Add to documentation (#74)

* Add to `MultipleDicotPipeline` explanation in notebook

* Cite HackMD in README

README.md

@@ -21,6 +21,10 @@ pip install sleap-roots
 
 ## Usage
 
+Detailed trait documentation per pipeline is available here:
+[sleap-roots HackMD](https://hackmd.io/DMiXO2kXQhKH8AIIcIy--g)
+
+
 ### `DicotPipeline`
 
 **1. Computing traits for a single plant:**

notebooks/MultipleDicotPipeline.ipynb

@@ -26,10 +26,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The `MultipleDicotPipeline` was constructed for multiple, dicot plants in cylinders with 72 frame image series.  \n",
-    "It expects h5 files, primary and lateral root predictions per cylinder.  \n",
-    "It also expects the number of plants per cylinder in the form of a csv with a column \"number_of_plants_cylinder\"  \n",
-    "for each series in the csv, which should be identified by a column called \"plant_qr_code\".  "
+    "- The `MultipleDicotPipeline` was constructed for multiple, dicot plants in cylinders   \n",
+    "with 72 frame image series.  \n",
+    "- It expects h5 files, primary and lateral root predictions per cylinder.  \n",
+    "- It expects the number of plants per cylinder in the form of a csv with a column   \n",
+    "\"number_of_plants_cylinder\" for each series in the csv, which should be identified by a   \n",
+    "column called \"plant_qr_code\".  \n",
+    "- We also get summary statistics per genotype in this notebook. In order to do this, we  \n",
+    " have a column called \"genotype\" in the input csv."
    ]
   },
   {