Update README.md

README.md

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 # callback (Calibrated Clustering via Knockoffs) <img src="man/figures/callback_logo.png" align="right" alt="" width="120"/>
 
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 ## Introduction
 
 Standard single-cell RNA-sequencing (scRNA-seq) pipelines nearly always include unsupervised clustering as a key step in identifying biologically distinct cell types. A follow-up step in these pipelines is to test for differential expression between the identified clusters. When algorithms over-cluster, downstream analyses will produce inflated P-values resulting in increased false discoveries. Here, we present `callback` (Calibrated Clustering via Knockoffs): a new method for protecting against over-clustering by controlling for the impact of double-dipping. Importantly, our approach can be applied to any clustering algorithm (implemented here are the Louvain, Leiden, K-means, and hierarchical clustering algorithms). `callback` provides state-of-the-art clustering performance and can rapidly analyze large-scale scRNA-seq studies, even on a personal laptop.
 
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 ## Installation
 
 You can install the lastest development version by using the [devtools](https://CRAN.R-project.org/package=devtools) library. To install this package with devtools, use this command:
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 devtools::install_github("lcrawlab/callback")
 ```
 
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 ## Tutorial
 
 ```r
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 library(callback)
 
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 set.seed(123)
 
 # load pbmc3k dataset
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 ## Questions and Feedback
 For questions or concerns with `callback`, please contact
 [Alan DenAdel](mailto:[email protected]) or [Lorin Crawford]([email protected]). Any feedback on the software, manuscript, and tutorials is appreciated.
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