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-# Breast_cancer_DigitalMicrofluidics
-**Studying Breast Cancer Invasion by Separating Invading and Non-Invading Cells on Digital Microfluidic Device"
+# Cell Invasion in Digital Microfluidic Microgel Systems
+Using digital microfluidics, complex matrices mimicing basement membranes that breast cancer cells invade into were made and breast cancer cells invading these matrices were studied first by using immunohistochemistry and then by performing RNA-seq on specific fractions relating to the breast cancer cells invading into the matrix and the cells residing at the matrix interface.  This is a study of breast cancer cell invasion that probes transcriptomes of invading versus non-invading cells in a 3D matrix created on a digital microfluidic device.
 
-Using digital microfluidics, complex matrices mimicing basement membranes that breast cancer cells invade into were made and breast cancer cells invading these matrices were studied first by using immunohistochemistry and then by performing RNA-seq on specific fractions relating to the breast cancer cells invading into the matrix and the cells residing at the matrix interface.
+## Getting Started
+This RNA-seq pipeline works through normalizing then comparing invading vs non-invading cell populations extracted using this wet lab pipeline (Li et al, 2020) and includes the software pipeline used to look for differentially expressed genes using edgeR and gene correlations using WGCNA.  Other data visualizations include dimensionality reduction using UMAP and T-SNE and hierarchial cluster and visualizations using heatmap.2 from the gplots package.
+Again, further details and interpretation of this data can be found in the publication:
 
-This RNA-seq data reflects the invading vs non-invading cell populations extracted using this wet lab pipeline and includes the software pipeline used to look for differentially expressed genes using edgeR and gene correlations using WGCNA.  Other data visualizations include dimensionality reduction using UMAP and T-SNE and hierarchial cluster and visualizations using heatmap.2 from the gplots package.
+### Prerequisites
 
-Further details and interpretation of this data can be found in the publication:
+#### General Workflow
+
+#####