Data Sources

Document the origin, structure, and preprocessing of datasets used in your project. This section supports transparency, reproducibility, and critical appraisal of the underlying evidence base.

Source Datasets and Descriptions

• Where did each dataset originate (e.g., public database, collaborator, institutional study)?
  • Example: GTEx v8 RNA-seq data for 17 tissues; dbGaP accession phs001234.v1 for whole-genome sequencing of PAH cohort.
• What kind of data is included (e.g., raw FASTQ, VCF, count matrices, clinical annotations)?
  • Example: Processed gene counts (TPM, raw) and matched genotype data for 300 individuals.

Cohorts and Sample Sizes

• What populations or models are represented?
  • Example: 105 BMPR2 mutation carriers (40 affected, 65 unaffected); 50 healthy controls.
• Are there subgroups of interest (e.g., stratified by sex, ancestry, disease subtype)?
  • Example: Stratification by WHO PAH subtype and family structure.

Preprocessing or Curation Steps

• What transformations were applied to the raw data?
  • Example: Adapter trimming with Trim Galore, alignment with STAR, quantification via featureCounts.
• How was quality control performed?
  • Example: Excluded samples with <70% mapping rate or <10M reads; removed genes with low variance across all samples.
• Were any samples excluded or imputed? Why?
  • Example: Imputed missing genotypes using Beagle; removed mislabeled samples based on genotype PCA.

Data Use and Access

• What are the data access constraints (e.g., open access, dbGaP-controlled, IRB approval)?
• Are any datasets sensitive (e.g., human subject data, Indigenous-controlled datasets)? What restrictions apply?