Application for the MSNZ RNA-seq data analysis workshop

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Thank you for your interest in the MSNZ RNA-seq data analysis workshop tutored by Dr. Federico Marini from the IMBEI in Mainz on the 30th of june, 2023.

To ensure a good learning opportunity for all attendings, we ask you to fill out the form below including a short abstract on why you think analysis of RNA-seq data would help in your scientific work and how you plan to use the insights you get from this course. If you already have hands-on experience or a particular data set or research question at hand you are welcome to write a brief abstract.

Below you find a quick quiz that you can use to self-assess your current level of knowledge. They cover very basic R skills and you should be able to answer them easily. Please note that we will not be able to cover basic R skills hence if you find the quick challanging please invest some time to prepare yourself for the course. You can find free online resources for example at

https://r4ds.had.co.nz/

or on YouTube. Alternativly, DataCamp and DataQuest offer well-structured but paid courses.

Please note that the quiz is for your self-assessment only and results are not sent.

RStudio is a
*

0 points

Plotting device to visualize data with R

Editor to write markdown files and publish data scientific reports, PDF and websides

Integrated Developement Environment (IDE) designed for working with the R statistical language

Data explorer tool to visually and programatically inspect data sets

All of the above

Select all the correct answers to load a *.csv gene expression matrix into R

0 points

exp <- read(file = "expression.csv")

exp <- readr::read_csv(file = "expression.csv")

exp <- load(file = "expression.csv")

exp <- read.csv(file = "expression.csv")

load.csv(file ="expresison.csv")

Clear selection

You have a data frame df_seq with experimental meta data with 500 samples as rows and "ID", "Batch", "Organism", "Sequencing_Date" and "Donor_ID" as columns. Which way to filter for rows where "Organism" is "homo_sapiens" and "Donor_ID" is "m_24" is wrong?

0 points

dplyr::filter(.data = df_seq, Organism == "homo_sapiens" & Donor_ID == "m_24")

df_seq[df_seq$Organism == "homo_sapiens" & df_seq$Donor_ID == "m24", ]

df_seq[Organism == "homo_sapiens" & Donor_ID == "m_24", ]

selection <- df_seq$Organism == "homo_sapiens" & df_seq$Donor_ID == "m24" followed by df_seq[selection, ]

Clear selection

Given a genes x samples count matrix count_mat, which approach will not work to calculate the gene-wise mean and variance

0 points

data.frame(mean = mean(count_mat), variance = var(count_mat))

data.frame(mean = apply(count_mat, FUN = mean, MARGIN = 1), variance = apply(count_mat, FUN = var, MARGIN = 1))

data.frame(mean = matrixStats::rowMeans2(count_mat), variance = matrixStats::rowVars(count_mat))

Clear selection

Select all ways to load function foo() from the library foo_bar

0 points

library(foo_bar) followed by foo()

require(foo_bar) followed by foo()

foo_bar::foo()

load(foo_bar) followed by foo()

Clear selection

Which of the following is not a data type in R

0 points

vector

list

data.frame

tibble

dictionary

matrix

Clear selection

Submit

Clear form

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