06: Use custom color palette for plotting

Pick a plotly color palette of your chosing or your own custom color palette to color transcript structure and expression

import RNApysoforms as RNApy
import polars as pl
import plotly.express as px

## Path to your ENSEMBL GTF file, counts matrix file, and metadata file
ensembl_gtf_path = "../dash_apps/RNApysoforms/tests/test_data/Homo_sapiens_chr21_and_Y.GRCh38.110.gtf"
counts_matrix_path = "../dash_apps/RNApysoforms/tests/test_data/counts_matrix_chr21_and_Y.tsv"
metadata_path = "../dash_apps/RNApysoforms/tests/test_data/sample_metadata.tsv"


## Read ENSEMBL GTF and counts matrix with metadata and normalizations
annotation = RNApy.read_ensembl_gtf(ensembl_gtf_path)
counts_matrix = RNApy.read_expression_matrix(expression_matrix_path=counts_matrix_path,
                                          metadata_path=metadata_path,
                                           cpm_normalization=True, relative_abundance=True)


## Filter APP gene and do not filter RNA isoforms by expression
app_annotation, app_expression_matrix = RNApy.gene_filtering(annotation=annotation, expression_matrix=counts_matrix, target_gene="APP",
                                                        order_by_expression=True, keep_top_expressed_transcripts=5,
                                                        order_by_expression_column="counts")


# Rescale introns
app_annotation = RNApy.shorten_gaps(app_annotation)


"""
Create traces, notice the `annotation_color_palette` and the
`expression_color_palette` being passed to define the color palettes
for the RNA isoform structure and RNA isoform expression plots
"""
traces = RNApy.make_traces(annotation=app_annotation,  expression_matrix=app_expression_matrix,
                        x_start="rescaled_start", x_end="rescaled_end",
                         y='transcript_id', annotation_hue="transcript_biotype",
                         hover_start="start", hover_end="end",
                         expression_columns=["counts", "CPM", "relative_abundance"],
                         expression_hue="AD status", marker_size=3, arrow_size=7,
                         annotation_color_palette=px.colors.qualitative.Dark2,
                         expression_color_palette=["red", "blue"])

## Put traces into a figure
fig = RNApy.make_plot(traces=traces, subplot_titles=["Transcript Structure", "Counts", "CPM", "Relative Abundance"],
                   width=1200, height=500)

## Show figure
fig.show()