docs update

docs/Getting Started.md

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 ## Data Loading and Integration 🔄
 
+SCIMAP operates on segmented single-cell data derived from imaging data using tools such as cellpose or MCMICRO. The essential inputs for SCIMAP are: (a) a single-cell expression matrix and (b) the X and Y coordinates for each cell. Additionally, multi-stack OME-TIFF or TIFF images can be optionally provided to enable visualization of the data analysis on the original raw images.
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 Scimap champions the interoperability of single-cell analysis tools by embracing the `AnnData` data structure. This strategic choice allows seamless use of numerous single-cell analysis utilities alongside `AnnData`.
 
 ### The AnnData Framework 🧬

docs/index.md

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 Scimap is a scalable toolkit for analyzing spatial molecular data. The underlying framework is generalizable to spatial datasets mapped to XY coordinates. The package uses the [anndata](https://anndata.readthedocs.io/en/stable/anndata.AnnData.html) framework making it easy to integrate with other popular single-cell analysis toolkits. It includes preprocessing, phenotyping, visualization, clustering, spatial analysis and differential spatial testing. The Python-based implementation efficiently deals with large datasets of millions of cells.
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+SCIMAP operates on segmented single-cell data derived from imaging data using tools such as cellpose or MCMICRO. The essential inputs for SCIMAP are: (a) a single-cell expression matrix and (b) the X and Y coordinates for each cell. Additionally, multi-stack OME-TIFF or TIFF images can be optionally provided to enable visualization of the data analysis on the original raw images.
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