Update README.md

README.md

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 # Google Colab interface to HDStIM (High Dimensional Stimulation Immune Mapping)
 
 ## Abstract
-HDStIM is a method for identifying responses to experimental stimulation in mass or flow cytometry that uses high dimensional analysis of measured parameters and can be performed with an end-to-end unsupervised approach. In the context of in vitro stimulation assays where high-parameter cytometry was used to monitor intracellular response markers, using cell populations annotated either through automated clustering or manual gating for a combined set of stimulated and unstimulated samples, 'HDStIM' labels cells as responding or non-responding. The package also provides auxiliary functions to rank intracellular markers based on their contribution to identifying responses and generating diagnostic plots. Documentation website: https://niaid.github.io/HDStIM/ Source code: https://github.com/niaid/HDStIM/ CRAN page: https://cran.r-project.org/package=HDStIM
+HDStIM is a method for identifying responses to experimental stimulation in mass or flow cytometry that uses high dimensional analysis of measured parameters and can be performed with an end-to-end unsupervised approach. In the context of in vitro stimulation assays where high-parameter cytometry was used to monitor intracellular response markers, using cell populations annotated either through automated clustering or manual gating for a combined set of stimulated and unstimulated samples, 'HDStIM' labels cells as responding or non-responding. The package also provides auxiliary functions to rank intracellular markers based on their contribution to identifying responses and generating diagnostic plots. 
 
 ![](ColabHDStIM.png)
 *Figure 1. Schematic outline for the use of multiple response markers by HDStIM to identify cells with a responding phenotype from unstimulated and stimulated experimental samples for a given stimulation - cell population combination.*
 
 ## Colab notebook
-This notebook is an attempt to make it easier to use HDStIM. However, since it runs on [Google Colab](https://research.google.com/colaboratory/faq.html), it has its limitations. For example, uploading a large dataset is very slow and may not be straightforward. Also, the marker ranking function that utilizes multiple cores may be orders of magnitude slower than on a local machine with more than two cores. See the more information section at the bottom of the notebook on how to run this notebook locally (recommended).
+This notebook is an attempt to make it easier to use HDStIM. However, since it runs on Google Colab, it has its limitations. For example, uploading a large dataset is very slow and may not be straightforward. Also, the marker ranking function that utilizes multiple cores may be orders of magnitude slower than on a local machine with more than two cores. See the more information section at the bottom of the notebook on how to run this notebook locally (recommended).
 
 
 | Notebook | Link |
@@ -17,6 +17,11 @@ This notebook is an attempt to make it easier to use HDStIM. However, since it r
 *Note: Under default settings, the notebook should be able to run an example dataset.*
 
 ## Helpful links
-1. [Google Colab Frequently Asked Questions](https://research.google.com/colaboratory/faq.html)
-2. [Welcome to Colab!](https://colab.research.google.com/)
-3. [Practical Introduction to Google Colab for Data Science (YouTube video)](https://www.youtube.com/watch?v=oCngVVBSsmA)
+1. HDStIM related
+   1. Documentation website: [https://niaid.github.io/HDStIM/](https://niaid.github.io/HDStIM/) 
+   2. Source code: [https://github.com/niaid/HDStIM/](https://github.com/niaid/HDStIM/) 
+   3. CRAN page: [https://cran.r-project.org/package=HDStIM](https://cran.r-project.org/package=HDStIM)
+2. Google colab related
+   1. [Google Colab frequently asked questions](https://research.google.com/colaboratory/faq.html)
+   2. [Welcome to Colab!](https://colab.research.google.com/)
+   3. [Practical introduction to Google Colab for data science (YouTube video)](https://www.youtube.com/watch?v=oCngVVBSsmA)