Multi-seq-Data-Analysis-Post-Analysis

Post-hoc analysis for scRNA-seq and scATAC-seq Data Analysis DREAM Challenge

Installation

1. Clone the repo

   git clone https://github.com/Sage-Bionetworks-Challenges/Multi-seq-Data-Analysis-Post-Analysis
   cd Multi-seq-Data-Analysis-Post-Analysis
   

2. Create a conda environment using python 3.9:

   conda create --name synapse python=3.9 -y
   conda activate synapse
   

3. Install Python dependencies

   python -m pip install challengeutils==4.2.0
   

   check if synapseclient and challengeutils are installed via:

   synapse --version
   challengeutils -v
   

4. Install R dependencies

   R -e 'source("install.R")'
   

   Note:
   The task 2 analysis uses bedr package that has two requisitions - bedpos and tabix needed to be installed as well.

5. Set up Synapse credentials via CLI, or manually store the credentials to ~/.synapseConfig - see details here synapse login --rememberMe

Usage

Download all final submission results and each individual test case's scores to data/ folder:

Rscript submission/get_submissions.R

• final_submissions_{task}.rds: Esseential information of final submission, e.g submission id, team, ranks
• final_scores_{task}.rds: All test case scores from final submissions, consists of test case name, scores of primary and secondary metrics

Download output files (imputed gene expression / called peaks) of all final submissions to data/model_output/

# replace {task} with 'task1' or 'task2'
Rscript submission/get_predictions_{task}.R

Warning For Task 1, the output (imputation) of each submission has large size ~30G. Please be aware of the available disk space.

Report statistics about submissions

Rscript -e 'rmarkdown::render("stats/get_submission_stats.rmd")'