Update README.md

README.md

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-# metadata_formatting
-Formatting tif/ome-tif metadata for MCMICRO staging modules
+# phenoimager2
+Formatting PhenoImager .tif output files to be compatible with the MCMCIRO pipeline and ASHLAR.
+
+## Description
+**Raw data:**
+The PhenoImager software outputs one float32 .tif file per tile and cycle containing all channels. The metadata is unstandardized. 
+**Goal:**
+For analysing the data within MCMCIRO (initial registration with ASHLAR), one stacked ome-tif file per channel containing all tiles and cycles is required. 
+**Steps in this module:**
+* Extraction of metadata from unstandardized tif files
+* Creation of stacked and correct ome-tiff files readable for ASHLAR
+* Conversion from float32 to uint16
+* Normalization to max or 99th percentile (user's choice)
+
+## Usage
+
+### CLI
+#### Input
+The CLI script `scripts/phenoimager2mc.py` requires 3 inputs
+* The path to the folder containing all .tif files from one cycle with `-i` or `--input`
+* The number of markers that was used in this cycle with `-m` or `--num_markers`
+* The normalization method that the intensities per cycle should be normalized with. Either 99th or max with `-n` or `--normalization`
+
+#### Output
+* Output .tif file containing all tiles and channels of one cycle with `-o` or `--output`
+
+### Docker usage
+
+If you want to run the module directly from a pre-configured container with all the required packages, you can either build the docker container yourself or pull it from the Github container registry.
+
+To build the container run:
+
+```
+git clone https://github.com/SchapiroLabor/phenoimager2mc.git
+docker build -t phenoimager2mc:latest .
+docker run phenoimager2mc:latest python phenoimager2mc.py
+```
+
+To pull the container from the Github container registry (ghcr.io):
+
+```
+## Login to ghcr.io
+docker login ghcr.io
+
+## Pull container
+docker pull ghcr.io/schapirolabor/phenoimager2mc:latest
+```