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biodataplot is a package that provides various useful biological plotting functions using matplotlib.

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biodataplot - A standard biological data plot package

biodataplot is a package that provides various useful biological plotting functions using matplotlib.

Installation

pip install biodataplot

biodataplot

biodataplot contains different modules that serve different purposes. The common module includes general plotting functions (not biology-related). The utils module includes some plot utility functions. Other modules are related to certain biological area.

In biodataplot, the plot functions could be separated into two types. The first type works on a matplotlib axes Object and return the artists. The second type works on a figure and return the matplotlib figure itself. Some functions may require additional packages.

common

A module with general plotting functions.

plot_fast_bar

An alternative bar plotting using fill_between. This allows quick plot on many bars (10000+) but with less customization available.

plot_ranked_values

genomeview

The genomeview contains the plot_genome_view function, which draws browser snapshot on certain regions.

import biodataplot.genomeview as gv
gv.plot_genome_view(r, data)
gv.plot_genome_view(r, data, formatters=formatters, height_ratios=height_ratios)
  • rs: Region(s) to be plotted. It could be a single string chr1:1-1000, a GenomicAnnotation instance, or a list with string or GenomicAnnotation as elements.
  • data: A dictionary of data to be plotted
  • formatters: A dictionary of formatter. Other than datatype and tracktype, formatters are unique for different track types. On could find more details in the track section.
  • height_ratios: A dictionary of relative track heights. The default height of track is 3.
  • group_autoscales: A list of list that indicates the tracks to be put in groups.
  • scalebar_kw: If None, no scalebar is drawn.
  • coordinate_kw: If None, no coordinate ruler is drawn

Data

Users could input the data as a dictionary of file(s)

data={"Signal":"signal.bw", "Anno1":"anno1.bed"}

All supported file / data types:

  • bigwig (signal)
  • bedgraph (signal, arc, annotation, default to annotation if not specified)
  • bed (annotation)
  • gff3 / gtf (annotation)
  • fasta (nucleotide_density)

biodataplot will automatically look for any index file whenever applicable. Without an index file, it may take a long time for biodataplot to load big data files. For certain data types, multiple track types could be used. In such case, one may want to specify the tracktype in the formatters:

data={"Signal":"signal.bedgraph"}
formatters={"Signal":{"tracktype":"signal"}}

Tracks

There are 4 types of tracks supported. Each track has its specific options used in formatters.

Signal

In signal plotting, either bigwig or bedgraph files are supported.

  • vmod: Modify the values in the signal before plotting.
  • density: If specified, plot a smoothed signals on the same graph. {"winsize":100}
  • trackstyle: Two track styles are support: either bar or heatmap
  • trackstyle: bar
    • pcolor: Color for positive signals
    • ncolor: Color for negative signals
    • plot_kw: Customized parameters used in plot_fast_bar
  • trackstyle: heatmap
    • plot_kw: Customized parameters used in imshow
  • fixed_ymin_ymax: Fix ymin, ymax as the input
  • yscale: Either asym_pos_neg or same_ymin_ymax. These alternative yscales are useful when dealing with both positive and negative signals.
Arc
  • min_signal: Minimum signal cutoff to draw the arc
Annotation
  • filter_func: A filtering function to retain annotations that pass this filter
  • anno_height: Annotation height
  • anno_vspace: Vertical space between two annotations
  • plot_kw: Customized parameters used in matplotlib.patches.Rectangle
  • anno_name: A function f(anno) that returns a string to display. Otherwise, the anno_name is automatically determined.
Nucleotide_density
  • winsize The window size for nucleotide density. Only ACGT are supported in the density plot. All other nucleotides are ignored.
  • plot_kw_dict: A dictionary of customized parameters used in plot. The dictionary keys should be in [A, C, G, T].

metaplot

This module is under testing.

sequence

plot_sequence_layout

utils

A module with useful plot utilities.

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biodataplot is a package that provides various useful biological plotting functions using matplotlib.

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