CADD pipeline

CADD specifications

Information


Unique identifier OMICS_02627
Name CADD
Alternative name Combined Annotation Dependent Depletion
Software type Package/Module
Interface Command line interface
Restrictions to use Academic or non-commercial use
Input data Nucleotide variants
Input format VCF
Operating system Unix/Linux, Mac OS
Programming languages Python
Computer skills Advanced
Version 1.3
Stability Stable
Requirements SAMtools, tabix, bx-Python, PySam, perl, Ensembl VEP
Maintained Yes

Taxon


  • Animals
    • Homo sapiens

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Maintainer


  • person_outline CADD <>

Information


Unique identifier OMICS_02627
Name CADD
Alternative name Combined Annotation Dependent Depletion
Interface Web user interface
Restrictions to use Academic or non-commercial use
Input data Nucleotide variants
Input format VCF
Programming languages Python
Computer skills Basic
Version 1.3
Stability Stable
Maintained Yes

Taxon


  • Animals
    • Homo sapiens

Maintainer


  • person_outline CADD <>

Publication for Combined Annotation Dependent Depletion

CADD citations

 (8)
2017
PMCID: 5748699

[…] genome of the netherlands (gonl) and wellderly) was set to 0.5%. this filtering resulted in 547 variants. these contained 244 missense variants which were assessed for pathogenicity clues using combined annotation dependent depletion (cadd) [6] scores and only those with a score above 15 were considered (76 variants). additionally, there were 86 splice site variants (7 covering canonical […]

2017
PMCID: 5282828

[…] information concerning variant type (valid annotations when refseq in concordance with ucsc), maf in the general population, and predictions of the variant’s effect on gene function, implementing cadd [84]., considering the worldwide prevalence of 0.041% for pd in the age range of 40–49 years [20], we selected rare variants with a maf < 1% (corresponding to a homozygous frequency of 0.01%) […]

2016
PMCID: 5221474

[…] by considering minor allele frequency (maf) of <0.05 and the availability of variants in public databases of dbsnp, clinseq and exac (the broad institute). filtered variants were annotated with cadd score using online tools [http://cadd.gs.washington.edu/score]., targeted dna resequencing was done by sanger big‐dye terminator v3.1 cycle sequencing (applied biosystems) on an abi 3730 […]

2016
PMCID: 5123402

[…] 2 × p × (1 − p) [43]. in addition, we also applied the cadd scores [11] as variant weights to the regulatory motifs. the weights were defined as the difference between raw cadd scores and the minimum cadd score scaled by the range of the raw cadd scores and were introduced into the t5 burden test using its quartic form. the analytical models were the same as described above. all analyses were carr […]

2016
PMCID: 5089441

[…] proband and less than 5% in each parent, and a minor allele frequency <1% in the 1000 genomes project and the exac. all candidate de novo variants that either affected a protein or had a scaled combined annotation dependent depletion (cadd) score >10 were manually reviewed.25 in each patient described, no other variants were identified as potentially disease causing. all de novo variants […]

CADD institution(s)
Department of Genome Sciences, University of Washington, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA; HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
CADD funding source(s)
This work was supported by National Institutes of Health (N.I.H.) grants U54HG006493, DP5OD009145 and DP1HG007811.

CADD review

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Pierre-Julien VIAILLY's avatar image No country

Pierre-Julien VIAILLY

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Combined Annotation Dependent Depletion (CADD) is a new tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions variants in the human genome. Most of pathogenicity prediction algorithms tend to exploit a single information such as conservation to create a score. CADD give a broadly applicable metric that weights and integrated diverse information using a SVM approach. It integrates multiple annotations into one metric by contrasting variants that survived natural selection with simulated mutations.

Precomputed CADD scores can be downloaded on CADD website (http://cadd.gs.washington.edu/download). Scores have been included too in dbNSFP databases.

We have demonstrated that CADD is the most sensitive and specific prediction algorithms by comparison with the ClinVar, a database which aggregates information about genomic variation and its relationship to human health.