---
title: "Zheng MZ Lab"
output: 
  flexdashboard::flex_dashboard:
    storyboard: true
    social: menu
    source: embed
---


```{r setup, include=FALSE}
library(flexdashboard)
```
<style>
/* 缩小三级标题区域高度 */
section > h3 {
  font-size: 1rem !important;
  margin-top: 0.25em !important;
  margin-bottom: 0.25em !important;
  line-height: 1.1 !important;
}
</style>
### HOME

```{r}  
knitr::include_graphics("pic/home-1.png")  
```

***

https://rstudio.github.io/leaflet/

- Interactive panning/zooming

- Compose maps using arbitrary combinations of map tiles, markers, polygons, lines, popups, and GeoJSON.

- Create maps right from the R console or RStudio

- Embed maps in knitr/R Markdown documents and Shiny apps

- Easily render Spatial objects from the sp package, or data frames with latitude/longitude columns

- Use map bounds and mouse events to drive Shiny logic


### RESEARCH

```{r}
#install.packages("ComplexHeatmap")
library(ComplexHeatmap)

# Example usage
Heatmap(as.matrix(mtcars))
```

***

https://github.com/rstudio/d3heatmap/

- Highlight rows/columns by clicking axis labels

- Click and drag over colormap to zoom in (click on colormap to zoom out)

- Optional clustering and dendrograms, courtesy of base::heatmap


### TEACHING

```{r}
library(dygraphs)
lungDeaths <- cbind(mdeaths, fdeaths)
dygraph(lungDeaths, main = "Deaths from Lung Diseases in the UK") %>%
  dySeries("mdeaths", label = "Male") %>%
  dySeries("fdeaths", label = "Female") %>%
  dyOptions(stackedGraph = TRUE) %>%
  dyRangeSelector(height = 20) %>% 
  dyRangeSelector()
```

***

https://rstudio.github.io/dygraphs/

- Automatically plots xts time series objects (or any object convertible to xts).

- Highly configurable axis and series display (including optional second Y-axis).

- Rich interactive features including zoom/pan and series/point highlighting.

- Display upper/lower bars (e.g. prediction intervals) around series.
- Various graph overlays including shaded regions, event lines, and point annotations.


### PUBLICATIONS

```{r}
library(plotly)
p <- ggplot(data = diamonds, aes(x = cut, fill = clarity)) +
            geom_bar(position = "dodge")
ggplotly(p)
```

***

https://plot.ly/ggplot2/

If you use ggplot2, `ggplotly()` converts your plots to an interactive, web-based version! It also provides sensible tooltips, which assists decoding of values encoded as visual properties in the plot.

plotly supports some chart types that ggplot2 doesn't (such as 3D surface, point, and line plots). You can create these (or any other plotly) charts using `plot_ly()`.


### MEMBERS

```{r}
library(metricsgraphics)
mjs_plot(mtcars, x=wt, y=mpg) %>%
  mjs_point(color_accessor=carb, size_accessor=carb) %>%
  mjs_labs(x="Weight of Car", y="Miles per Gallon")
```

***

https://hrbrmstr.github.io/metricsgraphics/

Building metricsgraphics charts follows the “piping” idiom made popular through the magrittr, ggvis and dplyr packages. This makes it possible to avoid one giant function with a ton of parameters and facilitates breaking out the chart building into logical steps. 

While MetricsGraphics.js charts may not have the flexibility of ggplot2, you can build functional, interactive [multi-]line, scatterplot, bar charts & histograms and + even link charts together.


### RESOURCE

```{r}
library(metricsgraphics)
mjs_plot(mtcars, x=wt, y=mpg) %>%
  mjs_point(color_accessor=carb, size_accessor=carb) %>%
  mjs_labs(x="Weight of Car", y="Miles per Gallon")
```
***

https://hrbrmstr.github.io/metricsgraphics/

Building metricsgraphics charts follows the “

### JOIN US


```{r}
library(metricsgraphics)
mjs_plot(mtcars, x=wt, y=mpg) %>%
  mjs_point(color_accessor=carb, size_accessor=carb) %>%
  mjs_labs(x="Weight of Car", y="Miles per Gallon")
```
***

https://hrbrmstr.github.io/metricsgraphics/

Building metricsgraphics charts follows the “