We have submitted our processed data from single-cell RNA sequencing (scRNA-seq) and whole-genome sequencing (WGS), including Seurat objects, annotated variant calls, and detailed metadata for further analysis in the study: Aberrant Basal Cell Clonal Dynamics Shape Early Lung Carcinogenesis.

Descriptions

NTCU_GEX_Trachea_processed_Celltype_seurat.rds

This Seurat object contains processed single-cell RNA sequencing data for mouse tracheal cells from NTCU-treated and Control groups. The data includes annotations for various cell types, allowing for the analysis of gene expression profiles and cellular heterogeneity.

• Metadata columns:
  • orig.ident: Original identifier for the sample
  • nCount_originalexp: Total RNA count per cell
  • nFeature_originalexp: Number of features detected per cell
  • sample: Sample identifier
  • patientID: Identifier for the mouse
  • tissue: Tissue type (trachea)
  • phenotype: Phenotype group (NTCU-treated, control)
  • age: Age of the animal in weeks
  • scrublet__predicted_multiplet: Predicted multiplet status (Y/N)
  • scrublet__multiplet_scores: Scrublet scores for multiplet detection
  • scrublet__multiplet_zscores: Z-scores from Scrublet
  • batch: Batch number for sample processing
  • n_genes: Number of genes detected per cell
  • n_genes_by_counts: Number of genes expressed, calculated by counts
  • log1p_n_genes_by_counts: Log-transformed count of genes by expression
  • total_counts: Total number of counts for the sample
  • log1p_total_counts: Log-transformed total counts per sample
  • total_counts_mt: Total mitochondrial counts per sample
  • log1p_total_counts_mt: Log-transformed mitochondrial counts per sample
  • pct_counts_mt: Percentage of mitochondrial counts relative to total counts
  • total_counts_ribo: Total ribosomal RNA counts per sample
  • log1p_total_counts_ribo: Log-transformed ribosomal RNA counts
  • pct_counts_ribo: Percentage of ribosomal RNA counts relative to total counts
  • Cell_types: Annotated cell types based on clustering

NTCU_Trachea_Epithelial_integrated_seurat.rds

This Seurat object contains data from epithelial subclustered cells isolated from mouse NTCU-treated and Control trachea samples. The cells are integrated for comparative analysis, facilitating the identification of cell subtypes and gene expression signatures.

• Metadata columns:
  • orig.ident: Sample identifier
  • nCount_originalexp: Total RNA count per cell
  • nFeature_originalexp: Number of features detected per cell
  • sample: Sample identifier
  • patientID: Identifier for the mouse
  • tissue: Tissue type (trachea)
  • phenotype: Phenotype group (NTCU-treated, control)
  • age: Age of the animal
  • scrublet__predicted_multiplet: Predicted multiplet status (Y/N)
  • scrublet__multiplet_scores: Scrublet scores for multiplet detection
  • scrublet__multiplet_zscores: Z-scores from Scrublet
  • batch: Batch number for sample processing
  • n_genes: Number of genes detected per cell
  • n_genes_by_counts: Number of genes expressed, calculated by counts
  • log1p_n_genes_by_counts: Log-transformed count of genes by expression
  • total_counts: Total number of counts for the sample
  • log1p_total_counts: Log-transformed total counts per sample
  • total_counts_mt: Total mitochondrial counts per sample
  • log1p_total_counts_mt: Log-transformed mitochondrial counts per sample
  • pct_counts_mt: Percentage of mitochondrial counts relative to total counts
  • total_counts_ribo: Total ribosomal RNA counts per sample
  • log1p_total_counts_ribo: Log-transformed ribosomal RNA counts
  • pct_counts_ribo: Percentage of ribosomal RNA counts relative to total counts
  • Montoro_Basal_Score: Basal cell score based on Montoro et al. scoring
  • Montoro_Club_Score: Club cell score based on Montoro et al.
  • Montoro_Ciliated_Score: Ciliated cell score based on Montoro et al.
  • Montoro_Tuft_Score: Tuft cell score based on Montoro et al.
  • Montoro_Neuroendocrine_Score: Neuroendocrine cell score from Montoro et al.
  • Montoro_Ionocyte_Score: Ionocyte cell score based on Montoro et al.
  • Hurskainen_AT2_Score: AT2 cell score based on Hurskainen et al.
  • Hurskainen_AT1_Score: AT1 cell score from Hurskainen et al.
  • Hurskainen_Ciliated_Score: Ciliated cell score based on Hurskainen et al.
  • Hurskainen_Club_Score: Club cell score based on Hurskainen et al.
  • Chen_AT2_Score: AT2 cell score from Chen et al.
  • Chen_Club_Score: Club cell score from Chen et al.
  • Chen_AT1_Score: AT1 cell score from Chen et al.
  • Chen_Basal_Score: Basal cell score based on Chen et al.
  • Chen_Goblet_Score: Goblet cell score from Chen et al.
  • Chen_Krt8_Score: KRT8-expressing cell score from Chen et al.
  • Chen_Proliferation_Score: Proliferation score based on Chen et al.
  • Chen_Club_Progenitor_Score: Club progenitor score from Chen et al.
  • Chen_AT1_AT2_Score: Combined AT1 and AT2 score from Chen et al.
  • Chen_Activated_Club_Score: Activated club cell score from Chen et al.
  • Chen_Tumour_Score: Tumour cell score based on Chen et al.
  • Chen_DATP_Score: DATP score from Chen et al.
  • Chen_PATS_Score: PATS score from Chen et al.
  • Goldfarbmuren_SMG_Basal_Score: SMG basal score from Goldfarbmuren et al.
  • Goldfarbmuren_Ciliated_Score: Ciliated cell score from Goldfarbmuren et al.
  • Goldfarbmuren_Diff_Basal_Score: Differentiated basal cell score from Goldfarbmuren et al.
  • Goldfarbmuren_Ionocytes_Tuft_Score: Ionocyte and tuft cell score from Goldfarbmuren et al.
  • Goldfarbmuren_Krt8_High_Score: High KRT8 expression score from Goldfarbmuren et al.
  • Goldfarbmuren_Mucus_Secretory_Score: Mucus secretory cell score from Goldfarbmuren et al.
  • Goldfarbmuren_PNEC_Score: PNEC cell score from Goldfarbmuren et al.
  • Goldfarbmuren_Proliferating_Basal_Score: Proliferating basal score from Goldfarbmuren et al.
  • Goldfarbmuren_Proteasomal_Basal_Score: Proteasomal basal cell score from Goldfarbmuren et al.
  • Goldfarbmuren_SMG_Secretory_Score: SMG secretory cell score from Goldfarbmuren et al.
  • Goldfarbmuren_Core_Response_Down_Score: Core response down-regulation score from Goldfarbmuren et al.
  • Goldfarbmuren_Core_Response_Up_Score: Core response up-regulation score from Goldfarbmuren et al.
  • integrated_snn_res.0.6: Seurat cluster resolution
  • seurat_clusters: Cluster assignments from Seurat analysis
  • integrated_snn_res.0.4: Seurat cluster resolution (alternative)
  • celltypes: Cell type annotations (e.g., basal, club, etc.)

Human_tracheal_epithelial_harmony_seurat.rds

This Seurat object contains harmonised data from human tracheal epithelial cells sampled from current-smoker and non-smoker individuals. The dataset spans multiple studies and has been integrated for downstream analysis.

• Metadata columns:
  • orig.ident: Original identifier for the sample
  • nCount_RNA: Total RNA count per cell
  • nFeature_RNA: Number of features detected per cell
  • Donor: Pseudonymized identifier for the individual from whom the sample was obtained
  • Sample: Sample identifier
  • Method: Method of RNA extraction or processing
  • Sex: Biological sex of the donor
  • age_range: Broad age category of the donor
  • Smoking_status: Smoking status of the donor (current-smoker, non-smoker)
  • dataset: Dataset identifier included
  • nUMI: Total UMI counts per cell
  • nGene: Total gene count per cell
  • log10GenesPerUMI: Log-transformed number of genes per UMI
  • Batch: Batch number for sample processing
  • percent.mito: Percentage of mitochondrial genes detected
  • percent.ribo: Percentage of ribosomal genes detected
  • RNA_snn_res.0.6: Seurat cluster resolution
  • seurat_clusters: Cluster assignments from Seurat analysis
  • Cluster_Annotations: Cell type or cluster annotation

Murine_Variant_Calls.xlsx

This file contains a list of annotated substitutions and indels detected across murine clones from NTCU-treated mice. The variants were identified using low-input whole-genome sequencing (WGS).

• Columns:
  • mouseID: Identifier for each mouse in the study
  • VariantID: Unique identifier for the detected variant
  • Chrom: Chromosome where the variant was located
  • Pos: Position of the variant on the chromosome
  • Ref: Reference allele
  • Alt: Alternate allele
  • Qual: Quality score for the variant
  • Filter: Filter status (passed/failed)
  • Gene: Gene affected by the variant
  • Transcript: Transcript associated with the variant
  • RNA: RNA sequence affected by the variant
  • CDS: Coding sequence affected by the variant
  • Protein: Protein sequence affected by the variant
  • Type: Type of variant (SNV, insertion, deletion)
  • Effect: Predicted functional effect (missense, silent, etc.)
  • sampleID: Identifier for the sample
  • Mut_Frags: Number of mutant fragments detected
  • mut_id: Mutation identifier
  • mutID_sampleID: Combination of mutation ID and sample ID
  • coverage: Sequencing coverage at the variant site
  • vaf: Variant allele frequency (VAF)
  • cluster_id: ID of the genomic cluster to which the variant belongs
  • lung_id: Identifier for the anotomical site of lung
  • mouseID_cluster: Combination of mouse ID and cluster ID

Key Information Sources

1. Single-cell RNA sequencing (scRNA-seq) data from mouse and human tracheal epithelial cells was used in the analysis.
2. Whole-genome sequencing (WGS) for annotated substitutions and indels was used to identify variants in murine clones, based on samples obtained through laser capture microdissection.

Code/Software

R and Seurat are required to run the analysis. The Seurat version used for the analysis is 5.0.1.
The script used for data processing and integration is provided on https://zenodo.org/records/15168190. Annotations are included throughout the script to explain the major steps, from data loading and cleaning to clustering and visualization.