---

type: allele_score
allele_score_mode: substitutions

table:
  filename: whole_genome_SNVs.tsv.gz
  format: tabix
  chrom_mapping:
    add_prefix: chr

  # defined by score_type
  chrom:
    name: Chrom
  pos_begin:
    name: Pos
  reference:
    name: Ref
  alternative:
    name: Alt

# score values
scores:
  - id: cadd_raw
    type: float
    name: RawScore
    desc: |
      CADD raw score for functional prediction of a SNP. The larger the score 
      the more likely the SNP has damaging effect
    large_values_desc: "more damaging"
    small_values_desc: "less damaging"
    histogram:
      type: number
      number_of_bins: 100
      view_range:
        min: -8.0
        max: 36.0
      y_log_scale: True
  
  - id: cadd_phred
    type: float
    name: PHRED
    desc: |
      CADD phred-like score. This is phred-like rank score based on whole
      genome CADD raw scores. The larger the score the more likely the SNP
      has damaging effect.
    large_values_desc: "more damaging"
    small_values_desc: "less damaging"
    histogram:
      type: number
      number_of_bins: 100
      view_range:
        min: 0.0
        max: 99.0
      y_log_scale: True

default_annotation:
  - source: cadd_raw
    name: cadd_raw

  - source: cadd_phred
    name: cadd_phred

meta:
  summary: |
    CADD (Combined Annotation Dependent Depletion score) predicts the potential impact of a SNP     
  description: |
    [CADD](https://cadd.gs.washington.edu/) (Combined Annotation Dependent Depletion) scores the deleteriousness of single nucleotide variants, multi-nucleotide substitutions, and indels by integrating diverse annotations into a single metric. Unlike tools limited to specific information types or variant categories, CADD combines naturally selected and simulated mutations for a comprehensive assessment. CADD scores correlate with allelic diversity, coding and non-coding pathogenicity, and regulatory effects, effectively prioritizing causal variants across varied functional categories and genetic architectures. Additionally, CADD scores for complex trait-associated variants from GWAS correlate with study sample size, making it a valuable tool in research and clinical settings.

    [Schubach et al., CADD v1.7: Using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions. Nucleic Acids Research 2024](https://academic.oup.com/nar/article/52/D1/D1143/7511313)

    [Kircher et al., A general framework for estimating the relative pathogenicity of human genetic variants, Nature Genetics 2014](https://www.nature.com/articles/ng.2892)

    Downloaded on: 10/24/24

    [https://krishna.gs.washington.edu/download/CADD/v1.7/GRCh38/whole\_genome\_SNVs.tsv.gz](https://krishna.gs.washington.edu/download/CADD/v1.7/GRCh38/whole_genome_SNVs.tsv.gz)
    [https://krishna.gs.washington.edu/download/CADD/v1.7/GRCh38/whole\_genome\_SNVs.tsv.gz.tbi](https://krishna.gs.washington.edu/download/CADD/v1.7/GRCh38/whole_genome_SNVs.tsv.gz.tbi)

  labels:
    reference_genome: hg38/genomes/GRCh38-hg38
