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sanjaynagi · Jul 24, 2023 · eac69c4 · eac69c4
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diff --git a/docs/rna-seq-pop-docs/notebooks/installation.ipynb b/docs/rna-seq-pop-docs/notebooks/installation.ipynb
@@ -42,6 +42,12 @@
     "\n",
     "When we run RNA-Seq-Pop, it is important to use the `--use-conda` directive - this will automatically install all necessary packages into isolated software environments, so we do not have to install any other dependencies.\n",
     "\n",
+    "Please also ensure your conda has channel priorities set to 'flexible', otherwise, conda may throw up errors when installing packages. You can do this with the following command:\n",
+    "\n",
+    "```\n",
+    "conda config --set channel_priority flexible\n",
+    "```\n",
+    "\n",
     "#### Testing the setup\n",
     "\n",
     "To test whether RNA-Seq-Pop is configured correctly, from the root directory you can perform a dry-run on the test dataset, with the following command:\n",

diff --git a/workflow/envs/pythonGenomics.yaml b/workflow/envs/pythonGenomics.yaml
@@ -259,5 +259,6 @@ dependencies:
   - zstd=1.5.2=hfc55251_7
   - papermill
   - ipykernel
+  - plotly
   - pip:
     - wand
diff --git a/workflow/notebooks/counts-qc.ipynb b/workflow/notebooks/counts-qc.ipynb
@@ -57,7 +57,7 @@
     "import pandas as pd \n",
     "import plotly.express as px\n",
     "\n",
-    "total_counts = pd.read_csv(\"results/quant/countStatistics.tsv\", sep=\"\\t\").rename(columns={'Sample':'sampleID'})\n",
+    "total_counts = pd.read_csv(\"results/counts/countStatistics.tsv\", sep=\"\\t\").rename(columns={'Sample':'sampleID'})\n",
     "metadata = pd.read_csv(metadata_path, sep=\"\\t\")\n",
     "\n",
     "total_counts = total_counts.merge(metadata, how='left')"
@@ -2885,7 +2885,7 @@
     }
    ],
    "source": [
-    "map_df = pd.read_csv(\"results/quant/KallistoQuantSummary.tsv\", sep=\"\\t\").rename(columns={'sample':'sampleID'})\n",
+    "map_df = pd.read_csv(\"results/counts/KallistoQuantSummary.tsv\", sep=\"\\t\").rename(columns={'sample':'sampleID'})\n",
     "map_df = map_df.merge(metadata)\n",
     "px.bar(map_df,\n",
     "       x='sampleID',  \n",
@@ -2927,7 +2927,7 @@
    ],
    "source": [
     "from wand.image import Image as WImage\n",
-    "img = WImage(filename='results/plots/heatmap_correlations.pdf')\n",
+    "img = WImage(filename='results/counts/heatmap_correlations.pdf')\n",
     "img"
    ]
   },
@@ -2963,7 +2963,7 @@
    ],
    "source": [
     "from wand.image import Image as WImage\n",
-    "img = WImage(filename='results/plots/PCA.pdf')\n",
+    "img = WImage(filename='results/counts/PCA.pdf')\n",
     "img"
    ]
   }

diff --git a/workflow/notebooks/windowed-selection.ipynb b/workflow/notebooks/windowed-selection.ipynb
@@ -122,7 +122,7 @@
     "                            ylim=1, \n",
     "                            save=True)\n",
     "                \n",
-    "                fig = px.express(x=FstArray, y=midpoint, title=f'Fst {cohortNoSpaceText} | {contig}')\n",
+    "                fig = px.line(x=FstArray, y=midpoint, title=f'Fst {cohortNoSpaceText} | {contig}')\n",
     "                fig.show()\n",
     "        \n",
     "    #### Population Branch Statistic (PBS) in windows ####\n",
@@ -157,7 +157,7 @@
     "                                ylim=0.5, \n",
     "                                save=True)\n",
     "                    \n",
-    "                    fig = px.express(x=pbsArray, y=midpoint, title=f'PBS {cohortNoSpaceText} | {contig}')\n",
+    "                    fig = px.line(x=pbsArray, y=midpoint, title=f'PBS {cohortNoSpaceText} | {contig}')\n",
     "                    fig.show()"
    ]
   }