updated main README

README.md

@@ -14,7 +14,7 @@ In this modified Cell Painting, there are three channels:
 There are two genotypes of the NF1 gene in these cells:
 
 - Wild type (`WT +/+`): In column 6 from the plate (e.g C6, D6, etc.)
-- Heterozygous (`Het +/-`): In column 7 from the plate (e.g C7, D7, etc.)
+- Null (`Null`): In column 7 from the plate (e.g C7, D7, etc.)
 
 It is important to study Schwann cells from NF1 patients because NF1 causes patients to develop neurofibromas, which are red bumps on the skin (tumors) that appear due to the loss of Ras-GAP neurofibromin. 
 This loss occurs when the NF1 gene is mutated (NF1 +/-).
@@ -34,5 +34,6 @@ Once we discover a biomarker from these cells, we hope that our method can be us
 | [1_preprocessing_data](1_preprocessing_data/) | Perform Illumination Correction (IC) | Use `BaSiCPy` to perform IC on images per channel |
 | [2_segmenting_data](2_segmenting_data/) | Segment Objects | Perform segmentation using `Cellpose` and outputing center (x,y) coordinates for each object |
 | [3_extracting_features](3_extracting_features/) | Extract features | Use center (x,y) coordinates in `DeepProfiler` to extract features from all channels |
+| [4_processing_features](4_processing_features/) | Normalize CellProfiler features | Use `Pycytominer` functions to merge and normalize features acquired from CellProfiler |
 | [CellProfiler_pipelines](CellProfiler_pipelines/) | Perform a full pipeline on NF1 data using CellProfiler (from IC to feature extraction) | We run two `CellProfiler` pipelines (1. illumination correction and 2. segmenation and feature extraction) |
-| TBD | TBD | TBD |
+| TBD | TBD | TBD |