Hotspot Analysis Code

This is the analysis repository which accompanies the manuscript for Hotspot

Directory Contents

• /data: Downloading and formatting of public data
• /pipelineScripts: Shared scripts for Snakemake pipelines
• /SlideSeq: Analysis code for the Slide-Seq example (mouse cerebellum)
• /Lineage: Analysis code for the Lineage example (mouse embryogenesis)
• /Transcriptomics: Analysis code for the CD4 T cell and Simulation examples
• /Notebooks: Example usage notebooks

Notes

Pipelines here make heavy use of Snakemake.

The Snakefile in directories describes the scripts and steps needed to run the pipeline.

Outputs can be recreated in each directory by running snakemake all

Figures

Code to re-create figures can be found in various Figures directories and depends on prior execution of Snakemake pipelines.

• Figure 1 - Algorithm Diagram

• Figure 2

  • Panel A: /Transcriptomics/Figures/EvaluateFeatureSelection/plotRelevance.py
  • Panel B: /Transcriptomics/Figures/EvaluateFeatureSelection/compareLatentSpaces.py
  • Panel C: /Transcriptomics/Figures/EvaluateFeatureSelection/compare_local_expression.py
  • Panel D: /Transcriptomics/Figures/CD4_Correlation/plot.py
  • Panel E: /Transcriptomics/Figures/CD4_Correlation/ModuleConsistency_CD4.py

• Figure 3

  • Panel A: /SlideSeq/Figures/MainFigure/moduleHeatmap.py
  • Panel B: /SlideSeq/Figures/MainFigure/moduleCellTypes.py
  • Panel C: /SlideSeq/Figures/MainFigure/moduleScores.py

• Figure 4

  • Panel A: /Lineage/Figure/plotCorrelations.py
  • Panel B: /Lineage/Figure/plotUMAPs.py
  • Panel C: /Lineage/Figure/plotKernels.py
  • Panel D: /Lineage/Figure/plotKernelsTx.py
  • Panel E: /Lineage/Figure/plotAngioblasts.py

• Figure S1

  • Panel A: /Transcriptomics/Figures/Simulation/plotTSNEs.py
  • Panel B: /Transcriptomics/Figures/Simulation/plotAUC_PR.py
  • Panel C: /Transcriptomics/Figures/Simulation/plotModuleAssignment.py

• Figure S2

  • Panel A: /SlideSeq/Figures/Supp1/plotMeanVar.py, /SlideSeq/Figures/Supp_Autocorr/compare_local_expression.py
  • Panel B: /SlideSeq/Figures/Supp1/plotPR.py
  • Panel C: /SlideSeq/Figures/Supp1/plotTimings.py
  • Panel D: /SlideSeq/Figures/Supp1/plotIDR.py

• Figure S3

  • Panel A: /SlideSeq/Figures/Supp2/comparePairwiseZScores.py
  • Panel B: /SlideSeq/Figures/Supp2/compareModules.py
  • Panel C: /SlideSeq/Figures/Supp2/compareModuleAssignments.py

• Figure S4

  • Panel A: /SlideSeq/Figures/Supp3/compareModulesSpatialDE.py
  • Panel B: /SlideSeq/Figures/Supp3/compareTiming.py
  • Panel C: /SlideSeq/Figures/Supp3/compareModulesSpatialDE.py

• Figure S5

  • Panel A: /SlideSeq/Figures/Supp4/plotPValues.py
  • Panel B: /Transcriptomics/Figures/Supp_Pvals/plotPValues.py
  • Panel C: /Lineage/Figure/plotPValues.py

• Figure S6

  • All Panels: /Transcriptomics/Figures/EvaluateFeatureSelection/hvg_vs_hs.py

• Figure S7

  • Panel A: /Transcriptomics/Figures/Simulation/downsampling_correlation.py
  • Panel B: /Transcriptomics/Figures/CD4_Correlation/plot_downsampled.py
  • Panel C: /Transcriptomics/Figures/CD4_Correlation/plot_downsampled.py
  • Panel D: /Transcriptomics/Figures/Simulation/downsampling_correlation.py

• Figure S8

  • All Panels: /SlideSeq/Figures/Supp5_HVG_vs_HS/hvg_vs_hs.py

• Figure S9

  • Panel A: /SlideSeq/Figures/Supp6_NegBinom_vs_Bernoulli/plotPR.py
  • Panel B: /SlideSeq/Figures/Supp6_NegBinom_vs_Bernoulli/compareModuleAssignments.py

• Figure S10

  • Column 1: /Transcriptomics/Figures/Simulation/plotAUC_PR_k_sensitivity.py
  • Column 2: /Transcriptomics/Figures/EvaluateFeatureSelection/plotRelevance_k_sensitivity.py
  • Column 3: /SlideSeq/Figures/Supp1/plotPR_k_sensitivity.py

• Figure S11

  • Panel A: /SlideSeq/Figures/Supp7_Bernoulli/plot.py
  • Panel B: /Transcriptomics/Figures/CD4_Correlation/ModuleConsistency_Monocytes.py

• Figure S12

  • All Panels: /Transcriptomics/Figures/EvaluateFeatureSelection/compare_local_expression.py

• Figure S13

  • All Panels: /SlideSeq/Figures/Supp_Autocorr/compare_local_expression.py

Software Versions

Python 3.6.8

biopython==1.72
ete3==3.1.1
feather-format==0.4.0
h5py==2.9.0
loompy==2.0.17
matplotlib==3.1.0
naivede==1.2.0
numba==0.45.0
numpy==1.16.5
pandas==0.25.1
scanpy==1.4
scipy==1.2.1
scvi==0.2.4
seaborn==0.9.0
scikit-learn==0.21.2
spatialde==1.1.1
snakemake==5.5.3
statsmodels==0.10.0
tqdm==4.32.2
umap-learn==0.3.6
hotspot==0.9.0 (github.com/yoseflab/hotspot)
bio_utils (included in /packages directory)
gene_enrich (included in /packages directory)

R 3.5.1

edgeR==3.22.3
feather==0.3.5
ggplot2==3.1.0
idr==1.2
jsonlite==1.6
loomR==0.2.0
M3Drop==3.10.4
matrixStats==0.54.0
NMF==0.21.0
openxlsx==4.1.0
pbmcapply==1.3.1
Rtsne==0.15
Seurat==2.3.4
SymSim==0.0.0.9000 (github.com/yoseflab/symsim)
VISION==2.0.0 (github.com/yoseflab/VISION)
DropSeq.util==2.0 (Available via DropViz)