Tracks for numerical signals#

Dynamic values#

class pygv.tracks.track.DynamicValueTrack(track: str = '', **kwargs)#

While other tracks load signal values from external files, DynamicValueTrack allows you to show the numerical values directly from your code. Track values should be assigned via the values property.

Parameters:

  • track (str) – Placeholder

  • kwargs

Raises:

ValueError will be raised if the len the values property is not equal to the span of plotting region as defined as end - start –

Examples

(Source code, png, pdf)

_images/plot_dyn_track.png

bigWig#

class pygv.tracks.bigwig_track.BigWigTrack(track: str, plot_type: str = 'line', **kwargs)#

Generic BigWig track

Examples

(Source code, png, pdf)

_images/plot_bigwig.png
class pygv.tracks.bigwig_track.OverlayingTrack(tracks, labels, palette='Set1', colors=None, legend=True, legend_kws=None, **kwargs)#

Overlay BigWig tracks (signals from multiple BigWig files in the same track) in a single track

Parameters:

  • tracks (list of str or tuple[str, ...]) – List of file paths or urls. Tracks will be organized with ascending zorder.

  • labels (list of str or tuple[str, ...]) – Labels for each bigwig file

  • palette (str or palette instances) – Name of the palette you want to use. Matplot colormaps / seaborn palettes

  • colors (list of colors or None) – List of colors you want to use. If it’s None, then colors will be extracted from palette.

  • legend (bool) – Enable/disable legends

  • legend_kws (dict, optional) – Keyword arguments passed to matplotlib legend.

Examples

(Source code, png, pdf)

_images/plot_overlaying_bigwigs.png
property colors#

Colors for each bigwig file

property labels#

Labels for each bigwig file

class pygv.tracks.bigwig_track.PairedStrandSpecificTrack(pl_track, mn_track, draw_y_independently=True, plot_type: str = 'line', **kwargs)#

Paired strand-specific tracks

Parameters:

  • pl_track (str or list[str]) – File path(s) or url(s) for the positive track. When multiple tracks are provided, the mean values will be used.

  • mn_track (str or list[str]) – File path(s) or url(s) for the negative track. When multiple tracks are provided, the mean values will be used.

  • draw_y_independently (bool) – By default, True, which means the output track centers at zero and the positive and negatives axis have identical lengths regardless to their ranges. Set it as False if you want the y-axis to reflect the dominance of signals on a strand.

  • plot_type (str) – “line”: line plot “bar”: bar plot

  • pos_color (color_like) – Color for positive signals, by default, #E10600

  • neg_color (color_like) – Color for negative signals, by default, #0048AC

  • kwargs

Examples

(Source code, png, pdf)

_images/plot_paired_strand_specific_bigwigs.png
property neg_color#

Color for negative signals

property pos_color#

Color for negative signals

class pygv.tracks.bigwig_track.PairedStrandSpecificTracks(pl_track, mn_track, draw_y_independently=True, plot_type: str = 'line', **kwargs)#
class pygv.tracks.bigwig_track.PairedStrandlessTrack(pl_track, mn_track, plot_type: str = 'line', **kwargs)#

Paired strandless tracks

Parameters:

  • pl_track (str or list[str]) – File path(s) or url(s) for the positive track. When multiple tracks are provided, the mean values will be used.

  • mn_track (str or list[str]) – File path(s) or url(s) for the negative track. When multiple tracks are provided, the mean values will be used.

  • plot_type (str) – “line”: line plot “bar”: bar plot

  • kwargs

Examples

(Source code, png, pdf)

_images/plot_paired_strandless_bigwigs.png