Scripts and data files for analyses performed in Barrett et al., 2024 from the CeNGEN project

Scripts are split by figure, and the order to run the scripts is indicated in this readme file

required packages to install

LittleBites Prop2Count

required files not included here:

"032224_L4_all_cells_Seurat5.rds" found on the CeNGEN downloads page, the full dataset (100k cells) was used for this analysis. direct download link

Pre-processing

Identifying likely Artifact genes

Some genes were removed from analysis because they are prone to artifactual expression patterns due to their potential inclusion in promoter-fusion constructs used for FACS sorting.

Putative artifact gene identification described in: R/filter_marker_promoters.R

Figure 1

FACS plots and micrographs are not included here
PCA: R/plot_PCA.R

Supplementary Figure 1

Single Cell - Bulk Correlation plot: R/Bulk_single_cell_correlation_heatmap.R

Figure 2

pre-processing LittleBites: R/subtraction.R
pre-processing bMIND: R/bMIND_deconvolution.R
pre-processing ENIGMA: R/ ENIGMA_L2_norm.R

ROC for non-neuronal and ubiquitous genes: R/UN_ROC_comparison_240401.R

ROC for neuronal genes: R/Neuronal_ROC_comparison_240516.R

Supplementary Figure 2

AUROC barcharts for non-neuronal and ubiquitous genes: R/UN_ROC_comparison_240401.R

AUCROC barcharts for neuronal genes: R/Neuronal_ROC_comparison_240516.R

AUROC scatterplots for non-neuronal and ubiquitous genes per sample: R/UN_ROC_comparison_240401.R

Figure 3

AFD ttx-1 expression: R/AFD_UMAP.R

Single Cell ROC plot: R/Single_cell_ROC.R

Simulated and real logit models: R/240520_Logit_transform_parameter_comparison.R

Supplementary Figure 3

Running Differential Expression analysis: R/single_cell_differential_expression.R
Visualizing Differential Expression vs Ground Truth: R/Differential_expression_metrics.R

Figure 4

Generating Integrated Datasets: R/Integrated_bulk_SingleCell.R

Neuronal ROC, AUROC, Precision-Recall, and Sensitivity bootstrapping plots: R/Integrated_Neuronal_ROC.R
Barchart of genes detected in single cell and integrated: R/Integrated_genes_new_detection.R

GO term and anatomical enrichment performed using the Enrichment Analysis tool on wormbase https://wormbase.org/tools/enrichment/tea/tea.cgi

Supplementary Figure 4

Heatmaps of expresssion vs ground truth correspondence

Figure 5

Scatterplots and bar plots of genes detected in integrated data but missed in single cell: R/Integrated_genes_new_detection.R

Supplementary Figure 5

GO term and anatomical enrichment performed using the Enrichment Analysis tool on wormbase https://wormbase.org/tools/enrichment/tea/tea.cgi

Gene lists for each cell that was used as input for the GSEA tool can be extracted using: R/Integrated_genes_new_detection.R

Figure 6

Noncoding RNA pie charts, and specific gene expression pattern heatmap: R/ncRNA_graphs_and_specificity.R

GPCR pseudogene expression plots: R/GPCR_gene_analysis_240731.R

Supplementary Figure 6

Relative maximum gene expression distributions, Contamination correlation cutoffs, ubiquitous ncRNA gene distribution, and total ncRNA genes per cell (by gene biotype): R/ncRNA_graphs_and_specificity.R