NEAT-seq reproducibility

Code to reproduce results from the NEAT-seq manuscript. (Link will be added upon publication)

Getting started

The exact R package versions used for running analysis code are saved in renv.lock. These can be installed into a reproducible R environment using the renv package's renv::restore() function.

Input data from GEO should be downloaded before running any analysis scripts. This can be done with the script code_utils/download_data.py and will download about 1.5GB of data

Code layout

Each main text figure and the corresponding supplemental figure is in its own directory. Details on the code + data files are provided in the folders for each figure. All scripts should be run from the project root, rather than inside any of the figure folders.

Running the code

Most of the code files run in <5 minutes, but can consume substantial RAM. It is recommended to run on a machine with >10GB of available memory.

Library Installation

• R: install.packages("renv"); renv::restore()
  • Additional packages that are required for certian scripts: Seurat, immunogenomics/presto, limma, seriation, org.Hs.eg.db, clusterProfiler (may require [email protected] for clusterProfiler install to work)
• python: pip install pysam snakemake
  • Some ArchR analysis further requires macs2, though it may be easiest to pip install macs3 then alias macs2 to point to macs3
• other: conda install samtools

Data download

python code_utils/download_data.py

Figure 1

Rscript fig1_species_mixing/code/barnyard_analysis.R

Figure 2

Rscript fig2_CD4_Tcells/code/hematopoiesis_projection.R
Rscript fig2_CD4_Tcells/code/CD4_HTO_singlet_ADT_counts.R
Rscript fig2_CD4_Tcells/code/CD4_ArchR_plots.R # This is the slow step
Rscript fig2_CD4_Tcells/code/ADT_normalization.R
Rscript fig2_CD4_Tcells/code/ArchR_CD4cells_add25xADT.R
Rscript fig2_CD4_Tcells/code/ADT_vs_RNA_correlations.R
Rscript fig2_CD4_Tcells/code/Seurat_markers.R
Rscript fig2_CD4_Tcells/code/Seurat_GATA3_differential_analysis.R

Figure3

Rscript fig3_correlation_analysis/code/correlation_analysis.R
Rscript fig3_correlation_analysis/code/correlation_plots.R

python fig3_correlation_analysis/code/extract_snp_information.py
Rscript fig3_correlation_analysis/code/snp_plots.R

Rscript fig3_correlation_analysis/code/trackplots.R
Rscript fig3_correlation_analysis/code/heatmaps.R

Revisions

snakemake -c5 -s Supplementary_figures/code/K562_bulk_ATAC/K562_download.snake
Rscript Supplementary_figures/code/bulk_correlation.R

Rscript Supplementary_figures/code/ADT_normalization_tests.R
Rscript Supplementary_figures/code/ArchR_CD4cells_add5xADT_250.R
Rscript Supplementary_figures/code/peak_gene_GO.R

To-do checklist upon SRA publication

[ ] Add instructions for accessing ATAC-seq bam files from SRA