Session 9: How to apply the classification algorithm to your data

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## Session 9: How to apply the classification algorithm to your data

### Dr Shazia Ruybal-Pesántez  
Presented at the [covidClassifyR Shiny app workshop](https://shaziaruybal.github.io/covidClassifyR-workshop) for researchers from PNGIMR and partner institutions

2022-03-17

---
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## Recap

#### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M400 480H48c-26.51 0-48-21.49-48-48V80c0-26.51 21.49-48 48-48h352c26.51 0 48 21.49 48 48v352c0 26.51-21.49 48-48 48zm-204.686-98.059l184-184c6.248-6.248 6.248-16.379 0-22.627l-22.627-22.627c-6.248-6.248-16.379-6.249-22.628 0L184 302.745l-70.059-70.059c-6.248-6.248-16.379-6.248-22.628 0l-22.627 22.627c-6.248 6.248-6.248 16.379 0 22.627l104 104c6.249 6.25 16.379 6.25 22.628.001z"/></svg> **[Session 1](https://shaziaruybal.github.io/covidClassifyR-workshop/sessions/2022-03-10-session1/index.html)** gave you an overview of the Luminex technology and the COVID-19 multi-antigen serological assay that was established in PNG

#### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M400 480H48c-26.51 0-48-21.49-48-48V80c0-26.51 21.49-48 48-48h352c26.51 0 48 21.49 48 48v352c0 26.51-21.49 48-48 48zm-204.686-98.059l184-184c6.248-6.248 6.248-16.379 0-22.627l-22.627-22.627c-6.248-6.248-16.379-6.249-22.628 0L184 302.745l-70.059-70.059c-6.248-6.248-16.379-6.248-22.628 0l-22.627 22.627c-6.248 6.248-6.248 16.379 0 22.627l104 104c6.249 6.25 16.379 6.25 22.628.001z"/></svg> **[Session 2](https://shaziaruybal.github.io/covidClassifyR-workshop/sessions/2022-03-10-session2/index.html)** gave you an overview of the purpose of serosurveillance and insights into the COVID-19 sero-surveys that have been carried out in PNG 
--

#### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M400 480H48c-26.51 0-48-21.49-48-48V80c0-26.51 21.49-48 48-48h352c26.51 0 48 21.49 48 48v352c0 26.51-21.49 48-48 48zm-204.686-98.059l184-184c6.248-6.248 6.248-16.379 0-22.627l-22.627-22.627c-6.248-6.248-16.379-6.249-22.628 0L184 302.745l-70.059-70.059c-6.248-6.248-16.379-6.248-22.628 0l-22.627 22.627c-6.248 6.248-6.248 16.379 0 22.627l104 104c6.249 6.25 16.379 6.25 22.628.001z"/></svg> **[Session 3](https://shaziaruybal.github.io/covidClassifyR-workshop/sessions/2022-03-10-session3/index.html)** gave you an overview of the [`covidClassifyR`](https://shaziaruybal.shinyapps.io/covidclassifyr) Shiny app

#### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M400 480H48c-26.51 0-48-21.49-48-48V80c0-26.51 21.49-48 48-48h352c26.51 0 48 21.49 48 48v352c0 26.51-21.49 48-48 48zm-204.686-98.059l184-184c6.248-6.248 6.248-16.379 0-22.627l-22.627-22.627c-6.248-6.248-16.379-6.249-22.628 0L184 302.745l-70.059-70.059c-6.248-6.248-16.379-6.248-22.628 0l-22.627 22.627c-6.248 6.248-6.248 16.379 0 22.627l104 104c6.249 6.25 16.379 6.25 22.628.001z"/></svg> **[Session 4](https://shaziaruybal.github.io/covidClassifyR-workshop/sessions/2022-03-11-session4/index.html)** gave you an overview of how to prepare and import your data to the [`covidClassifyR`](https://shaziaruybal.shinyapps.io/covidclassifyr) Shiny app

#### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M400 480H48c-26.51 0-48-21.49-48-48V80c0-26.51 21.49-48 48-48h352c26.51 0 48 21.49 48 48v352c0 26.51-21.49 48-48 48zm-204.686-98.059l184-184c6.248-6.248 6.248-16.379 0-22.627l-22.627-22.627c-6.248-6.248-16.379-6.249-22.628 0L184 302.745l-70.059-70.059c-6.248-6.248-16.379-6.248-22.628 0l-22.627 22.627c-6.248 6.248-6.248 16.379 0 22.627l104 104c6.249 6.25 16.379 6.25 22.628.001z"/></svg> **[Session 5](https://shaziaruybal.github.io/covidClassifyR-workshop/sessions/2022-03-11-session5/index.html)** gave you an overview of how to prepare your data and upload your data to the [`covidClassifyR`](https://shaziaruybal.shinyapps.io/covidclassifyr) app

#### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M400 480H48c-26.51 0-48-21.49-48-48V80c0-26.51 21.49-48 48-48h352c26.51 0 48 21.49 48 48v352c0 26.51-21.49 48-48 48zm-204.686-98.059l184-184c6.248-6.248 6.248-16.379 0-22.627l-22.627-22.627c-6.248-6.248-16.379-6.249-22.628 0L184 302.745l-70.059-70.059c-6.248-6.248-16.379-6.248-22.628 0l-22.627 22.627c-6.248 6.248-6.248 16.379 0 22.627l104 104c6.249 6.25 16.379 6.25 22.628.001z"/></svg> **[Session 6](https://shaziaruybal.github.io/covidClassifyR-workshop/sessions/2022-03-11-session6/index.html)** gave you an overview of how to download your processed data and quality control report

#### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M400 480H48c-26.51 0-48-21.49-48-48V80c0-26.51 21.49-48 48-48h352c26.51 0 48 21.49 48 48v352c0 26.51-21.49 48-48 48zm-204.686-98.059l184-184c6.248-6.248 6.248-16.379 0-22.627l-22.627-22.627c-6.248-6.248-16.379-6.249-22.628 0L184 302.745l-70.059-70.059c-6.248-6.248-16.379-6.248-22.628 0l-22.627 22.627c-6.248 6.248-6.248 16.379 0 22.627l104 104c6.249 6.25 16.379 6.25 22.628.001z"/></svg> **[Session 7](https://shaziaruybal.github.io/covidClassifyR-workshop/sessions/2022-03-17-session7/index.html)** gave a recap of how to QC your data

#### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M400 480H48c-26.51 0-48-21.49-48-48V80c0-26.51 21.49-48 48-48h352c26.51 0 48 21.49 48 48v352c0 26.51-21.49 48-48 48zm-204.686-98.059l184-184c6.248-6.248 6.248-16.379 0-22.627l-22.627-22.627c-6.248-6.248-16.379-6.249-22.628 0L184 302.745l-70.059-70.059c-6.248-6.248-16.379-6.248-22.628 0l-22.627 22.627c-6.248 6.248-6.248 16.379 0 22.627l104 104c6.249 6.25 16.379 6.25 22.628.001z"/></svg> **[Session 8](https://shaziaruybal.github.io/covidClassifyR-workshop/sessions/2022-03-17-session8/index.html)** gave you an overview of the classification algorithm

--
.footnote[
.bottom[
For all the workshop materials see the [workshop website <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M432,320H400a16,16,0,0,0-16,16V448H64V128H208a16,16,0,0,0,16-16V80a16,16,0,0,0-16-16H48A48,48,0,0,0,0,112V464a48,48,0,0,0,48,48H400a48,48,0,0,0,48-48V336A16,16,0,0,0,432,320ZM488,0h-128c-21.37,0-32.05,25.91-17,41l35.73,35.73L135,320.37a24,24,0,0,0,0,34L157.67,377a24,24,0,0,0,34,0L435.28,133.32,471,169c15,15,41,4.5,41-17V24A24,24,0,0,0,488,0Z"/></svg>](https://shaziaruybal.github.io/covidClassifyR-workshop/materials.html) 
]]

---

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# <svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M96 64h448v352h64V40c0-22.06-17.94-40-40-40H72C49.94 0 32 17.94 32 40v376h64V64zm528 384H480v-64H288v64H16c-8.84 0-16 7.16-16 16v32c0 8.84 7.16 16 16 16h608c8.84 0 16-7.16 16-16v-32c0-8.84-7.16-16-16-16z"/></svg>
# Today we will cover:

--
### How to apply the algorithm to your data

### How to download your classification data

### You can find the app [here <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M432,320H400a16,16,0,0,0-16,16V448H64V128H208a16,16,0,0,0,16-16V80a16,16,0,0,0-16-16H48A48,48,0,0,0,0,112V464a48,48,0,0,0,48,48H400a48,48,0,0,0,48-48V336A16,16,0,0,0,432,320ZM488,0h-128c-21.37,0-32.05,25.91-17,41l35.73,35.73L135,320.37a24,24,0,0,0,0,34L157.67,377a24,24,0,0,0,34,0L435.28,133.32,471,169c15,15,41,4.5,41-17V24A24,24,0,0,0,488,0Z"/></svg>](https://shaziaruybal.shinyapps.io/covidClassifyR)

---

## <svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M640 264v-16c0-8.84-7.16-16-16-16H344v-40h72c17.67 0 32-14.33 32-32V32c0-17.67-14.33-32-32-32H224c-17.67 0-32 14.33-32 32v128c0 17.67 14.33 32 32 32h72v40H16c-8.84 0-16 7.16-16 16v16c0 8.84 7.16 16 16 16h104v40H64c-17.67 0-32 14.33-32 32v128c0 17.67 14.33 32 32 32h160c17.67 0 32-14.33 32-32V352c0-17.67-14.33-32-32-32h-56v-40h304v40h-56c-17.67 0-32 14.33-32 32v128c0 17.67 14.33 32 32 32h160c17.67 0 32-14.33 32-32V352c0-17.67-14.33-32-32-32h-56v-40h104c8.84 0 16-7.16 16-16zM256 128V64h128v64H256zm-64 320H96v-64h96v64zm352 0h-96v-64h96v64z"/></svg> Classify your data

.panelset.sideways[

.panel[.panel-name[Upload your data files]

]

.panel[.panel-name[Select the algorithm]

.pull-left[

The PNG algorithm should be used for data generated using the COVID-19 Luminex assay established at PNGIMR

_*Note: the ability to upload already processed data is in development, for now you must upload raw data and your plate layout in order to run the classification algorithm on your data_

]

.pull-right[

![](img/classification_select.png)

]
]

.panel[.panel-name[Check your classification data]

**<svg aria-hidden="true" role="img" viewBox="0 0 352 512" style="height:1em;width:0.69em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M96.06 454.35c.01 6.29 1.87 12.45 5.36 17.69l17.09 25.69a31.99 31.99 0 0 0 26.64 14.28h61.71a31.99 31.99 0 0 0 26.64-14.28l17.09-25.69a31.989 31.989 0 0 0 5.36-17.69l.04-38.35H96.01l.05 38.35zM0 176c0 44.37 16.45 84.85 43.56 115.78 16.52 18.85 42.36 58.23 52.21 91.45.04.26.07.52.11.78h160.24c.04-.26.07-.51.11-.78 9.85-33.22 35.69-72.6 52.21-91.45C335.55 260.85 352 220.37 352 176 352 78.61 272.91-.3 175.45 0 73.44.31 0 82.97 0 176zm176-80c-44.11 0-80 35.89-80 80 0 8.84-7.16 16-16 16s-16-7.16-16-16c0-61.76 50.24-112 112-112 8.84 0 16 7.16 16 16s-7.16 16-16 16z"/></svg> Tip:** Make sure that your data was processed using the correct algorithm by cross-checking the “Algorithm choice”, which will display the algorithm that was applied.
]

.panel[.panel-name[Download your classification data]

You can download your classification data, by navigating to the "Download data" tab. Make sure that you click on the correct button depending on the algorithm you applied to your data.

![](img/download.png)

**<svg aria-hidden="true" role="img" viewBox="0 0 352 512" style="height:1em;width:0.69em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M96.06 454.35c.01 6.29 1.87 12.45 5.36 17.69l17.09 25.69a31.99 31.99 0 0 0 26.64 14.28h61.71a31.99 31.99 0 0 0 26.64-14.28l17.09-25.69a31.989 31.989 0 0 0 5.36-17.69l.04-38.35H96.01l.05 38.35zM0 176c0 44.37 16.45 84.85 43.56 115.78 16.52 18.85 42.36 58.23 52.21 91.45.04.26.07.52.11.78h160.24c.04-.26.07-.51.11-.78 9.85-33.22 35.69-72.6 52.21-91.45C335.55 260.85 352 220.37 352 176 352 78.61 272.91-.3 175.45 0 73.44.31 0 82.97 0 176zm176-80c-44.11 0-80 35.89-80 80 0 8.84-7.16 16-16 16s-16-7.16-16-16c0-61.76 50.24-112 112-112 8.84 0 16 7.16 16 16s-7.16 16-16 16z"/></svg> Tip:** The downloaded .csv file will include the algorithm in the file name, which you can also cross-check to make sure the appropriate algorithm was applied to classify the data.
]

]

---
# <svg aria-hidden="true" role="img" viewBox="0 0 576 512" style="height:1em;width:1.12em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M542.22 32.05c-54.8 3.11-163.72 14.43-230.96 55.59-4.64 2.84-7.27 7.89-7.27 13.17v363.87c0 11.55 12.63 18.85 23.28 13.49 69.18-34.82 169.23-44.32 218.7-46.92 16.89-.89 30.02-14.43 30.02-30.66V62.75c.01-17.71-15.35-31.74-33.77-30.7zM264.73 87.64C197.5 46.48 88.58 35.17 33.78 32.05 15.36 31.01 0 45.04 0 62.75V400.6c0 16.24 13.13 29.78 30.02 30.66 49.49 2.6 149.59 12.11 218.77 46.95 10.62 5.35 23.21-1.94 23.21-13.46V100.63c0-5.29-2.62-10.14-7.27-12.99z"/></svg> Your homework for next time

### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M400 480H48c-26.51 0-48-21.49-48-48V80c0-26.51 21.49-48 48-48h352c26.51 0 48 21.49 48 48v352c0 26.51-21.49 48-48 48zm-204.686-98.059l184-184c6.248-6.248 6.248-16.379 0-22.627l-22.627-22.627c-6.248-6.248-16.379-6.249-22.628 0L184 302.745l-70.059-70.059c-6.248-6.248-16.379-6.248-22.628 0l-22.627 22.627c-6.248 6.248-6.248 16.379 0 22.627l104 104c6.249 6.25 16.379 6.25 22.628.001z"/></svg> Try to import the raw data and explore the "Classification" tab

---
class: inverse, middle, center

# <svg aria-hidden="true" role="img" viewBox="0 0 384 512" style="height:1em;width:0.75em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M336 64h-80c0-35.3-28.7-64-64-64s-64 28.7-64 64H48C21.5 64 0 85.5 0 112v352c0 26.5 21.5 48 48 48h288c26.5 0 48-21.5 48-48V112c0-26.5-21.5-48-48-48zM192 40c13.3 0 24 10.7 24 24s-10.7 24-24 24-24-10.7-24-24 10.7-24 24-24zm121.2 231.8l-143 141.8c-4.7 4.7-12.3 4.6-17-.1l-82.6-83.3c-4.7-4.7-4.6-12.3.1-17L99.1 285c4.7-4.7 12.3-4.6 17 .1l46 46.4 106-105.2c4.7-4.7 12.3-4.6 17 .1l28.2 28.4c4.7 4.8 4.6 12.3-.1 17z"/></svg>

## Next session:

### How to visualize your data in the [`covidClassifyR`](https://shaziaruybal.shinyapps.io/covidclassifyr) app

---

# Acknowledgments

- Dr Maria Ome-Kaius and Dr Fiona Angrisano
- PNGIMR and partner institutions
- WEHI & Burnet Institute
- All of you for attending!

*We are extremely grateful for financial support to develop and host the covidClassifyR Shiny web application, and to host these virtual workshops through the [Regional Collaborations Programme COVID-19 Digital Grant](https://www.science.org.au/news-and-events/news-and-media-releases/regional-research-set-get-digital-boost) from the Australian Academy of Science and Australian Department of Industry, Science, Energy and Resources.*

The scripts and functions used in [`covidClassifyR`](https://shaziaruybal.shinyapps.io/covidclassifyr) were developed by Shazia Ruybal-Pesántez, with contributions from the following researchers: Eamon Conway, Connie Li Wan Suen, Narimane Nekkab and Michael White.

.footnote[
_These slides were created using the R packages:  
[xaringan](https://github.com/yihui/xaringan), 
[xaringanthemer](https://github.com/gadenbuie/xaringanthemer), 
[xaringanExtra](https://github.com/gadenbuie/xaringanExtra)_ 
]

---
name: contact
class: inverse

.pull-left[
.center[
### Dr Shazia Ruybal-Pesántez

#### Contact details

[<svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 17.4 52.1 39.5 154.1 113.6 21.1 15.4 56.7 47.8 92.2 47.6 35.7.3 72-32.8 92.3-47.6 102-74.1 131.6-96.3 154-113.7zM256 320c23.2.4 56.6-29.2 73.4-41.4 132.7-96.3 142.8-104.7 173.4-128.7 5.8-4.5 9.2-11.5 9.2-18.9v-19c0-26.5-21.5-48-48-48H48C21.5 64 0 85.5 0 112v19c0 7.4 3.4 14.3 9.2 18.9 30.6 23.9 40.7 32.4 173.4 128.7 16.8 12.2 50.2 41.8 73.4 41.4z"/></svg> ruybal.s@wehi.edu.au](mailto:ruybal.s@wehi.edu.au)  
[<svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg> @DrShaziaRuybal](https://twitter.com/DrShaziaRuybal)

]]

.pull-right[

### Session 9 Resources:

### [<i class="fab  fa-youtube "></i> Recording](https://youtu.be/LDihJvJZ3MQ)  
### [<i class="fas  fa-laptop-code "></i> `covidClassifyR`](https://shaziaruybal.shinyapps.io/covidClassifyR)  
### [<svg aria-hidden="true" role="img" viewBox="0 0 496 512" style="height:1em;width:0.97em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"/></svg> Workshop materials](https://shaziaruybal.github.io/covidClassifyR-workshop/materials.html)  
### [<svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M464 448H48c-26.51 0-48-21.49-48-48V112c0-26.51 21.49-48 48-48h416c26.51 0 48 21.49 48 48v288c0 26.51-21.49 48-48 48zM112 120c-30.928 0-56 25.072-56 56s25.072 56 56 56 56-25.072 56-56-25.072-56-56-56zM64 384h384V272l-87.515-87.515c-4.686-4.686-12.284-4.686-16.971 0L208 320l-55.515-55.515c-4.686-4.686-12.284-4.686-16.971 0L64 336v48z"/></svg> Slides for Session 9](https://shaziaruybal.github.io/covidClassifyR-workshop/slides/session7/session9_slides.html)
]

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# <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M504 256c0 136.997-111.043 248-248 248S8 392.997 8 256C8 119.083 119.043 8 256 8s248 111.083 248 248zM262.655 90c-54.497 0-89.255 22.957-116.549 63.758-3.536 5.286-2.353 12.415 2.715 16.258l34.699 26.31c5.205 3.947 12.621 3.008 16.665-2.122 17.864-22.658 30.113-35.797 57.303-35.797 20.429 0 45.698 13.148 45.698 32.958 0 14.976-12.363 22.667-32.534 33.976C247.128 238.528 216 254.941 216 296v4c0 6.627 5.373 12 12 12h56c6.627 0 12-5.373 12-12v-1.333c0-28.462 83.186-29.647 83.186-106.667 0-58.002-60.165-102-116.531-102zM256 338c-25.365 0-46 20.635-46 46 0 25.364 20.635 46 46 46s46-20.636 46-46c0-25.365-20.635-46-46-46z"/></svg> Questions?