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README.md

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 ## Description
 
-```limiric``` is a quality control package for identifying damaged cells in scRNA-seq data. Many existing scRNA-seq quality control packages have highly specialized functions to identify droplets that contain more than one cell or no cells, rather than those that are damaged. Directly addressing which droplets contain damaged cells is often achieved by setting thresholds for metrics such as average mitochondrial gene expression and UMI count. These thresholds, even when dynamically calculated, can vary significantly across samples, tissues of origin, cell types, treatment conditions, and species, resulting in a high probablity of false positive filtering. But searching for true damaged droplets in a sample-specific manner is tedious and non-intuitive and leads to user-defined filtering that lacks reproducibility. 
+```limiric``` is a quality control package for identifying damaged cells in scRNA-seq data. Many existing scRNA-seq quality control packages have highly specialized functions to identify droplets that contain more than one cell or no cells, rather than those that are damaged. Directly addressing which droplets contain damaged cells is often achieved by setting thresholds for metrics such as average mitochondrial gene expression and UMI count. These thresholds, even when dynamically calculated, vary across samples, tissues of origin, cell types, treatment conditions, and species, resulting in a high probablity of false positive filtering. But searching for true damaged droplets in a sample-specific manner is tedious and non-intuitive and leads to user-defined filtering that lacks reproducibility. 
 
 
 ```limiric``` automates the sample-specific detection of damaged cells in one fast acting and highly reproducible function. It operates on the basic principle that damaged and healthy cells are differentiable in lower dimensional space by mitochondrial and ribosomal gene expression and complexity. Here, dimensionality reduction is performed by applying the Louvain clustering algorithm to a shared nearest neighbor graph constructed for each droplet using the full set of genes encoding mitochondrial and ribosomal structure and function.