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SpielmannLab/2022_TRalpha1_Sreenivasan

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2022_TRalpha1_Sreenivasan

Read Only - Archived on 19th Jan 2023

Following are the scripts used to analyse data, as presented in the manuscript

  1. Run Preprocess_fastq/script_count_wrap.sh to generate gene expression count matrices from sequencing fastq files
  2. Run Main_Analysis/vs_sc_p_sample_main.sh to perform a standard analysis of the data. This wrapper calls a Nextflow script Main_Analysis/src/sc_p_sample.nf, which includes multiple steps including importing the data, QC, filtering, clustering, dimensionality reduction, and DE gene analysis. This is run in the conda environment Main_Analysis/ScRNA.yml
  3. Run Main_Analysis/sc_multi_sample_main.sh to combine the samples. This wrapper calls a Nextflow script Main_Analysis/src/sc_multi_sample.nf, which combines the data, performs dimensionality reduction, clustering and DE gene analysis. This is run in the conda environment Main_Analysis/ScRNA.yml
  4. Run Figure_Generation/make_figures.nf nextflow run Figure_Generation/make_figures.nf to perform custom analysis used in this manuscript as well as generate figures presented in the manuscript. This is run in the conda environment Figure_Generation/HypthmsMittag.yml

[1] Absolute paths are used at certain instances, which will need to be adapted, as needed.
[2] Anaconda was used to set up the necessary environments

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