Retrieve the entire repository including all datasets and notebooks.
cd ~/Desktop/course
git clone git@github.com:NBISweden/workshop_omics_integration.git .
Inside you will find the following folders:
environments/
- all conda environments necessary for running notebookssession_preprocessing/
- data pre-processing, prior to course startsession_ml/
- the machine learning sessions, days 1 and 2session_topology/
- the network topology analysis, day 3 morningsession_meta/
- network meta-analysis, day 3 afternoonsession_nmf/
- session on matrix factorization, SNF and recommender systems, day 4 morningsession_gems/
- the genome-scale modeling session, day 4 afternoonsession_gsa/
- gene set and reporter feature, day 5 morning.../
- remaining folders not necessary for running any of the contentsYou will need to create specific conda environments as indicated below.
Environments
See the pre-course installation, specifically 3. Create and activate the environment.
Environments - we merged the environments for many notebooks down to 4 environments.
env-preprocessing_linux.yaml
, macOS: env-preprocessing.yaml
)Supervised Integration & Feature selection& (linux: env-ml_linux.yaml |
macOS: env-ml.yaml ) |
Meta analysis (linux | macOS /session_meta/renv.lock ) |
All remaining notebooks (linux env-ml_nets_linux.yaml |
MacOS env-ml_nets.yaml ) |
Alternatively, you can find smaller environments below.
/environments/env-preprocessing.yaml
/environments/env-preprocessing_linux.yaml
/session_preprocessing/preprocessing.ipynb
In MacOSX you need to install XQuartz if you get errors related with rgl
:
install.packages('session_ml/rgl_0.100.54.tgz', repos = NULL, type="source", dependencies = TRUE)
/environments/env-ml.yaml
/environments/env-ml_linux.yaml
/session_ml/SupervisedOMICsIntegration/supervised_omics_integr_CLL/supervised_omics_integr_CLL.Rmd
/environments/env-ml.yaml
/environments/env-ml_linux.yaml
session_ml/FeatureSelectionIntegrOMICs/OmicsIntegration_FeatureSelection.Rmd
/environments/env-ml_day2.yaml
/environments/env-ml_day2_linux.yaml
session_ml/UnsupervisedOMICsIntegration/UnsupervisedOMICsIntegration.Rmd
After activating the environment as above, open the .Rmd
below by launching Rstudio with rstudio &
or the jupyter notebooks with jupyter-notebook
.
/environments/env-ml_day2.yaml
/environments/env-ml_day2_linux.yaml
session_ml/DimReductSingleCell/OmicsIntegration_DimensionReduction.Rmd
gunzip scRNAseq.csv.gz; gunzip scProteomics.csv.gz
/environments/env-ml_day2.yaml
/environments/env-ml_day2_linux.yaml
session_ml/UMAP_DataIntegration/UMAP_DataIntegration.ipynb
/environments/env-ml_day2.yaml
/environments/env-ml_day2_linux.yaml
session_ml/DeepLearningDataIntegration/DeepLearningDataIntegration.ipynb
/environments/env-ml_day2.yaml
/environments/env-ml_day2_linux.yaml
session_ml/SingleCell/SingleCell_OmicsIntegration.Rmd
/environments/env-merged_nets.yaml
/environments/env-merged_nets_linux.yaml
/session_topology/lab.ipynb
/session_meta/renv.lock
/session_meta/renv.lock
/session_meta/lab_meta-analayses-v2.Rmd
/environments/env-merged_nets.yaml
/environments/env-merged_nets_linux.yaml
/session_gems/lab.ipynb
/environments/env-merged_nets.yaml
/environments/env-merged_nets_linux.yaml
/session_gsa/GEM_GSA.Rmd