From 7c3fa17d34e96926230a66ecf8a7bc5a3cf03ba7 Mon Sep 17 00:00:00 2001
From: Niko Papadopoulos <nikolaos.papadopoulos@embl.de>
Date: Thu, 12 Jan 2023 09:47:59 +0100
Subject: [PATCH] added HMMER annotation performance
---
analysis/revision-percent_annotated.svg | 1636 +++++++++++++++++
analysis/revision-profile_search.ipynb | 255 ++-
analysis/revision-proteome_coverage.ipynb | 29 +-
...vision-single_cell_DEG_with_profiles.ipynb | 917 +++++++++
analysis/single_cell_DEG_revisited.ipynb | 2 +-
analysis/suppl-marker_gene_origins.ipynb | 2 +-
6 files changed, 2802 insertions(+), 39 deletions(-)
create mode 100644 analysis/revision-percent_annotated.svg
create mode 100644 analysis/revision-single_cell_DEG_with_profiles.ipynb
diff --git a/analysis/revision-percent_annotated.svg b/analysis/revision-percent_annotated.svg
new file mode 100644
index 0000000..86465be
--- /dev/null
+++ b/analysis/revision-percent_annotated.svg
@@ -0,0 +1,1636 @@
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diff --git a/analysis/revision-profile_search.ipynb b/analysis/revision-profile_search.ipynb
index 0df2506..6ea0a17 100644
--- a/analysis/revision-profile_search.ipynb
+++ b/analysis/revision-profile_search.ipynb
@@ -18,7 +18,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "2023-01-09 16:55\n"
+ "2023-01-11 11:56\n"
]
}
],
@@ -253,7 +253,189 @@
"ax.hist(morf['#OGs'], bins=20, label='MorF', alpha=0.5, density=True)\n",
"ax.hist(emapper['#OGs'], bins=20, label='emapper', alpha=0.5, density=True)\n",
"ax.hist(hmmer['#OGs'], bins=20, label='emapper-hmmer', alpha=0.5, density=True)\n",
- "ax.legend();"
+ "ax.legend();\n",
+ "fig.savefig('./no_OGs.svg')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "49dd3421-75a0-49a9-a615-227d651e2320",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from scipy.stats import ks_2samp"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "id": "9a54cfe4-291f-4a7e-9d93-49adfc9462b3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "methods = ['MorF', 'emapper', 'emapper-hmmer']\n",
+ "no_OGs = [morf['#OGs'], emapper['#OGs'], hmmer['#OGs']]\n",
+ "pvals = np.zeros((3, 3))\n",
+ "stats = np.zeros((3, 3))\n",
+ "for i in range(3):\n",
+ " for j in range(i, 3):\n",
+ " stat, pval = ks_2samp(no_OGs[i], no_OGs[j])\n",
+ " stats[i, j] = stat\n",
+ " pvals[i, j] = pval"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "464f860c-38fd-4ee0-8b6c-b72a7191e7f0",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "dstat = pd.DataFrame(stats, index=methods, columns=methods)\n",
+ "dpval = pd.DataFrame(pvals, index=methods, columns=methods)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "47511d38-48d9-4cbd-b0e4-b9c42df825d9",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>MorF</th>\n",
+ " <th>emapper</th>\n",
+ " <th>emapper-hmmer</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>MorF</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.535453</td>\n",
+ " <td>0.512195</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>emapper</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.070044</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>emapper-hmmer</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " MorF emapper emapper-hmmer\n",
+ "MorF 0.0 0.535453 0.512195\n",
+ "emapper 0.0 0.000000 0.070044\n",
+ "emapper-hmmer 0.0 0.000000 0.000000"
+ ]
+ },
+ "execution_count": 14,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "dstat"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "4bbde247-8a9d-4c7f-8143-dbb0f1eca85f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>MorF</th>\n",
+ " <th>emapper</th>\n",
+ " <th>emapper-hmmer</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>MorF</th>\n",
+ " <td>1.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>0.000000e+00</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>emapper</th>\n",
+ " <td>0.0</td>\n",
+ " <td>1.0</td>\n",
+ " <td>9.633633e-48</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>emapper-hmmer</th>\n",
+ " <td>0.0</td>\n",
+ " <td>0.0</td>\n",
+ " <td>1.000000e+00</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " MorF emapper emapper-hmmer\n",
+ "MorF 1.0 0.0 0.000000e+00\n",
+ "emapper 0.0 1.0 9.633633e-48\n",
+ "emapper-hmmer 0.0 0.0 1.000000e+00"
+ ]
+ },
+ "execution_count": 15,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "dpval"
]
},
{
@@ -266,7 +448,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 16,
"id": "e53585a7-b2d8-4ad7-90d4-e1baace690a2",
"metadata": {},
"outputs": [
@@ -361,7 +543,7 @@
"max 17.000000 13.000000 16.000000"
]
},
- "execution_count": 11,
+ "execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
@@ -390,7 +572,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 17,
"id": "69d79788-2835-4d54-a97f-841877b1b090",
"metadata": {},
"outputs": [],
@@ -400,7 +582,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 18,
"id": "bb1646f2-8a27-4bbc-9a2b-20e7ed45d18c",
"metadata": {},
"outputs": [],
@@ -429,7 +611,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 19,
"id": "993e7652-aff9-4880-a54f-4fa22e3fc169",
"metadata": {},
"outputs": [],
@@ -440,7 +622,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 20,
"id": "85c67750-3125-412a-8179-71b0401858cb",
"metadata": {},
"outputs": [],
@@ -459,7 +641,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 21,
"id": "d3b9c02c-e388-4cfb-9255-d824f25a368a",
"metadata": {},
"outputs": [],
@@ -477,7 +659,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 22,
"id": "b69d5175-0d57-475c-8f46-62be8265beab",
"metadata": {},
"outputs": [
@@ -494,7 +676,8 @@
],
"source": [
"subplots = upset(overlap, sum_over='counts')\n",
- "subplots['intersections'].set_title('#proteins annotated by each source');"
+ "subplots['intersections'].set_title('#proteins annotated by each source');\n",
+ "plt.savefig('./upset.svg')"
]
},
{
@@ -509,7 +692,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 23,
"id": "82814d7f-d401-49fd-aedf-9b1f6702f150",
"metadata": {},
"outputs": [
@@ -520,7 +703,7 @@
"dtype: int64"
]
},
- "execution_count": 18,
+ "execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
@@ -539,7 +722,7 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 24,
"id": "a412b367-b3b7-46ad-9f22-77dd3509521f",
"metadata": {},
"outputs": [
@@ -549,7 +732,7 @@
"16346"
]
},
- "execution_count": 19,
+ "execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
@@ -571,7 +754,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 25,
"id": "85664620-0bb3-410b-bc7c-e75ad2a90c71",
"metadata": {},
"outputs": [],
@@ -583,7 +766,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 26,
"id": "add4fa47-8fbd-4a95-b522-1cf6bb0a0fd6",
"metadata": {},
"outputs": [],
@@ -593,7 +776,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 27,
"id": "72071b54-9db9-4a50-a4d8-4828453e6115",
"metadata": {},
"outputs": [],
@@ -613,7 +796,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 28,
"id": "859149f7-05d4-4241-99b6-1b8cc20eb558",
"metadata": {},
"outputs": [],
@@ -631,7 +814,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": 29,
"id": "45f4676c-6654-40e7-bee3-1cf4f61d36ec",
"metadata": {},
"outputs": [],
@@ -650,7 +833,7 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": 30,
"id": "66793098-a668-4e0a-8999-9e33a95a7e86",
"metadata": {},
"outputs": [],
@@ -666,7 +849,7 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 31,
"id": "6c7ecd7f-3531-4870-b078-62840bff6b9f",
"metadata": {},
"outputs": [],
@@ -691,7 +874,7 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 32,
"id": "3adc0728-ee33-46b7-8f05-a6d2ece5777f",
"metadata": {},
"outputs": [],
@@ -713,7 +896,7 @@
},
{
"cell_type": "code",
- "execution_count": 28,
+ "execution_count": 33,
"id": "7a2f5c9a-fe22-4d4c-ab9f-b69d157c0f27",
"metadata": {},
"outputs": [],
@@ -732,7 +915,7 @@
},
{
"cell_type": "code",
- "execution_count": 29,
+ "execution_count": 34,
"id": "4382f954-010b-486d-8d28-89cb5bae400b",
"metadata": {},
"outputs": [],
@@ -759,7 +942,7 @@
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": 35,
"id": "5d672a2f-adfa-46da-8548-0657836576a3",
"metadata": {},
"outputs": [],
@@ -781,7 +964,7 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": 36,
"id": "5a683094-4840-4ede-b1a6-ba21a0f49bde",
"metadata": {},
"outputs": [],
@@ -800,7 +983,7 @@
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": 37,
"id": "f31398bf-eeda-4c49-9f35-e11acbe739d9",
"metadata": {},
"outputs": [],
@@ -812,7 +995,7 @@
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": 38,
"id": "588ea19c-6661-4a82-bcda-08253f7c583d",
"metadata": {},
"outputs": [],
@@ -838,7 +1021,7 @@
},
{
"cell_type": "code",
- "execution_count": 34,
+ "execution_count": 39,
"id": "6eb5faba-729c-4745-b9a7-3c2586504e42",
"metadata": {},
"outputs": [
@@ -889,7 +1072,7 @@
},
{
"cell_type": "code",
- "execution_count": 35,
+ "execution_count": 40,
"id": "62496fa8-166a-460c-9354-c49bcfd37fa0",
"metadata": {},
"outputs": [
@@ -909,7 +1092,7 @@
"Name: most_specific_hmmer, dtype: int64"
]
},
- "execution_count": 35,
+ "execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
@@ -920,7 +1103,7 @@
},
{
"cell_type": "code",
- "execution_count": 36,
+ "execution_count": 41,
"id": "539bd579-25c5-46f6-b034-7141ad8b76f8",
"metadata": {},
"outputs": [
@@ -940,7 +1123,7 @@
"Name: most_specific_emapper, dtype: int64"
]
},
- "execution_count": 36,
+ "execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
@@ -951,7 +1134,7 @@
},
{
"cell_type": "code",
- "execution_count": 37,
+ "execution_count": 42,
"id": "1e004899-37ae-4005-a59d-e64bc867a504",
"metadata": {},
"outputs": [
@@ -971,7 +1154,7 @@
"Name: most_specific_morf, dtype: int64"
]
},
- "execution_count": 37,
+ "execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
diff --git a/analysis/revision-proteome_coverage.ipynb b/analysis/revision-proteome_coverage.ipynb
index b4d3446..2382063 100644
--- a/analysis/revision-proteome_coverage.ipynb
+++ b/analysis/revision-proteome_coverage.ipynb
@@ -54,6 +54,33 @@
"plddt[\"S_lacustris\"] = np.array(score)"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "0977f3aa-29b1-4a31-8f81-78fe340cb561",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "A_thaliana: 76.22393314776092\n",
+ "M_musculus: 76.83108403554503\n",
+ "D_rerio: 77.01267466362071\n",
+ "S_cerevisiae: 77.06218951526964\n",
+ "H_sapiens: 75.10441887682073\n",
+ "D_discoideum: 72.2162702104969\n",
+ "C_elegans: 76.09296514024136\n",
+ "D_melanogaster: 75.47418361932716\n",
+ "S_lacustris: 71.38809554389019\n"
+ ]
+ }
+ ],
+ "source": [
+ "for species, score in plddt.items():\n",
+ " print(f\"{species}: {np.mean(score)}\")"
+ ]
+ },
{
"cell_type": "markdown",
"id": "9637a995-be1d-467e-8073-4238e8ae080e",
@@ -658,7 +685,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.9.6"
+ "version": "3.10.8"
}
},
"nbformat": 4,
diff --git a/analysis/revision-single_cell_DEG_with_profiles.ipynb b/analysis/revision-single_cell_DEG_with_profiles.ipynb
new file mode 100644
index 0000000..c5f394e
--- /dev/null
+++ b/analysis/revision-single_cell_DEG_with_profiles.ipynb
@@ -0,0 +1,917 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "8b813252-6913-44b4-91f9-a5fb6e4092af",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "2023-01-12 09:33:39.395283+01:00\n"
+ ]
+ }
+ ],
+ "source": [
+ "from datetime import datetime, timezone\n",
+ "import pytz\n",
+ "\n",
+ "utc_dt = datetime.now(timezone.utc) # UTC time\n",
+ "dt = utc_dt.astimezone()\n",
+ "tz = pytz.timezone('Europe/Berlin')\n",
+ "berlin_now = datetime.now(tz)\n",
+ "print(berlin_now)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "902f2931-a576-45c2-81a9-2fcc3b78dd92",
+ "metadata": {},
+ "source": [
+ "# 0. import libraries, general settings"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "0c13d25a-13ed-468d-961e-e80ac57aecdd",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/Users/npapadop/miniconda3/envs/samap/lib/python3.10/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+ " from .autonotebook import tqdm as notebook_tqdm\n"
+ ]
+ }
+ ],
+ "source": [
+ "# first mute future warnings and only then import pandas\n",
+ "import warnings\n",
+ "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
+ "\n",
+ "import numpy as np\n",
+ "import scipy\n",
+ "import pandas as pd\n",
+ "import scanpy as sc\n",
+ "\n",
+ "from matplotlib import pyplot as plt\n",
+ "from matplotlib import cm\n",
+ "import seaborn as sns\n",
+ "from tqdm import tqdm"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "2e0e9ac4-4f61-4491-a891-a78f6299ee83",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sc.settings.verbosity = 3 # verbosity: errors (0), warnings (1), info (2), hints (3)\n",
+ "sc.settings.set_figure_params(dpi=80, facecolor='white')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "f9907683-d99f-44e2-bb63-7db21f8a7150",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from numpy.random import MT19937\n",
+ "from numpy.random import RandomState, SeedSequence\n",
+ "rs = RandomState(MT19937(SeedSequence(42)))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5ec02706-d1e8-455a-bb98-350c9320048c",
+ "metadata": {},
+ "source": [
+ "# 1. Set up annotation"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "00ff9ce0-0a2f-4149-b731-0a003227e07d",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/var/folders/md/d6lwwbv97xb6g6ddypntnprh0000gp/T/ipykernel_20464/3664721023.py:5: DtypeWarning: Columns (6,7,29) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+ " annot = pd.read_csv(\"../data/revision/spongilla_lut.tsv\", sep='\\t')\n"
+ ]
+ }
+ ],
+ "source": [
+ "hmmer = pd.read_csv('../data/profile/slac_hmmer.emapper.annotations', engine='python', skiprows=4, skipfooter=3, sep='\\t')\n",
+ "hmmer['gene_id'] = hmmer['#query'].str.split('_').str[:2].str.join('_')\n",
+ "\n",
+ "# read foldseek annotation and keep relevant columns\n",
+ "annot = pd.read_csv(\"../data/revision/spongilla_lut.tsv\", sep='\\t')\n",
+ "\n",
+ "annot = annot.join(hmmer.set_index('gene_id'), on='gene_id')\n",
+ "\n",
+ "annot_nodoubl = annot.sort_values('bit score', ascending=False).drop_duplicates('gene_id')\n",
+ "keep = ['gene_id', 'Preferred_name_seq', 'Preferred_name_struct', 'Preferred_name' , 'Description_seq', 'Description_struct', 'Description', 'Function [CC]', 'PFAMs_seq', 'PFAMs_struct']\n",
+ "annot_nodoubl = annot_nodoubl[keep]\n",
+ "\n",
+ "annot_nodoubl.columns = ['gene_id', 'Preferred_name_seq', 'Preferred_name_struct', 'Preferred_name_hmmer' , 'Description_seq', 'Description_struct', 'Description_hmmer', 'Function [CC]', 'PFAMs_seq', 'PFAMs_struct']"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "804f632e-0131-4bf0-92f0-41bb73bfb2ba",
+ "metadata": {},
+ "source": [
+ "# 1. Read single-cell data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "079fe25c-de03-4b28-a89d-b30890fd141a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "adata = sc.read('../data/revision/spongilla_basic.h5ad')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "77217333-43ee-4ed3-992c-370c0efa4740",
+ "metadata": {},
+ "source": [
+ "# 2. Set up gene annotation"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "fddc78f9-7b86-4035-8bde-c1e950e260cd",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# create a naked gene_id column to merge on\n",
+ "adata.var['gene_id'] = adata.var.index.str.split().str[0].str.replace('-', '_')\n",
+ "adata.var['legacy name'] = adata.var.index.values\n",
+ "adata.var.set_index('gene_id', inplace=True)\n",
+ "\n",
+ "adata.var = adata.var.join(annot_nodoubl.set_index('gene_id'), how='left')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "93218bd8-2317-4d05-b7f2-c9710599c26a",
+ "metadata": {},
+ "source": [
+ "To facilitate marker gene plotting but also counting the number of annotated genes we will create new columns in the `.var` slot that will hold the sequence based names, structure based names, and combinations thereof, which will be the most comprehensive.\n",
+ "\n",
+ "First we'll start by finding the different annotation levels - named genes, described genes, and unannotated genes - both for sequence-based and structure-based annotation."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "20e0dae0-ae54-48cf-a4ba-2283bff66c02",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "seq_isnan = adata.var[\"Preferred_name_seq\"].isnull()\n",
+ "seq_missing = adata.var[\"Preferred_name_seq\"] == \"-\"\n",
+ "seq_no_desc = adata.var[\"Description_seq\"].isnull()\n",
+ "seq_desc_mis = adata.var[\"Description_seq\"] == \"-\"\n",
+ "\n",
+ "struct_isnan = adata.var[\"Preferred_name_struct\"].isnull()\n",
+ "struct_missing = adata.var[\"Preferred_name_struct\"] == \"-\"\n",
+ "struct_no_desc = adata.var[\"Description_struct\"].isnull()\n",
+ "struct_desc_mis = adata.var[\"Description_struct\"] == \"-\"\n",
+ "\n",
+ "hmmer_isnan = adata.var[\"Preferred_name_hmmer\"].isnull()\n",
+ "hmmer_missing = adata.var[\"Preferred_name_hmmer\"] == \"-\"\n",
+ "hmmer_no_desc = adata.var[\"Description_hmmer\"].isnull()\n",
+ "hmmer_desc_mis = adata.var[\"Description_hmmer\"] == \"-\"\n",
+ "\n",
+ "seq_has_name = ~(seq_isnan | seq_missing)\n",
+ "seq_has_desc = ~(seq_no_desc | seq_desc_mis)\n",
+ "struct_has_name = ~(struct_isnan | struct_missing)\n",
+ "struct_has_desc = ~(struct_no_desc | struct_desc_mis)\n",
+ "hmmer_has_name = ~(hmmer_isnan | hmmer_missing)\n",
+ "hmmer_has_desc = ~(hmmer_no_desc | hmmer_desc_mis)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "f5bf8136-431a-453d-90f2-4faef4746c7d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "adata.var['gene_id'] = adata.var.index.values"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "770496d9-cb80-4c28-912d-f00f196a1bda",
+ "metadata": {},
+ "source": [
+ "Now we will combine the masks to build the best sequence annotation by using the gene IDs and the emapper fields"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "9a8782a1-7227-46ec-ae5d-9c6fe6ec97b3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# build best sequence annotation\n",
+ "has_seq_desc_but_no_seq_name = seq_has_desc & ~seq_has_name\n",
+ "seq_unannotated = ~(seq_has_name | has_seq_desc_but_no_seq_name)\n",
+ "seq_named = adata.var[\"gene_id\"][seq_has_name] + \" | \" + \"[\" + adata.var[\"Preferred_name_seq\"][seq_has_name] + \"]\"\n",
+ "seq_described = adata.var[\"gene_id\"][has_seq_desc_but_no_seq_name] + \" | [\" + adata.var[\"Description_seq\"][has_seq_desc_but_no_seq_name] +\"]\"\n",
+ "seq_unnamed = adata.var[\"gene_id\"][seq_unannotated]\n",
+ "seq_names = pd.DataFrame(seq_named.append(seq_described).append(seq_unnamed))\n",
+ "seq_names.columns = ['best seq. name']"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "cb84210e-c14a-4841-b400-6116112e16b0",
+ "metadata": {},
+ "source": [
+ "same for structure-based annotation"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "b1b15b87-ece8-4cbe-9875-3a5724e291ea",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# build best structure annotation\n",
+ "has_struct_desc_but_no_struct_name = struct_has_desc & ~struct_has_name\n",
+ "struct_unannotated = ~(struct_has_name | has_struct_desc_but_no_struct_name)\n",
+ "struct_named = adata.var[\"gene_id\"][struct_has_name] + \" | (\" + adata.var[\"Preferred_name_struct\"][struct_has_name] + ')'\n",
+ "struct_described = adata.var[\"gene_id\"][has_struct_desc_but_no_struct_name] + \" | (\" + adata.var[\"Description_struct\"][has_struct_desc_but_no_struct_name] + \")\"\n",
+ "struct_unnamed = adata.var[\"gene_id\"][struct_unannotated]\n",
+ "struct_names = pd.DataFrame(struct_named.append(struct_described).append(struct_unnamed))\n",
+ "struct_names.columns = ['best struct. name']"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5195ed39-90ae-4335-9a74-112925a6fc50",
+ "metadata": {},
+ "source": [
+ "...and for HMMER:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "id": "cf3a7576-4443-4272-9d42-0908be4719d2",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# build best hmmeruence annotation\n",
+ "has_hmmer_desc_but_no_hmmer_name = hmmer_has_desc & ~hmmer_has_name\n",
+ "hmmer_unannotated = ~(hmmer_has_name | has_hmmer_desc_but_no_hmmer_name)\n",
+ "hmmer_named = adata.var[\"gene_id\"][hmmer_has_name] + \" | \" + \"[\" + adata.var[\"Preferred_name_hmmer\"][hmmer_has_name] + \"]\"\n",
+ "hmmer_described = adata.var[\"gene_id\"][has_hmmer_desc_but_no_hmmer_name] + \" | [\" + adata.var[\"Description_hmmer\"][has_hmmer_desc_but_no_hmmer_name] +\"]\"\n",
+ "hmmer_unnamed = adata.var[\"gene_id\"][hmmer_unannotated]\n",
+ "hmmer_names = pd.DataFrame(hmmer_named.append(hmmer_described).append(hmmer_unnamed))\n",
+ "hmmer_names.columns = ['best hmmer name']"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1d9cf4cc-e11c-4283-9680-7083294704f7",
+ "metadata": {},
+ "source": [
+ "Very similarly, we will combine the masks to make the best combination. We will always give precedence to sequence-based annotation, wherever available."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "ef29fc56-9490-4670-aeb9-8c947735d612",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# best overall annotation\n",
+ "# first sequence name, then sequence description\n",
+ "# then structure name, then structure description\n",
+ "has_struct_name_but_no_seq_any = seq_unannotated & struct_has_name\n",
+ "has_struct_desc_but_no_else = seq_unannotated & ~struct_has_name & struct_has_desc\n",
+ "unannotated = ~(seq_has_name | seq_has_desc | struct_has_name | struct_has_desc)\n",
+ "\n",
+ "struct_named_no_seq = adata.var[\"gene_id\"][has_struct_name_but_no_seq_any] + \" | (\" + adata.var[\"Preferred_name_struct\"][has_struct_name_but_no_seq_any] + \")\"\n",
+ "struct_desc_nothing_else = adata.var[\"gene_id\"][has_struct_desc_but_no_else] + \" | (\" + adata.var[\"Description_struct\"][has_struct_desc_but_no_else] + \")\"\n",
+ "unnamed = adata.var[\"gene_id\"][unannotated]\n",
+ "\n",
+ "best_names = pd.DataFrame(seq_named.append(seq_described).append(struct_named_no_seq).append(struct_desc_nothing_else).append(unnamed))\n",
+ "best_names.columns = ['best name']"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "55492863-9381-41ac-8c4d-774f44aefb84",
+ "metadata": {},
+ "source": [
+ "Actuall add the annotation to the object:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "d1d6756d-f096-456f-bb93-8216aca01429",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "adata.var = adata.var.join(seq_names)\n",
+ "adata.var = adata.var.join(struct_names)\n",
+ "adata.var = adata.var.join(hmmer_names)\n",
+ "adata.var = adata.var.join(best_names)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "0abf39c4-7888-43a2-b55c-b233c69068d6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "adata.var.drop('gene_id', inplace=True, axis=1)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "8d6a1a84-1e69-44a8-beec-fda53550dca7",
+ "metadata": {
+ "tags": []
+ },
+ "source": [
+ "# Comparing performance\n",
+ "\n",
+ "We will look at how many more DEGs we can annotate using the MAF output, and we will do so on the cluster, cell type, and clade level. First we'll read the tables from Supplementary Data S1 [Musser _et al._, 2021](https://www.science.org/doi/10.1126/science.abj2949):\n",
+ "\n",
+ "- `DEG_clusters.tsv` is the \"Diff. Exp. 42 clusters\" tab\n",
+ "- `DEG_celltypes.tsv` is the \"Diff. Exp. cell types\" tab\n",
+ "- `DEG_clusters.tsv` is the \"Cell Type clade genes (OU tests\" tab"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "86ebdafa-c5ea-41bf-a473-07a2b93d6a37",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cluster_DEG = pd.read_csv('../data/revision/DEG_clusters.tsv', sep='\\t', decimal=',')\n",
+ "cluster_DEG['gene_id'] = cluster_DEG['Automated Gene Name (in seurat object and some suppl. Figs.)'].str.split().str[0].str.replace('-', '_')\n",
+ "cluster_DEG = cluster_DEG.merge(seq_names, on='gene_id').merge(struct_names, on='gene_id').merge(best_names, on='gene_id').merge(hmmer_names, on='gene_id')\n",
+ "\n",
+ "celltype_DEG = pd.read_csv('../data/revision/DEG_celltypes.tsv', sep='\\t', decimal=',')\n",
+ "celltype_DEG['gene_id'] = celltype_DEG['Automated Gene Name (in seurat object and some suppl. Figs.)'].str.split().str[0].str.replace('-', '_')\n",
+ "celltype_DEG = celltype_DEG.merge(seq_names, on='gene_id').merge(struct_names, on='gene_id').merge(best_names, on='gene_id').merge(hmmer_names, on='gene_id')\n",
+ "\n",
+ "clade_DEG = pd.read_csv('../data/revision/DEG_clades.tsv', sep='\\t', decimal=',')\n",
+ "clade_DEG['gene_id'] = clade_DEG['Automated Gene Name (in seurat object and some suppl. Figs.)'].str.split().str[0].str.replace('-', '_')\n",
+ "clade_DEG = clade_DEG.merge(seq_names, on='gene_id').merge(struct_names, on='gene_id').merge(best_names, on='gene_id').merge(hmmer_names, on='gene_id')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2c162380-adc1-4707-8022-eaea27396da6",
+ "metadata": {},
+ "source": [
+ "From each table we will extract the DEGs per level of annotation (cluster, cell type, clade), and count which proportion of them is annotated using the legacy annotation (phylome+blastp from the Musser _et al._ paper) versus the MAF pipeline."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "id": "76167388-748e-49de-9a24-30a29d21f34d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def parse_table(df, slot):\n",
+ " df = df[df[slot].notna()]\n",
+ " res = {}\n",
+ " for category in np.unique(df[slot]):\n",
+ " tmp = df[df[slot] == category]\n",
+ " legacy_named = ~tmp['Manually curated gene name'].isnull() | tmp['Automated Gene Name (in seurat object and some suppl. Figs.)'].str.contains(' ')\n",
+ " seq_named = tmp['best seq. name'].str.contains('\\|')\n",
+ " struct_named = tmp['best struct. name'].str.contains('\\|')\n",
+ " hmmer_named = tmp['best hmmer name'].str.contains('\\|')\n",
+ " best_named = tmp['best name'].str.contains('\\|')\n",
+ " res[category] = np.array([sum(legacy_named), sum(seq_named), sum(struct_named), sum(hmmer_named), sum(best_named)]) / len(tmp)\n",
+ " annot = pd.DataFrame(res).T\n",
+ " annot.columns = ['legacy', 'emapper only', 'FoldSeek only', 'hmmer only', 'emapper+FoldSeek']\n",
+ " return annot"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "b8b22d4d-640c-43db-97be-cc626a59247f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cluster_annot = parse_table(cluster_DEG, 'Cluster #')\n",
+ "celltype_annot = parse_table(cluster_DEG, 'Cell Type')\n",
+ "clade_annot = parse_table(clade_DEG, 'Clade with changed optimal expression')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "a1efdb8a-dbd1-461a-88d5-8b5b38f6ef8c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Text(0.5, 1.0, '%annotated DEGs (cell type level)')"
+ ]
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<Figure size 1600x400 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 569,
+ "width": 1293
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# fig, ax = plt.subplots(figsize=(30, 5))\n",
+ "# cluster_annot.plot(y=['legacy', 'emapper only', 'FoldSeek only', 'emapper+FoldSeek'], kind='bar', ax=ax);\n",
+ "# ax.set_title('%annotated DEGs (cluster level)')\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(20, 5))\n",
+ "celltype_annot.plot(y=['legacy', 'emapper only', 'hmmer only', 'FoldSeek only', 'emapper+FoldSeek'], kind='bar', ax=ax);\n",
+ "ax.set_title('%annotated DEGs (cell type level)')\n",
+ "# plt.savefig('./figures/analysis-celltype_DEG.pdf')\n",
+ "# fig, ax = plt.subplots(figsize=(30, 5))\n",
+ "# clade_annot.plot(y=['legacy', 'emapper only', 'FoldSeek only', 'emapper+FoldSeek'], kind='bar', ax=ax);\n",
+ "# ax.set_title('%annotated DEGs (clade level)');"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "87e84edd-f1e4-43d2-aa10-0625b5212039",
+ "metadata": {},
+ "source": [
+ "Maybe a better way to get a feeling is to compare %enrichment. We will extract it from the peaks and plot it separately:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "0569065e-523e-45a2-a2cc-256f37d4c0e5",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "n_clust = len(cluster_annot)\n",
+ "n_cellt = len(celltype_annot)\n",
+ "n_clade = len(clade_annot)\n",
+ "total_categories = n_clust + n_cellt + n_clade\n",
+ "\n",
+ "morf_enrichment_clust = list(cluster_annot['FoldSeek only'] / cluster_annot['hmmer only'] - 1)\n",
+ "morf_enrichment_cellt = list(celltype_annot['FoldSeek only'] / celltype_annot['hmmer only'] - 1)\n",
+ "morf_enrichment_clade = list(clade_annot['FoldSeek only'] / clade_annot['hmmer only'] - 1)\n",
+ "\n",
+ "blastp_enrichment_clust = list(cluster_annot['FoldSeek only'] / cluster_annot['legacy'] - 1)\n",
+ "blastp_enrichment_cellt = list(celltype_annot['FoldSeek only'] / celltype_annot['legacy'] - 1)\n",
+ "blastp_enrichment_clade = list(clade_annot['FoldSeek only'] / clade_annot['legacy'] - 1)\n",
+ "\n",
+ "best_enrichment_clust = list(cluster_annot['FoldSeek only'] / cluster_annot['emapper only'] - 1)\n",
+ "best_enrichment_cellt = list(celltype_annot['FoldSeek only'] / celltype_annot['emapper only'] - 1)\n",
+ "best_enrichment_clade = list(clade_annot['FoldSeek only'] / clade_annot['emapper only'] - 1)\n",
+ "\n",
+ "enrichment = morf_enrichment_clust + morf_enrichment_cellt + morf_enrichment_clade + blastp_enrichment_clust + blastp_enrichment_cellt + blastp_enrichment_clade + best_enrichment_clust + best_enrichment_cellt + best_enrichment_clade\n",
+ "tool = ['MorF to emapper-hmmer'] * total_categories + ['MorF to BLASTP'] * total_categories + ['MorF to emapper'] * total_categories\n",
+ "single_level = ['cluster'] * n_clust + ['cell type'] * n_cellt + ['clade'] * n_clade\n",
+ "level = single_level + single_level + single_level"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "id": "e9ba57f3-4d03-4efe-8c0b-6e0f1c3dd7fa",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "summary = pd.DataFrame({'%enrichment': np.array(enrichment) * 100, 'comparison': tool, 'level': level})"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "id": "8d27b55b-bb95-4542-add6-03d9f0e2e17b",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x28b10cf10>"
+ ]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 320x320 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 300,
+ "width": 514
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots()\n",
+ "sns.boxplot(data=summary, x='level', y='%enrichment', hue='comparison', ax=ax, hue_order=['MorF to emapper-hmmer', 'MorF to BLASTP', 'MorF to emapper'], palette=cm.Set3.colors[:3], whis=[5, 95])\n",
+ "ax.legend(loc=[1.05, 0.4])\n",
+ "# ax.set_ylim(0, 150)\n",
+ "# plt.savefig('./analysis-enrichment.svg')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "fd0c6703-199f-40af-a68b-0fdbda8e841b",
+ "metadata": {},
+ "source": [
+ "let's just plot the raw numbers for that:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "id": "776a9ee5-36b0-460c-966a-008967b6b0d2",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "raw = pd.concat([cluster_annot, celltype_annot, clade_annot], keys=['cluster', 'cell type', 'clade'])\n",
+ "raw.reset_index(inplace=True)\n",
+ "raw.columns = ['level', 'category', 'emapper + BLASTp', 'standard emapper', 'MorF', 'emapper-hmmer', 'MorF + sequence']"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "id": "0dc371dd-2075-47cd-8f4f-3ab62fa8d46e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>level</th>\n",
+ " <th>category</th>\n",
+ " <th>emapper + BLASTp</th>\n",
+ " <th>standard emapper</th>\n",
+ " <th>MorF</th>\n",
+ " <th>emapper-hmmer</th>\n",
+ " <th>MorF + sequence</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>cluster</td>\n",
+ " <td>1</td>\n",
+ " <td>0.760632</td>\n",
+ " <td>0.781288</td>\n",
+ " <td>0.873633</td>\n",
+ " <td>0.842041</td>\n",
+ " <td>0.877278</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>cluster</td>\n",
+ " <td>2</td>\n",
+ " <td>0.645000</td>\n",
+ " <td>0.625000</td>\n",
+ " <td>0.805000</td>\n",
+ " <td>0.750000</td>\n",
+ " <td>0.810000</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>cluster</td>\n",
+ " <td>3</td>\n",
+ " <td>0.675234</td>\n",
+ " <td>0.619159</td>\n",
+ " <td>0.794393</td>\n",
+ " <td>0.750000</td>\n",
+ " <td>0.801402</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>cluster</td>\n",
+ " <td>4</td>\n",
+ " <td>0.651413</td>\n",
+ " <td>0.567968</td>\n",
+ " <td>0.769852</td>\n",
+ " <td>0.706595</td>\n",
+ " <td>0.776581</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>cluster</td>\n",
+ " <td>5</td>\n",
+ " <td>0.600400</td>\n",
+ " <td>0.517483</td>\n",
+ " <td>0.727273</td>\n",
+ " <td>0.662338</td>\n",
+ " <td>0.733267</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>104</th>\n",
+ " <td>clade</td>\n",
+ " <td>incPin1/2</td>\n",
+ " <td>0.338028</td>\n",
+ " <td>0.244131</td>\n",
+ " <td>0.441315</td>\n",
+ " <td>0.377934</td>\n",
+ " <td>0.450704</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>105</th>\n",
+ " <td>clade</td>\n",
+ " <td>incPin2</td>\n",
+ " <td>0.362869</td>\n",
+ " <td>0.261603</td>\n",
+ " <td>0.468354</td>\n",
+ " <td>0.413502</td>\n",
+ " <td>0.485232</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>106</th>\n",
+ " <td>clade</td>\n",
+ " <td>incPin_apnPin</td>\n",
+ " <td>0.434783</td>\n",
+ " <td>0.327231</td>\n",
+ " <td>0.521739</td>\n",
+ " <td>0.469108</td>\n",
+ " <td>0.530892</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>107</th>\n",
+ " <td>clade</td>\n",
+ " <td>incPin_apnPin_Lph</td>\n",
+ " <td>0.461538</td>\n",
+ " <td>0.323887</td>\n",
+ " <td>0.587045</td>\n",
+ " <td>0.518219</td>\n",
+ " <td>0.595142</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>108</th>\n",
+ " <td>clade</td>\n",
+ " <td>incPin_apnPin_Lph_Scp_basPin</td>\n",
+ " <td>0.589552</td>\n",
+ " <td>0.500000</td>\n",
+ " <td>0.619403</td>\n",
+ " <td>0.589552</td>\n",
+ " <td>0.626866</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>109 rows × 7 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " level category emapper + BLASTp \\\n",
+ "0 cluster 1 0.760632 \n",
+ "1 cluster 2 0.645000 \n",
+ "2 cluster 3 0.675234 \n",
+ "3 cluster 4 0.651413 \n",
+ "4 cluster 5 0.600400 \n",
+ ".. ... ... ... \n",
+ "104 clade incPin1/2 0.338028 \n",
+ "105 clade incPin2 0.362869 \n",
+ "106 clade incPin_apnPin 0.434783 \n",
+ "107 clade incPin_apnPin_Lph 0.461538 \n",
+ "108 clade incPin_apnPin_Lph_Scp_basPin 0.589552 \n",
+ "\n",
+ " standard emapper MorF emapper-hmmer MorF + sequence \n",
+ "0 0.781288 0.873633 0.842041 0.877278 \n",
+ "1 0.625000 0.805000 0.750000 0.810000 \n",
+ "2 0.619159 0.794393 0.750000 0.801402 \n",
+ "3 0.567968 0.769852 0.706595 0.776581 \n",
+ "4 0.517483 0.727273 0.662338 0.733267 \n",
+ ".. ... ... ... ... \n",
+ "104 0.244131 0.441315 0.377934 0.450704 \n",
+ "105 0.261603 0.468354 0.413502 0.485232 \n",
+ "106 0.327231 0.521739 0.469108 0.530892 \n",
+ "107 0.323887 0.587045 0.518219 0.595142 \n",
+ "108 0.500000 0.619403 0.589552 0.626866 \n",
+ "\n",
+ "[109 rows x 7 columns]"
+ ]
+ },
+ "execution_count": 24,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "raw"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "id": "db7d14a8-55ed-4ac4-92d2-84da2c145ce3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "melted = pd.melt(raw, id_vars='level', value_vars=['emapper + BLASTp', 'standard emapper', 'emapper-hmmer', 'MorF'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "id": "a3ace622-684c-47ac-b320-ed107b6b1dc7",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(28897, 22)"
+ ]
+ },
+ "execution_count": 26,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "hmmer.shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "id": "67a709d0-7e42-4567-a135-fc7015373114",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "2473"
+ ]
+ },
+ "execution_count": 27,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "((hmmer['Description'] == '-') & (hmmer['Preferred_name'] == '-')).sum()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "id": "5c63c05d-502d-4137-b913-51a263649a2a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "melted = melted.append({'level': 'whole organism', 'variable': 'standard mapper', 'value': 17990/41943}, ignore_index=True)\n",
+ "melted = melted.append({'level': 'whole organism', 'variable': 'MorF', 'value': 25232/41943}, ignore_index=True)\n",
+ "melted = melted.append({'level': 'whole organism', 'variable': 'emapper + BLASTp', 'value': (17990 + 682)/41943}, ignore_index=True)\n",
+ "melted = melted.append({'level': 'whole organism', 'variable': 'emapper-hmmer', 'value': (28897-2473)/41943}, ignore_index=True)\n",
+ "# melted.append(['whole organism', 'CoFFE', ])\n",
+ "# melted.append(['whole organism', 'EggNOG-mapper + BLASTp', ])\n",
+ "# melted['level'] = melted['level'].str.replace(' ', '\\n')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "id": "e96a39fb-13c3-44b2-81b0-f4f8cc4d74c0",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 320x320 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 300,
+ "width": 476
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots()\n",
+ "sns.boxplot(data=melted, x='level', y='value', hue='variable', ax=ax, hue_order=['standard emapper', 'emapper + BLASTp', 'emapper-hmmer', 'MorF'], \n",
+ " palette=cm.Set3.colors[:4], whis=[5, 95], order=['whole organism', 'clade', 'cell type'])\n",
+ "ax.legend(loc=[1.05, 0.4])\n",
+ "# ax.set_ylim(0, 150)\n",
+ "plt.savefig('./revision-percent_annotated.svg')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "8dc9af18-c5b8-43e2-ba84-5cb8f7153973",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.8"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/analysis/single_cell_DEG_revisited.ipynb b/analysis/single_cell_DEG_revisited.ipynb
index 0d06c3e..a23aa06 100644
--- a/analysis/single_cell_DEG_revisited.ipynb
+++ b/analysis/single_cell_DEG_revisited.ipynb
@@ -866,7 +866,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.9.6"
+ "version": "3.10.8"
}
},
"nbformat": 4,
diff --git a/analysis/suppl-marker_gene_origins.ipynb b/analysis/suppl-marker_gene_origins.ipynb
index febf8a8..72d90cc 100644
--- a/analysis/suppl-marker_gene_origins.ipynb
+++ b/analysis/suppl-marker_gene_origins.ipynb
@@ -320,7 +320,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.6"
+ "version": "3.10.8"
}
},
"nbformat": 4,
--
GitLab