlen – Can be used to set the sequence length if not using seqs.

• first_index – Can be used to set the sequence start index (where the line representing the sequence starts), for aligned features this is determined automatically. If the parameter is set, it overrides the automatic detection. Can be either an int or a dict mapping group keys to first indices.

• **kw – Other kwargs are passed to toftsviewer(), GraphicFeature or GraphicRecord or CircularGraphicRecord, and GraphicRecord.plot().

Returns:

Figure object if fname=None, otherwise the figure is saved and closed

Example

>>> from sugar import read
>>> seqs = read()
>>> seqs.plot_ftsviewer()

sugar.imaging.colors.get_color_scheme(name)

Return color scheme

Parameters:

name – Name of the color scheme, the following color schemes are supported out of the box: autumn, blossom, buried, clustalx, clustalx_nt, flower, hydrophobicity, ocean, prophelix, propstrand, propturn, rainbow, rainbow_nt, spring, sunset, taylor, wither, zappo. These color schemes originate from Biotite (Gecos), Jalview and ClustalX, see here for a description. Alternatively, a JSON file, as generated by the Gecos library can be specified. A colors entry with a letter->color mapping in the JSON file is sufficient.

Returns:

Dictionary with letter->color mapping