---
# System prepended metadata

title: ReproHack

---

# ReproHack
*A collaborative effort on reproducible data analysis*

----

## 1. First things first

**Code of conduct:** As all ReproHack events, we strive to make this event open and inclusive to all. As such the event is governed by the [ReproHack Code of Conduct](https://github.com/reprohack/reprohack-hq/blob/master/CODE_OF_CONDUCT.md) and you should read it before participating. By participating, you are expected to uphold this code.

**Authors:** We encourage authors to be available for participants to reach out to for guidance or even just to say hello!

**Communication:** via Discord: https://discord.gg/usZbfm6. Install the app for proper functionality. 

**Participants**
Please sign in (Affiliation)
```
- Tuur Muyldermans (VIB Bioinformatics Core / ELIXIR Belgium)
- Alexander Botzki (VIB Bioinformatics Core / ELIXIR Belgium)
- Jordy De Coninck (IRC-VIB University of Ghent Unit Geert Berx)
    single cell analysis, Rmd, scripts and pipelines, R main language
    github for documentation of code for analysis, reproduce figures? 
- Sam Dupont (IRC-VIB Unit Bart Lambrecht-Hamida Hammad)
    single cell analysis, RNA bulk analysis, R, some bash, try to answer 
    the questions from researchers - here is a pubmed entry 
- Surya Gupta (UGent-VIB, Belgium)
    compomics group, Python, quick plots with R, github, how do you put data
    and code out - look at good or less good examples who published data and 
    codes before
- Tereza Lausova (DKFZ Heidelberg, DE)
    bioinformatics tool, microarrays, R, bash, learn how to use guidelines,
    do it right from the start
- Elena Eyre (IDIBAPS, Barcelona, Spain)
    computational lab hypothalamus and obesity, sequencing analysis, 
    RNA and DNA, R, some Python, Linux, worried to upload data to github,  
    looking for guidelines, how to do it right from the start  
- Liesbet Martens (IRC-VIB, Belgium)
    single cell, R, packrat, jupyter notebooks, github for tools, 
    structure for data analysis is difficult to obtain, see how docker can fit
    the reproducible data analysis
```


## 2. Organisation



**1. Paper review**
- Have a look at the papers available for reproduction on the [hackmd](https://hackmd.io/o3GZZhRORCOq6HGOLkyg3A). 

**2. Project registration and team formation**
- Feel free to work on your own if you prefer, but 
- We highly recommend to work together and discuss your experiences with fellow participants as you work.
- Register your project & team: add your details to the [hackmd](https://hackmd.io/o3GZZhRORCOq6HGOLkyg3A)

**3. Reprohack!**
- Follow any instructions/documentation associated with the papers and try and reproduce the data analysis. 
- As you work through your paper, keep in mind the following points: Findability, Accessibility, Reproducibility, Documentation and Reusability.
- We encourage you to use the event hackpad to record general findings you wish to share with everyone. 

**4. Mid-point regroup**
- Which paper have you selected? Briefly describe what it's about.
- Briefly describe the approach to reproducibility the paper has taken.
- Anything in particular you like about the paper's approach so far?
- Anything you're having difficulty with? Maybe there is someone that can help you?

**5. Feedback to the authors**
- Complete the [feedback form](https://forms.gle/uHxV588JztGuiB887) for the authors of the paper
- We expect that any feedback and criticism on authors’ work is expressed in a constructive, friendly and respectful manner.


**6. Final regroup**
- How was it? Any final comments?
- What will you take home? 
- If there's time, tackle some discussion topics from the hackmd
- Feedback for the organizers. 

**Additional activities**: 
You might want to consider attempting to replicate the results, for example, if the code is in R consider translating the analysis to python and examining whether you are getting the same results. Such a contribution would be appropriate for publication in the ReScience C journal! Have a look at the journals website for further details.

Should you finish reproducing your paper quickly, feel free to explore the work more deeply. For example, you could try and run additional analyses, create new plots or even combine materials with your own or other open materials available on the web!

Should you produce any additional materials relating to your reproduction during the session, we ask that you share it publicly and add any links to such materials to the hackpad.

## 3. List of proposed papers
On our GitHub: 

Additional inspiration: 
- https://sheffield-university.shinyapps.io/ReproHack_CCMcr/
- https://reprohacknl.github.io/ReproHack/

## 4. Teams

**Team 1**  
Paper: Assessing sub-cellular resolution in spatial proteomics experiments.   
Members:  
Hack-link: https://hackmd.io/1DyJqyHmSxyp299UvgWbOw

**Team 2**  
Paper: A single-cell atlas of mouse brain macrophages reveals unique transcriptional identities shaped by ontogeny and tissue environment.  
Members: Tuur Muyldermans, Tereza Lausová, Elena Eyre  
Hack-link: https://hackmd.io/bkxqBdQwSyubo74AfAQCIA


**Team 3**  
Paper: Profiling peripheral nerve macrophages reveals two macrophage subsets with distinct localization, transcriptome and response to injury.  
Members: Jordy De Coninck, Sam Dupont 
Hack-link: https://hackmd.io/Nm9vyrnrRl28FjW98M1BaQ

**Team 4**  
Paper: Addressing the pooled amplification paradox with unique molecular identifiers in single-cell RNA-seq.  
Members: Liesbet Martens, Surya Gupta 
Hack-link: https://hackmd.io/b5wRqX8uTxqe9cfWAAvFGQ

**Team 5**  
Paper: Addressing the pooled amplification paradox with unique molecular identifiers in single-cell RNA-seq.  
Members:  
Hack-link: https://hackmd.io/b5wRqX8uTxqe9cfWAAvFGQ

**Team 6**  
Paper:  
Members:  
Hack-link:


# 6. Feedback:
https://forms.gle/fVyxR9XpdVJDhhEE6





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