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docs/how-to/ChIP_seq_genomic_ranges_tutorial.ipynb

@@ -14,13 +14,10 @@
    "outputs": [],
    "source": [
     "# Core scverse libraries\n",
-    "import scanpy as sc\n",
     "import numpy as np\n",
-    "import pandas as pd\n",
     "import genomic_features as gf\n",
     "\n",
     "# Data retrieval\n",
-    "import pooch\n",
     "import bioframe\n",
     "import seaborn\n",
     "import matplotlib.pyplot as plt"
@@ -268,7 +265,7 @@
    "source": [
     "ctcf_peak = bioframe.read_table(\n",
     "    \"https://www.encodeproject.org/files/ENCFF417KHZ/@@download/ENCFF417KHZ.bed.gz\",\n",
-    "    schema=\"narrowPeak\"\n",
+    "    schema=\"narrowPeak\",\n",
     ")\n",
     "\n",
     "ctcf_peak"
@@ -615,7 +612,7 @@
     }
    ],
    "source": [
-    "genes = ensdb.genes(    \n",
+    "genes = ensdb.genes(\n",
     "    filter=gf.filters.GeneBioTypeFilter(\"protein_coding\"),\n",
     ")\n",
     "\n",
@@ -1313,10 +1310,7 @@
    ],
    "source": [
     "gene_ov = bioframe.overlap(\n",
-    "    ctcf_peak,\n",
-    "    genes,\n",
-    "    cols2=[\"seq_name\", \"gene_seq_start\", \"gene_seq_end\"],\n",
-    "    how='inner'\n",
+    "    ctcf_peak, genes, cols2=[\"seq_name\", \"gene_seq_start\", \"gene_seq_end\"], how=\"inner\"\n",
     ")\n",
     "\n",
     "gene_ov"
@@ -1494,8 +1488,7 @@
     }
    ],
    "source": [
-    "exons = ensdb.exons(\n",
-    "    filter=gf.filters.GeneIDFilter(gene_ov[\"gene_id_\"]))\n",
+    "exons = ensdb.exons(filter=gf.filters.GeneIDFilter(gene_ov[\"gene_id_\"]))\n",
     "\n",
     "exons[\"seq_name\"] = exons[\"seq_name\"].map(hg38.alias_dict)\n",
     "\n",
@@ -2337,11 +2330,11 @@
    ],
    "source": [
     "# Create a histogram\n",
-    "palette = seaborn.color_palette(\"ch:s=.25,rot=-.25\", \n",
-    "                                len(exon_ov[\"gene_feature\"].unique()))\n",
+    "palette = seaborn.color_palette(\n",
+    "    \"ch:s=.25,rot=-.25\", len(exon_ov[\"gene_feature\"].unique())\n",
+    ")\n",
     "\n",
-    "ax = seaborn.histplot(exon_ov[\"gene_feature\"], \n",
-    "                      stat=\"percent\")\n",
+    "ax = seaborn.histplot(exon_ov[\"gene_feature\"], stat=\"percent\")\n",
     "\n",
     "# Set ylim\n",
     "plt.ylim(0, 100)\n",
@@ -2352,14 +2345,16 @@
     "\n",
     "# Add values on top of the bars\n",
     "for p in ax.patches:\n",
-    "    ax.annotate(f'{p.get_height():.2f}%', \n",
-    "                (p.get_x() + p.get_width() / 2., p.get_height()), \n",
-    "                ha='center', \n",
-    "                va='center',\n",
-    "                fontsize=10, \n",
-    "                color='black', \n",
-    "                xytext=(0, 5), \n",
-    "                textcoords='offset points')\n",
+    "    ax.annotate(\n",
+    "        f\"{p.get_height():.2f}%\",\n",
+    "        (p.get_x() + p.get_width() / 2.0, p.get_height()),\n",
+    "        ha=\"center\",\n",
+    "        va=\"center\",\n",
+    "        fontsize=10,\n",
+    "        color=\"black\",\n",
+    "        xytext=(0, 5),\n",
+    "        textcoords=\"offset points\",\n",
+    "    )\n",
     "\n",
     "# Show the plot\n",
     "plt.show()"
@@ -2774,7 +2769,9 @@
     "    ignore_downstream=True,\n",
     "    k=1,\n",
     ")\n",
-    "out[out[\"distance\"] < 2000] #filter for peaks 2000kb upstream or closer to promoter region\n",
+    "out[\n",
+    "    out[\"distance\"] < 2000\n",
+    "]  # filter for peaks 2000kb upstream or closer to promoter region\n",
     "out"
    ]
   }