Automated Author ProfileTebbenkamp, AT
Tebbenkamp, AT
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.8 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
NDAR Data for this study consist of Whole Exome sequencing for the additional 56 families from SSC collection. Other Whole Exome sequencing data and results used in this study were originally published elsewhere. NDAR Studies 340, 320, and 317 describe the data published in Iossifov et al., 2012; Neale et al., 2012; O'Roak et al., 2012b, respectively, as cited in this publication. The RNA-Seq data from this publication are available from NCBI at the given BioProject accession.Autism spectrum disorder (ASD) is a complex developmental syndrome of unknown etiology. Recent studies employing exome- and genome-wide sequencing have identified nine high-confidence ASD (hcASD) genes. Working from the hypothesis that ASD-associated mutations in these biologically pleiotropic genes will disrupt intersecting developmental processes to contribute to a common phenotype, we have attempted to identify time periods, brain regions, and cell types in which these genes converge. We have constructed coexpression networks based on the hcASD "seed" genes, leveraging a rich expression data set encompassing multiple human brain regions across human development and into adulthood. By assessing enrichment of an independent set of probable ASD (pASD) genes, derived from the same sequencing studies, we demonstrate a key point of convergence in midfetal layer 5/6 cortical projection neurons. This approach informs when, where, and in what cell types mutations in these specific genes may be productively studied to clarify ASD pathophysiology.
Authors
- Et Al. ;
- Xu, X ;
- Lu, C ;
- Liu, L ;
- Liu, W ;
- Lei, J ;
- Klei, L ;
- Hoffman, EJ ;
- He, X ;
- Han, W ;
- Gupta, AR ;
- Gockley, J ;
- Ercan-Sencicek, AG ;
- Cotney, J ;
- Niu, W ;
- Bichsel, C ;
- Murtha, MT ;
- Miller, JA ;
- Fertuzinhos, S ;
- Lin, L ;
- Reilly, SK ;
- Muhle, RA ;
- Tebbenkamp, AT ;
- Dong, S ;
- Li, M ;
- Sanders, SJ ;
- Willsey, AJ