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index.Rmd
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---
title: "Cyclic Multiplex Fluorescent Immunohistochemistry and Machine Learning Reveal Distinct States of Astrocytes and Microglia in Normal Aging and Alzheimer’s Disease"
description: |
We have developed a methodology of cyclic multiplex fluorescent immunohistochemistry on human postmortem brain sections followed by an image analysis and machine learning pipeline that enables a deep morphological characterization of astrocytes and microglia in the Alzheimer's brain.
site: distill::distill_website
bibliography: glia-ihc-bibliography.bib
csl: https://www.zotero.org/styles/nature-communications
output:
distill::distill_article:
toc: true
---
```{r include = FALSE, eval = FALSE}
# to render website
library(rmarkdown)
library(distill)
render_site()
# to remove files
clean_site()
# requires development distill version
devtools::install_github("rstudio/distill", ref = "csl-fix")
```
# Dependencies
To run our code, please install the following dependencies:
<a href="https://www.r-project.org/" target="_blank" rel="noreferrer noopener"><img src="https://img.shields.io/badge/Language-R-276DC3?style=for-the-badge&logo=r" alt="ayushnoori" align="center"/></a>
<a href="https://imagej.net/" target="_blank" rel="noreferrer noopener"><img src="https://img.shields.io/static/v1?style=for-the-badge&logo=imagej&color=00D8E0&logoColor=white&label=Language&message=ImageJ" alt="ayushnoori" align="center"/></a>
<a href="https://www.python.org/" target="_blank" rel="noreferrer noopener"><img src="https://img.shields.io/badge/Language-Python-3776AB?style=for-the-badge&logo=python" align="center"/></a>
<a href="https://pytorch.org/" target="_blank" rel="noreferrer noopener"><img src="https://img.shields.io/badge/Library-PyTorch-EE4C2C?style=for-the-badge&logo=pytorch" alt="ayushnoori" align="center"/></a>
Additional required libraries are specified in each script. Image segmentation was performed with the FIJI distribution of the open-source Java-based image analysis program ImageJ [@schindelin_fiji_2012; @rueden_imagej2_2017]. Convolutional neural networks (CNN) were constructed using the PyTorch open-source deep learning library in the Python programming language (version 3.8.5) [@paszke_pytorch_2019]. Unless otherwise indicated, all other analyses were performed in the R programming language and statistical computing environment (version 4.1.0).
# Workflow
Please see the analysis workflow below. Click on any icon to be navigated to the appropriate page.
```{r echo = FALSE, results = "asis", layout = "l-body", fig.width = 2}
library(htmltools)
includeHTML("images/flowchart.svg")
```
# Documentation
To read our documented code, please visit [www.serranopozolab.org/glia-ihc](https://www.serranopozolab.org/glia-ihc).
# Code Availability
Our full codebase is available for download on [GitHub](https://github.com/serrano-pozo-lab/glia-ihc).