Automated Author ProfileYoon,
Yoon,
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: 3.2 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.PLEASE NOTE: Additional data on these subjects, unrelated to this publication exist in other NDAR Studies. These data include realigned BAM files, unfiltered SNV/InDel variant calls (made by GATK and FreeBayes), and CNVs. Please see this news item for more details: https://ndar.nih.gov/ndarpublicweb/aboutNDAR.html#news_item_201
Authors
- Wigler, M ;
- Iossifov, ;
- I., ;
- O'Roak, ;
- B.J., ;
- Sanders, ;
- S.J., ;
- Ronemus, ;
- M., ;
- Krumm, ;
- N., ;
- Levy, ;
- D., ;
- Stessman, ;
- H.A., ;
- Witherspoon, ;
- K.T., ;
- Vives, ;
- L., ;
- Patterson, ;
- K.E., ;
- Smith, ;
- J.D., ;
- Paeper, ;
- B., ;
- Nickerson, ;
- D.A., ;
- Dea, ;
- J., ;
- Dong, ;
- S., ;
- Gonzalez, ;
- L.E., ;
- Mandell, ;
- J.E., ;
- Mane, ;
- S.M., ;
- Murtha, ;
- M.T., ;
- Sullivan, ;
- C.A., ;
- Walker, ;
- M.F., ;
- Waqar, ;
- Z., ;
- Wei, ;
- L., ;
- Willsey, ;
- A.J., ;
- Yamrom, ;
- B., ;
- Lee, ;
- Y.H., ;
- Grabowska, ;
- E., ;
- Dalkic, ;
- E., ;
- Wang, ;
- Z., ;
- Marks, ;
- S., ;
- Andrews, ;
- P., ;
- Leotta, ;
- A., ;
- Kendall, ;
- J., ;
- Hakker, ;
- I., ;
- Rosenbaum, ;
- J., ;
- Ma, ;
- B., ;
- Rodgers, ;
- L., ;
- Troge, ;
- J., ;
- Narzisi, ;
- G., ;
- Yoon, ;
- S., ;
- Schatz, ;
- M.C., ;
- Ye, ;
- K., ;
- McCombie, ;
- W.R., ;
- Shendure, ;
- J., ;
- Eichler, ;
- E.E., ;
- State, ;
- M.W,