Updates

.github/workflows/build-book-release.yml

@@ -136,8 +136,10 @@ jobs:
           remotes::install_github("HenrikBengtsson/matrixStats", ref="develop")
           BiocManager::install("Cairo")
           BiocManager::install("biclust")	  
-          BiocManager::install("cobiclust")	  	  
+          BiocManager::install("cobiclust")
+          BiocManager::install("ecodist")	  	  	  
           BiocManager::install("HDF5Array")
+          BiocManager::install("kableExtra")	  
           BiocManager::install("microbiome/microbiomeDataSets")
           BiocManager::install("fionarhuang/TreeSummarizedExperiment")
           # Remove when available in docker
@@ -167,7 +169,7 @@ jobs:
         run: |
           git config --global user.email "action@github.com"
           git config --global user.name "GitHub Action"
-          git config --global --add safe.directory /__w/course_2022_oulu/course_2022_oulu
+          git config --global --add safe.directory /__w/course_2022_radboud/course_2022_radboud
           git fetch --all
           commit=$(git --work-tree=../ rev-parse --verify --short HEAD)
           git worktree add --track -B gh-pages docs origin/gh-pages

01-program.Rmd

@@ -1,105 +0,0 @@
-# Program
-
-The course takes place daily from 9am – 5pm (CEST), including
-coffee and lunch breaks.
-
-We expect that participants will prepare for the course in advance, see section
-\@ref(start). Online support is available.
-
-
-The material follows open online book created by the course teachers,
-Orchestrating Microbiome Analysis
-https://microbiome.github.io/OMA. This is R/Bioconductor framework for
-multi-omic data science.
-
-
-<img src="fig.png" alt="ML4microbiome" width="50%"/>
-<p style="font-size:12px">Figure source: Moreno-Indias _et al_. (2021) [Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions](https://doi.org/10.3389/fmicb.2021.635781). Frontiers in Microbiology 12:11.</p>
-
-
-## Day 1 - Open data science 
-
-**Morning session**
-
-9-10 Coffee, Welcome & Practicalities
-
-10-11 Lecture: Open & reproducible workflows 
-
-11-12 Demo & hands-on: Introduction to CSC RStudio notebook 
-
-12-13 Lunch break
-
-
-**Afternoon hands-on session**
-
-13-15 Demo: Data science framework
-
-15-17 Hands-on: microbiome data summaries & exploration 
-
-17-18 Presentations & Discussion
-
-
-----------------------------------------------------------------
-
-## Day 2 - Tabular data 
-
-**Morning session**
-
- 9-10 Lecture: Analysis & visualization of _tabular data_
-
-10-12 Demo & hands-on: Univariate methods
-
-12-13 Lunch break
-
-**Afternoon hands-on session**
-
-13-14 Demo: Multivariate data analysis & visualization
-
-14-17 Hands-on: Multivariate data analysis & visualization
-
-17-18 Presentations & Discussion
-
-----------------------------------------------------------------
-
-## Day 3 - Multi-assay data
-
-**Morning session**
-
- 9-10 Lecture: multi-omic data integration
-
-10-12 Demo & hands-on: multi-assay data container
-
-12-13 Lunch break
-
-
-**Afternoon hands-on session**
-
-13-15: Demo & hands-on: association analysis
-
-13-17: Demo & hands-on: machine learning
-
-17-18 Presentations & Discussion
-
-
------------------------------------------------------------------
-
-## Day 4 - Advanced topics
-
-**Morning session**
-
- 9-10 Summary of the learning material
-
-10-12 Demo & hands-on: custom data & advanced tools
-
-12-13 Q & A session
-
-
-**Afternoon session**
-
-13-14 Lunch
-
-14-16 Wrap-up
-
-
-
-

01.1-codeofconduct.Rmd

@@ -1,11 +1,5 @@
 
-# Project-wide Code of Conduct statement for Bioconductor
-[link to code of conduct](https://bioconductor.github.io/bioc_coc_multilingual/)
-
-
-(Adapted from the BioC 2020 Code of Conduct)
-
-## Code of Conduct -Version 1.0.2 (July 27, 2021)
+# Code of Conduct 
 
 The Bioconductor community values an open approach to science that promotes the
 
@@ -15,64 +9,6 @@ The Bioconductor community values an open approach to science that promotes the
  - a kind and welcoming environment
  - community contributions
 
-In line with these values, Bioconductor is dedicated to providing a welcoming, supportive, collegial experience free of harassment, intimidation, and bullying regardless of:
-
- - identity: gender, gender identity and expression, sexual orientation, disability, physical appearance, ethnicity, body size, race, age, religion, language etc.
- - intellectual position: approaches to data analysis, software preferences, coding style, scientific perspective, stage of career, etc.
-
-By participating in this community, you agree not to engage in behavior contrary to these values at any Bioconductor-sponsored event (in person or virtual, including but not limited to talks, workshops, poster sessions, social activities) or electronic communication channel (including but not limited to community-bioc Slack, the support site, online forums, package review site and social media communications). Furthermore, we require all participants to have identifiable accounts in Bioconductor online forums. Accounts that do not adhere to this after request to de-anonymise may be deleted.
-
-We do not tolerate harassment, intimidation, or bullying of community members. Sexual language and imagery are not appropriate in presentations, communications or in online venues, including chats.
-
-Any person/s violating the Code of Conduct may be sanctioned or expelled temporarily or permanently from an electronic platform or event at the discretion of the Code of Conduct committee.
-
-**Examples of unacceptable harassment, intimidation, and bullying behavior**
-
-Harassment includes, but is not limited to:
-
- - Making comments in chats, to an audience or personally, that belittle or demean another person
- - Sharing sexual images online
- - Harassing photography or recording
- - Sustained disruption of talks or other events
- - Unwelcome sexual attention
- - Advocating for, or encouraging, any of the above behavior
-
-Intimidation and bullying include, but are not limited to:
-
- - Aggressive or browbeating behavior
- - Mocking or insulting another person’s intellect, work, perspective, or question/comment
- - Making reference to someone’s gender, gender identity and expression, sexual orientation, disability, physical appearance, body size, race, age, religion, or other personal attributes in the context of a scientific discussion
- - Deliberately making someone feel unwelcome
- - Trolling behaviour (deliberately inflammatory or offensive messages)
- - Sustained off-topic posts
-
-## Enforcement
-
-Anyone asked to stop harassing or intimidating behavior are expected to comply immediately.
-
-If a person/s contravene the Code of Conduct the Code of Conduct committee retains the right to take any action that ensures a welcoming environment for all community members. This includes warning the alleged offender or temporary/permanent expulsion from the event and/or electronic platforms under Bioconductor’s control.
-
-The Code of Conduct committee may take action to redress anything designed to, or with the clear impact of, disrupting an event or electronic communication platform or making the environment hostile for any community member.
-
-We expect everyone in the Bioconductor community to comply with the Code of Conduct when participating in Bioconductor events and online communication platforms.
-
-## Reporting
-
-If someone makes you or anyone else feel unsafe or unwelcome, please report it as soon as possible. You can make a report either anonymously or personally. All reports will be reviewed by the Code of Conduct Committee and will be kept confidential.
-
-*Electronically*
-You can make an anonymous or non-anonymous report via the following link: https://forms.gle/gEWHBWnXvZbEdFsq5. It is a free-form text box that will be forwarded to the Code of Conduct Committee. Alternatively you can email the Code of Conduct Committee (code-of-conduct@bioconductor.org). If you are uncomfortable reporting to the Code of Conduct committee as a group, you can contact any individual committee member via email or a direct message on the community-bioc Slack channel. Please include screenshots/copies of all relevant electronic conversations whenever possible (you don’t need to compromise your anonymity!).
-
-We can’t follow up an anonymous report with you directly, but we will fully investigate it and take whatever action is necessary to prevent a recurrence.
-
-**Personal Report (for any Bioconductor events: in-person or virtual)**
-
-You can make a personal report to any member of the event Code of Conduct committee present at an event.
-
-When taking a personal report, we will ensure you are safe and cannot be overheard. We may involve other event staff to ensure your report is managed properly. Once safe, we’ll ask you to tell us about what happened. This can be upsetting, but we’ll handle it as respectfully as possible, and you can bring someone to support you. You won’t be asked to confront anyone, and we won’t tell anyone who you are.
-
-Our team will be happy to help you get the relevant support (e.g. help contacting hotel/venue security, local law enforcement, local support services, provide escorts, or otherwise assist you to feel safe for the duration of the event).
-
 We value your attendance and participation at Bioconductor events and in our community.
 
-
+For the full version, enforcement, and reporting instructions, see the [Bioconductor code of conduct](https://bioconductor.github.io/bioc_coc_multilingual/).

02-data.Rmd

@@ -0,0 +1,187 @@
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo=TRUE, message=FALSE, warning=FALSE)
+```
+
+
+# Importing microbiome data
+
+This section demonstrates how to import taxonomic profiling data in R.
+
+
+## Data access
+
+*ADHD-associated changes in gut microbiota and brain in a mouse model*
+
+Tengeler AC _et
+al._ (2020) [**Gut microbiota from persons with
+attention-deficit/hyperactivity disorder affects the brain in
+mice**](https://doi.org/10.1186/s40168-020-00816-x). Microbiome
+8:44.
+
+In this study, mice are colonized with microbiota from participants
+with ADHD (attention deficit hyperactivity disorder) and healthy
+participants.  The aim of the study was to assess whether the mice
+display ADHD behaviors after being inoculated with ADHD microbiota,
+suggesting a role of the microbiome in ADHD pathology.
+
+Download the data from
+  [data](https://github.com/microbiome/course_2022_radboud/tree/main/data)
+  subfolder.
+
+
+## Importing microbiome data in R
+
+**Import example data** by modifying the examples in the online book
+section on [data exploration and
+manipulation](https://microbiome.github.io/OMA/data-introduction.html#loading-experimental-microbiome-data).
+
+The data files in our example are in _biom_ container, which is a
+standard file format for microbiome data. Other file formats exist as
+well, and import details vary by platform. Here, we import _biom_ data
+files into a specific data container (structure) in R,
+_TreeSummarizedExperiment_ (TreeSE) [Huang et
+al. (2020)](https://f1000research.com/articles/9-1246).
+
+The data container provides the basis for downstream data analysis in
+the _miaverse_ data science framework.
+
+
+<img src="https://raw.githubusercontent.com/FelixErnst/TreeSummarizedExperiment
+/2293440c6e70ae4d6e978b6fdf2c42fdea7fb36a/vignettes/tse2.png" width="100%"/>
+
+**Figure sources:** 
+
+**Original article**
+-   Huang R _et al_. (2021) [TreeSummarizedExperiment: a S4 class 
+for data with hierarchical structure](https://doi.org/10.12688/
+f1000research.26669.2). F1000Research 9:1246.
+
+**Reference Sequence slot extension**
+- Lahti L _et al_. (2020) [Upgrading the R/Bioconductor ecosystem for microbiome 
+research](https://doi.org/10.7490/
+f1000research.1118447.1) F1000Research 9:1464 (slides).
+
+
+
+
+### Example solution
+
+Let us first import the biom file into R / TreeSE container.
+
+```{r import, message=FALSE, warning=FALSE}
+# Load the mia R package
+library(mia)
+
+# Defining file paths
+## Biom file (taxonomic profiles)
+biom_file_path <- "data/Tengeler2020/Aggregated_humanization2.biom"
+
+# Import the data into SummarizedExperiment container
+se <- loadFromBiom(biom_file_path)
+
+# Convert this data to TreeSE container (no direct importer exists)
+tse <- as(se, "TreeSummarizedExperiment")
+```
+
+
+Check and clean up rowData (information on the taxonomic features).
+
+
+```{r rowdata, message=FALSE, warning=FALSE}
+# Investigate the rowData of this data object
+print(head(rowData(tse)))
+
+# We notice that the rowData fields do not have descriptibve names.
+# Hence, let us rename the columns in rowData
+names(rowData(tse)) <- c("Kingdom", "Phylum", "Class", "Order", 
+                        "Family", "Genus")
+
+# We also notice that the taxa names are of form "c__Bacteroidia" etc.
+# Goes through the whole DataFrame. Removes '.*[kpcofg]__' from strings, where [kpcofg] 
+# is any character from listed ones, and .* any character.
+rowdata_modified <- BiocParallel::bplapply(rowData(tse), 
+                                           FUN = stringr::str_remove, 
+                                           pattern = '.*[kpcofg]__')
+
+# Genus level has additional '\"', so let's delete that also
+rowdata_modified <- BiocParallel::bplapply(rowdata_modified, 
+                                           FUN = stringr::str_remove, 
+                                           pattern = '\"')
+
+# rowdata_modified is a list, so convert this back to DataFrame format. 
+# and assign the cleaned data back to the TSE rowData
+rowData(tse) <- DataFrame(rowdata_modified)
+
+# Recheck rowData after the modifications
+print(head(rowData(tse)))
+```
+
+
+Next let us add sample information (colData) to our TreeSE object.
+
+
+```{r coldata, message=FALSE, warning=FALSE}
+## Sample phenodata
+sample_meta_file_path <- "data/Tengeler2020/Mapping_file_ADHD_aggregated.csv"
+
+# Check what type of data it is
+# read.table(sample_meta_file_path)
+
+# It seems like a comma separated file and it does not include headers
+# Let us read the file; note that sample names are in the first column
+sample_meta <- read.table(sample_meta_file_path, sep=",", header=FALSE, row.names=1)
+
+# Check the data
+print(head(sample_meta))
+
+# Add headers for the columns (as they seem to be missing)
+colnames(sample_meta) <- c("patient_status", "cohort",
+                           "patient_status_vs_cohort", "sample_name")
+
+# Add this sample data to colData of the taxonomic data object
+# Note that the data must be given in a DataFrame format (required for our purposes)
+colData(tse) <- DataFrame(sample_meta)
+
+# Check the colData after modifications
+print(head(colData(tse)))
+```
+
+
+Add phylogenetic tree (rowTree).
+
+```{r rowtree, message=FALSE, warning=FALSE}
+## Phylogenetic tree
+tree_file_path <- "data/Tengeler2020/Data_humanization_phylo_aggregation.tre"
+
+# Read the tree file
+tree <- ape::read.tree(tree_file_path)
+
+# Add tree to rowTree
+rowTree(tse) <- tree
+```
+
+We can save the data object as follows.
+
+```{r save, message=FALSE, warning=FALSE}
+saveRDS(tse, file="tse.rds")
+```
+
+
+### Loading readily processed data
+
+Alternatively, you can just load the already processed data set.
+
+By using this readily processed data set we can skip the data import
+step, and assume that the data has already been appropriately
+preprocessed and available in the TreeSE container.
+
+
+```{r, message=FALSE, warning=FALSE, eval=FALSE}
+tse <- readRDS("data/Tengeler2020/tse.rds")
+```
+
+In addition to our example data, further demonstration data sets are
+available in the TreeSE data container: see [OMA demo data
+sets](https://microbiome.github.io/OMA/containers.html#example-data).
+