update README

Author: deto

README.md

@@ -1,6 +1,40 @@
 # scTransformPy
 A Python implementation of of the scTransform method
 
-Based on https://github.com/ChristophH/sctransform originally by Christoph Hafemeister
+Based on the R package [sctransform](https://github.com/ChristophH/sctransform) originally by Christoph Hafemeister
 
-[Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. bioRxiv 576827 (2019). doi:10.1101/576827](https://www.biorxiv.org/content/10.1101/576827v1)
+- [Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. bioRxiv 576827 (2019). doi:10.1101/576827](https://www.biorxiv.org/content/10.1101/576827v1)
+
+Currently this supports basic functionality - variance stabilizing transform of UMI count data based on a general linear model and kernel-regularized parameters.
+
+## Installation
+
+```
+pip install git+https://github.com/deto/scTransformPy.git
+```
+
+## Usage
+
+```
+import scTransform
+
+residuals = scTransform.vst(
+    umi, latent_var=['log_umi'], cell_attr
+)
+```
+
+## Feature comparison with original R package
+
+Supported:
+
+- cell\_attr
+- latent\_var
+
+Unsupported:
+
+- batch variables (batch\_var)
+- non-regularized latent variables (latent\_var\_nonreg)
+- gene sub-sampling (n\_genes)
+- cell sub-sampling (n\_cells)
+- alternate GLM fitting procedures (only the default, method="poisson" supported)
+- sparse input umi matrix