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Publication Details

Results for Ruzzo2019:

Summary
Title Inherited and De Novo Genetic Risk for Autism Impacts Shared Networks
AuthorsRuzzo, E.K., Pérez-Cano, L., Jung, J.-Y., Wang, L., Kashef-Haghighi, D., Hartl, C., Singh, C., Xu, J., Hoekstra, J.N., Leventhal, O., Leppä, V.M., Gandal, M.J., Paskov, K., Stockham, N., Polioudakis, D., Lowe, J.K., Prober, D.A., Geschwind, D.H., Wall, D.P.
TechnologyWhole genome sequencing
Variant sourceMultiplex families were sequenced and de novo and inherited variants were recalled using a machine learning algorithm
CohortsiHart
DesignMultiplex
URLhttps://dx.doi.org/10.1016/j.cell.2019.07.015
Pubmed28325891
Subject count790
The number of subjects for this study could not be determined directly from the variant data; the value given is that reported by the authors in the publication.
Variant event count6209
Curation notesView
Breakdown by exonic function
FunctionVariant Count
frameshift deletion1782
frameshift insertion749
nonframeshift deletion29
nonsynonymous SNV157
other64
splicing1238
stopgain2161
stoploss3
synonymous SNV1
unknown25

What am I looking at?

Summary: Information from the literature piece (e.g. Author, Publisher, DOI) and the study experimental design (e.g. sample size, source of probands, sequencing technology.) For a full list of sources of variants, be sure to check out the publications page. Documentation and description of our work can be found on the help page.

Breakdown by exonic function: We annotated the variants with an effect prediction using ANNOVAR. The functions are categories of variants, such as frameshift variants (i.e. frameshift_elongation (SO:0001909)), loss/gain of stop codon, SNVs and non-frameshift variants. See the full list of possible annotations for exonic variants in the documentation.