.. This document is auto-generated by the gosling-gallery extension. Do not modify directly.

.. _gallery_corces:

Single-cell Epigenomic Analysis
===============================

`Corces et al. 2020`_

.. _Corces et al. 2020: https://www.nature.com/articles/s41588-020-00721-x

.. gosling-plot::
    :code-below:

    
    import gosling as gos

    WIDTH = 600

    # DATA

    cytogenetic_band = gos.csv(
        url="https://raw.githubusercontent.com/sehilyi/gemini-datasets/master/data/cytogenetic_band.csv",
        chromosomeField="Chr.",
        genomicFields=["ISCN_start", "ISCN_stop", "Basepair_start", "Basepair_stop"],
    )

    gene_anno = gos.beddb(
        url="https://server.gosling-lang.org/api/v1/tileset_info/?d=gene-annotation",
        genomicFields=[{"index": 1, "name": "start"}, {"index": 2, "name": "end"}],
        valueFields=[
            {"index": 5, "name": "strand", "type": "nominal"},
            {"index": 3, "name": "name", "type": "nominal"}
        ],
        exonIntervalFields=[{"index": 12, "name": "start"}, {"index": 13, "name": "end"}],
    )

    # TRACKS

    ideo_base = gos.Track(cytogenetic_band).mark_rect(outlineWidth=1).encode(
        x=gos.X("Basepair_start:G", axis="none"),
        xe="Basepair_stop:G",
        stroke=gos.value("black"),
        strokeWidth=gos.value(1),
    )

    ideogram = gos.overlay(
        ideo_base.encode(
            color=gos.Color("Density:N",
                domain=["", "25", "50", "75", "100"],
                range=["white", "#D9D9D9", "#979797", "#636363", "black"]
            ),
            size=gos.value(20),
        ).transform_filter_not("Stain", oneOf=["acen-1", "acen-2"]),
        ideo_base.encode(
            color=gos.value("#A0A0F2"),
            size=gos.value(20),
        ).transform_filter("Stain", oneOf=["gvar"]),
        ideo_base.mark_triangleRight().encode(
            color=gos.value("#B40101"),
            size=gos.value(20),
        ).transform_filter("Stain", oneOf=["acen-1"]),
        ideo_base.mark_triangleLeft().encode(
            color=gos.value("#B40101"),
            size=gos.value(20)
        ).transform_filter("Stain", oneOf=["acen-2"]),
        ideo_base.mark_brush().encode(
            x={"linkingId": "detail"},
            color=gos.value("red"),
            opacity=gos.value(1),
            strokeWidth=gos.value(1),
            stroke=gos.value("red"),
        )
    ).properties(title="chr3", width=WIDTH, height=25)

    gene_base = gos.Track(gene_anno).encode(
        color=gos.Color("strand:N", domain=["+", "-"], range=["#012DB8", "#BE1E2C"]),
        row=gos.Row("strand:N", domain=["+", "-"]),
    ).visibility_lt(
        measure="width",
        threshold="|xe-x|",
        transitionPadding=10,
        target="mark",
    )
    genes = gos.overlay(
        gene_base
            .mark_text(textFontSize=8, dy=-12, outline="#20102F")
            .encode(text="name:N", x="start:G", xe="end:G", size=gos.value(8))
            .transform_filter("type", oneOf=["gene"])
            .transform_filter("strand", oneOf=["+"]),
        gene_base
            .mark_text(textFontSize=8, dy=10, outline="#20102F")
            .encode(text="name:N", x="start:G", xe="end:G", size=gos.value(8))
            .transform_filter("type", oneOf=["gene"])
            .transform_filter("strand", oneOf=["-"]),
        gene_base
            .mark_rect(outline="#20102F")
            .encode(x="end:G", size=gos.value(7))
            .transform_filter("type", oneOf=["gene"])
            .transform_filter("strand", oneOf=["+"]),
        gene_base
            .mark_rect(outline="#20102F")
            .encode(x="start:G", size=gos.value(7))
            .transform_filter("type", oneOf=["gene"])
            .transform_filter("strand", oneOf=["-"]),
        gene_base
            .mark_rect(outline="#20102F")
            .encode(x="start:G", xe="end:G", size=gos.value(14))
            .transform_filter("type", oneOf=["exon"]),
        gene_base
            .mark_rule(outline="#20102F")
            .encode(x="start:G", xe="end:G", strokeWidth=gos.value(3))
            .transform_filter("type", oneOf=["exon"]),
    )

    def bar(title: str, color: str, file: str) -> gos.Track:
        url = f"https://s3.amazonaws.com/gosling-lang.org/data/{file}"
        data = gos.bigwig(url, column="position", value="peak")
        return gos.Track(data).mark_bar(outline="#20102F").encode(
            x="position:G",
            y=gos.Y("peak:Q", axis="right"),
            color=gos.value(color),
        ).properties(title=title, width=WIDTH, height=40)

    def link(tileset_id: str, stroke: str) -> gos.Track:
        url = f"https://server.gosling-lang.org/api/v1/tileset_info/?d={tileset_id}"
        data = gos.beddb(url, genomicFields=[{"name": "start", "index": 1}, {"name": "end", "index": 2}])
        return gos.Track(data).mark_withinLink().encode(
            x="start:G",
            xe="end:G",
            y={"flip": True},
            strokeWidth=gos.value(1),
            color=gos.value("none"),
            stroke=gos.value(stroke),
            opacity=gos.value(0.1),
        )

    tracks = [
        bar("Excitatory neurons", "#F29B67", "ExcitatoryNeurons-insertions_bin100_RIPnorm.bw"),
        bar("Inhibitory neurons", "#3DC491", "InhibitoryNeurons-insertions_bin100_RIPnorm.bw"),
        bar("Dopaminergic neurons", "#565C8B", "DopaNeurons_Cluster10_AllFrags_projSUNI2_insertions_bin100_RIPnorm.bw"),
        bar("Microglia", "#77C0FA", "Microglia-insertions_bin100_RIPnorm.bw"),
        bar("Oligodendrocytes", "#9B46E5", "Oligodendrocytes-insertions_bin100_RIPnorm.bw"),
        bar("Astrocytes", "#D73636", "Astrocytes-insertions_bin100_RIPnorm.bw"),
        bar("OPCs", "#E38ADC", "OPCs-insertions_bin100_RIPnorm.bw"),
        genes.properties(title="Genes", width=WIDTH, height=80),
        gos.overlay(
            link("oligodendrocyte-plac-seq-bedpe", "#F97E2A"),
            link("microglia-plac-seq-bedpe", "#50ADF9"),
            link("neuron-plac-seq-bedpe", "#7B0EDC"),
        ).properties(title="PLAC-seq (H3K4me3) Nott et al.", width=WIDTH, height=60)
    ]

    # COMPOSE

    gos.vertical(
        gos.View(layout="linear", tracks=[ideogram], centerRadius=0.8, xDomain=gos.GenomicDomain(chromosome="chr3")),
        gos.View(tracks=tracks, linkingId="detail", xDomain=gos.GenomicDomain(chromosome="chr3", interval=[52168000, 52890000])),
    )