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NDAR provides a single access to de-identified autism research data. For permission to download data, you will need an NDAR account with approved access to NDAR or a connected repository (AGRE, IAN, or the ATP). For NDAR access, you need to be a research investigator sponsored by an NIH recognized institution with federal wide assurance. See Request Access for more information.

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Format should be in the following format: Activity Code, Institute Abbreviation, and Serial Number. Grant Type, Support Year, and Suffix should be excluded. For example, grant 1R01MH123456-01A1 should be entered R01MH123456

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Title, investigators, and Collection Description may be edited along with the Collection Phase. For Collection Phase, the options Pre-enrollment, Enrollment, and Completed can be chosen allowing the Collection Owner to indicate the stage of data collection.

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The ability to associate the funding source for the project is provided. For NIH funded grants, linkage to Project Reporter information (e.g. R01MH123456) is supported. Projects funded by others, including the URL of the project, are listed. Non NIH funded projects will become available here to link that data with the appropriate funding agency.

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Collection Summary Collection Charts
Collection Title Collection Investigators Collection Description
Genomic Identification of Autism Loci
Evan E Eichler 
The goal of this grant is to use a targeted approach to identify the genes responsible for autism. Three different approaches were put forward to focus on genomic regions associated with autism, each was a dedicated specific aim.
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NIH - Extramural None

sequencing_files_readme_col_1878.pdf Background Readme for sequencing files Qualified Researchers
http://www.nature.com/ng/journal/v43/n6/full/ng.835.html Publication Exome sequencing in sporadic autism spectrum disorders identifies severe de novo mutations Qualified Researchers
http://www.nature.com/ng/journal/v43/n6/full/ng.835.html Software Exome sequencing in sporadic autism spectrum disorders identifies severe de novo mutations Qualified Researchers

R01HD065285-01 Genomic Identification of Autism Loci 09/30/2009 08/31/2011 Not Reported Not Reported UNIVERSITY OF WASHINGTON $2,623,078.00

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:


To create a new Omics, eye tracking, fMRI, or EEG experiment, press the "+ New Experiment" button. Once an experiment is created, then raw files for these types of experiments should be provided, associating the experiment – through Experiment_ID – with the metadata defined in the experiments interface.

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Shared Data

Data structures with the number of subjects submitted and shared are provided.

Genomics Sample Genomics 6842
Genomics Subject Genomics 6284

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:


Publications relevant to NDAR data are listed below. Most displayed publications have been associated with the grant within Pubmed. Use the "+ New Publication" button to add new publications. Publications relevant/not relevant to data expected are categorized. Relevant publications are then linked to the underlying data by selecting the Create Study link. Study provides the ability to define cohorts, assign subjects, define outcome measures and lists the study type, data analysis and results. Analyzed data and results are expected in this way.

PubMed IDStudyTitleJournalAuthorsDateStatus
28408746Create StudyNovel metrics to measure coverage in whole exome sequencing datasets reveal local and global non-uniformity.Scientific reportsWang Q, Shashikant CS, Jensen M, Altman NS, Girirajan SApril 13, 2017Not Determined
24360806Study (371)Rare-variant extensions of the transmission disequilibrium test: application to autism exome sequence data.American journal of human geneticsHe Z, O'Roak BJ, Smith JD, Wang G, Hooker S, Santos-Cortez RL, Li B, Kan M, Krumm N, Nickerson DA, Shendure J, Eichler EE, Leal SMJanuary 2, 2014Relevant
24035194Study (312)Transmission disequilibrium of small CNVs in simplex autism.American journal of human geneticsKrumm N, O'Roak BJ, Karakoc E, Mohajeri K, Nelson B, Vives L, Jacquemont S, Munson J, Bernier R, Eichler EEOctober 3, 2013Relevant
23375656Study (301)Refinement and discovery of new hotspots of copy-number variation associated with autism spectrum disorder.American journal of human geneticsGirirajan S, Dennis MY, Baker C, Malig M, Coe BP, Campbell CD, Mark K, Vu TH, Alkan C, Cheng Z, Biesecker LG, Bernier R, Eichler EEFebruary 7, 2013Relevant
23160955Study (320)Multiplex targeted sequencing identifies recurrently mutated genes in autism spectrum disorders.Science (New York, N.Y.)O'Roak BJ, Vives L, Fu W, Egertson JD, Stanaway IB, Phelps IG, Carvill G, Kumar A, Lee C, Ankenman K, Munson J, Hiatt JB, Turner EH, Levy R, O'Day DR, Krumm N, Coe BP, Martin BK, Borenstein E, Nickerson DA, Mefford HC, Doherty D, Akey JM, Bernier R, Eichler EE, et al.December 21, 2012Relevant
22970919Create StudyPhenotypic heterogeneity of genomic disorders and rare copy-number variants.The New England journal of medicineGirirajan S, Rosenfeld JA, Coe BP, Parikh S, Friedman N, Goldstein A, Filipink RA, McConnell JS, Angle B, Meschino WS, Nezarati MM, Asamoah A, Jackson KE, Gowans GC, Martin JA, Carmany EP, Stockton DW, Schnur RE, Penney LS, Martin DM, Raskin S, Leppig K, Thiese H, Smith R, Aberg E, et al.October 4, 2012Not Relevant
22585873Create StudyCopy number variation detection and genotyping from exome sequence data.Genome researchKrumm N, Sudmant PH, Ko A, O'Roak BJ, Malig M, Coe BP, , Quinlan AR, Nickerson DA, Eichler EEAugust 2012Not Determined
22495309Study (316)Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations.NatureO'Roak BJ, Vives L, Girirajan S, Karakoc E, Krumm N, Coe BP, Levy R, Ko A, Lee C, Smith JD, Turner EH, Stanaway IB, Vernot B, Malig M, Baker C, Reilly B, Akey JM, Borenstein E, Rieder MJ, Nickerson DA, Bernier R, Shendure J, Eichler EEMay 10, 2012Relevant
22365152Create StudyDe novo pathogenic SCN8A mutation identified by whole-genome sequencing of a family quartet affected by infantile epileptic encephalopathy and SUDEP.American journal of human geneticsVeeramah KR, O'Brien JE, Meisler MH, Cheng X, Dib-Hajj SD, Waxman SG, Talwar D, Girirajan S, Eichler EE, Restifo LL, Erickson RP, Hammer MFMarch 9, 2012Not Relevant
22179552Study (324)Detection of structural variants and indels within exome data.Nature methodsKarakoc E, Alkan C, O'Roak BJ, Dennis MY, Vives L, Mark K, Rieder MJ, Nickerson DA, Eichler EEFebruary 2012Relevant
22102821Create StudyRelative burden of large CNVs on a range of neurodevelopmental phenotypes.PLoS geneticsGirirajan S, Brkanac Z, Coe BP, Baker C, Vives L, Vu TH, Shafer N, Bernier R, Ferrero GB, Silengo M, Warren ST, Moreno CS, Fichera M, Romano C, Raskind WH, Eichler EENovember 2011Not Determined
22095694Create StudyEvidence for involvement of GNB1L in autism.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric GeneticsChen YZ, Matsushita M, Girirajan S, Lisowski M, Sun E, Sul Y, Bernier R, Estes A, Dawson G, Minshew N, Shellenberg GD, Eichler EE, Rieder MJ, Nickerson DA, Tsuang DW, Tsuang MT, Wijsman EM, Raskind WH, Brkanac ZJanuary 2012Not Relevant
21854229Create StudyHuman copy number variation and complex genetic disease.Annual review of geneticsGirirajan S, Campbell CD, Eichler EE2011Not Relevant
21841781Create StudyA copy number variation morbidity map of developmental delay.Nature geneticsCooper GM, Coe BP, Girirajan S, Rosenfeld JA, Vu TH, Baker C, Williams C, Stalker H, Hamid R, Hannig V, Abdel-Hamid H, Bader P, McCracken E, Niyazov D, Leppig K, Thiese H, Hummel M, Alexander N, Gorski J, Kussmann J, Shashi V, Johnson K, Rehder C, Ballif BC, Shaffer LG, et al.September 2011Not Relevant
21731881Create StudySpeech delays and behavioral problems are the predominant features in individuals with developmental delays and 16p11.2 microdeletions and microduplications.Journal of neurodevelopmental disordersRosenfeld JA, Coppinger J, Bejjani BA, Girirajan S, Eichler EE, Shaffer LG, Ballif BCMarch 2010Not Relevant
21572417Study (323)Exome sequencing in sporadic autism spectrum disorders identifies severe de novo mutations.Nature geneticsO'Roak BJ, Deriziotis P, Lee C, Vives L, Schwartz JJ, Girirajan S, Karakoc E, Mackenzie AP, Ng SB, Baker C, Rieder MJ, Nickerson DA, Bernier R, Fisher SE, Shendure J, Eichler EEJune 2011Relevant
20154674Create StudyA recurrent 16p12.1 microdeletion supports a two-hit model for severe developmental delay.Nature geneticsGirirajan S, Rosenfeld JA, Cooper GM, Antonacci F, Siswara P, Itsara A, Vives L, Walsh T, McCarthy SE, Baker C, Mefford HC, Kidd JM, Browning SR, Browning BL, Dickel DE, Levy DL, Ballif BC, Platky K, Farber DM, Gowans GC, Wetherbee JJ, Asamoah A, Weaver DD, Mark PR, Dickerson J, et al.March 2010Not Relevant
19846438Create StudyTargeted interrogation of copy number variation using SCIMMkit.Bioinformatics (Oxford, England)Zerr T, Cooper GM, Eichler EE, Nickerson DAJanuary 1, 2010Not Relevant

The Data Expected tab is a tracking and scheduling tool. It displays the data that is expected from the project, along with final expected enrollment counts and initial dates for the submission and sharing of the data. There are two types of Data Expected displayed:

  1. Data Expected from Relevant Publications: Publications reported in association with the Collection’s grant and determined as relevant to data expected for sharing are listed first. Any data specific to these publications are expected to be shared using the NDA Study feature. If a publication on this list is marked relevant in error, the PI of the project can correct the status in the Publications tab. Once created Studies are visible in the Associated Studies tab. When sharing a Study, only the outcome measures for the subjects/time-points specific to the publication are shared. Other data with share dates that have not yet been met as defined below remain embargoed. Investigators can initiate Study creation from this page when logged in.
  2. Data Expected by Data Structure: The table displayed second is defined by the investigator and lists all of the measures expected for sharing as defined in the Data Dictionary. Targeted Enrollment indicates the expected final unique subject count for that structure. Initial submission dates indicate when NDA should expect the first upload of those data, and initial sharing dates indicate when the first round of those data is expected to be shared. Click the i next to the Data Expected title to view the structures that are counted within that item.

Those with Administrator control over the Collection may also use the Data Expected tab to request an exemption period from an expected biannual submission by providing a timeframe and reason, and then saving the Collection. Please note the program officer of the associated grant may review this request.

Relevant Publications
PubMed IDStudyTitleJournalAuthorsDate
No records found.

You can use "Add New Data Expected" to add exsiting structures and create your project's list. However, this is also the method you can use to request new structures be created for your project. When adding the Data Expected item, if the structure already exists you can locate it and specify your dates and enrollment. To add a new structure and request it be defined in the Data Dictionary, select Upload Definition and attach the definition or material needed to create it, including manual, codebooks, forms, etc. If you have multiple files, please upload a zipped archive containing them all.

Expected dates should be selected based on the standard Data Sharing Regimen and are restricted to within date ranges based on the project start and end dates.

Data Expected
Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
genomics/omics info iconApproved
Structure not yet defined

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Associated Studies

Studies that have been defined using data from a Collection are important criteria to determine the value of data shared. The number of subjects column displays the counts from this Collection that are included in a Study, out of the total number of subjects in that study. The Data Use column represents whether or not the study is a primary analysis of the data or a secondary analysis. State indicates whether the study is private or shared with the research community.

Study Name Description Number of Subjects
Collection / Total
Data Use State
Detection of structural variants and indels within exome data. We report an algorithm to detect structural variation and indels from 1 base pair (bp) to 1 Mbp within exome sequence data sets. Splitread uses one end-anchored placements to cluster the mappings of subsequences of unanchored ends to identify the size, content and location of variants with high specificity and sensitivity. The algorithm discovers indels, structural variants, de novo events and copy number-polymorphic processed pseudogenes missed by other methods. 60 / 60 Primary Analysis Shared
Exome sequencing in sporadic autism spectrum disorders identifies severe de novo mutations Evidence for the etiology of autism spectrum disorders (ASDs) has consistently pointed to a strong genetic component complicated by substantial locus heterogeneity. We sequenced the exomes of 20 individuals with sporadic ASD (cases) and their parents, reasoning that these families would be enriched for de novo mutations of major effect. We identified 21 de novo mutations, 11 of which were protein altering. Protein-altering mutations were significantly enriched for changes at highly conserved residues. We identified potentially causative de novo events in 4 out of 20 probands, particularly among more severely affected individuals, in FOXP1, GRIN2B, SCN1A and LAMC3. In the FOXP1 mutation carrier, we also observed a rare inherited CNTNAP2 missense variant, and we provide functional support for a multi-hit model for disease risk. Our results show that trio-based exome sequencing is a powerful approach for identifying new candidate genes for ASDs and suggest that de novo mutations may contribute substantially to the genetic etiology of ASDs. 60 / 60 Primary Analysis Shared
The evolution and population diversity of human-specific segmental duplications Segmental duplications contribute to human evolution, adaptation and genomic instability but are often poorly characterized. We investigate the evolution, genetic variation and coding potential of human-specific segmental duplications (HSDs). We identify 218 HSDs based on analysis of 322 deeply sequenced archaic and contemporary hominid genomes. We sequence 550 human and nonhuman primate genomic clones to reconstruct the evolution of the largest, most complex regions with protein-coding potential (n=80 genes/33 gene families). We show that HSDs are non-randomly organized, associate preferentially with ancestral ape duplications termed “core duplicons”, and evolved primarily in an interspersed inverted orientation. In addition to Homo sapiens-specific gene expansions (e.g., TCAF1/2), we highlight ten gene families (e.g., ARHGAP11B and SRGAP2C) where copy number never returns to the ancestral state, there is evidence of mRNA splicing, and no common gene-disruptive mutations are observed in the general population. Such duplicates are candidates for the evolution of human-specific adaptive traits. 1731 / 6360 Primary Analysis Shared
Refinement and discovery of new hotspots of copy-number variation associated with autism spectrum disorder. Rare copy-number variants (CNVs) have been implicated in autism and intellectual disability. These variants are large and affect many genes but lack clear specificity toward autism as opposed to developmental-delay phenotypes. We exploited the repeat architecture of the genome to target segmental duplication-mediated rearrangement hotspots (n = 120, median size 1.78 Mbp, range 240 kbp to 13 Mbp) and smaller hotspots flanked by repetitive sequence (n = 1,247, median size 79 kbp, range 3-96 kbp) in 2,588 autistic individuals from simplex and multiplex families and in 580 controls. Our analysis identified several recurrent large hotspot events, including association with 1q21 duplications, which are more likely to be identified in individuals with autism than in those with developmental delay (p = 0.01; OR = 2.7). Within larger hotspots, we also identified smaller atypical CNVs that implicated CHD1L and ACACA for the 1q21 and 17q12 deletions, respectively. Our analysis, however, suggested no overall increase in the burden of smaller hotspots in autistic individuals as compared to controls. By focusing on gene-disruptive events, we identified recurrent CNVs, including DPP10, PLCB1, TRPM1, NRXN1, FHIT, and HYDIN, that are enriched in autism. We found that as the size of deletions increases, nonverbal IQ significantly decreases, but there is no impact on autism severity; and as the size of duplications increases, autism severity significantly increases but nonverbal IQ is not affected. The absence of an increased burden of smaller CNVs in individuals with autism and the failure of most large hotspots to refine to single genes is consistent with a model where imbalance of multiple genes contributes to a disease state. 3285 / 3285 Primary Analysis Shared
Transmission disequilibrium of small CNVs in simplex autism. Cohorts: 411 ASD Quads from Simons Simplex Collection 177 Quads from Sanders et al. (PubMed ID: 22495306) 166 Quads from I. Iossifov et al. (PubMed ID: 22542183) 71 Quads from O'Roak et al. (PubMed ID: 22495309) Publication Abstract: We searched for disruptive, genic rare copy-number variants (CNVs) among 411 families affected by sporadic autism spectrum disorder (ASD) from the Simons Simplex Collection by using available exome sequence data and CoNIFER (Copy Number Inference from Exome Reads). Compared to high-density SNP microarrays, our approach yielded ¿2× more smaller genic rare CNVs. We found that affected probands inherited more CNVs than did their siblings (453 versus 394, p = 0.004; odds ratio [OR] = 1.19) and that the probands' CNVs affected more genes (921 versus 726, p = 0.02; OR = 1.30). These smaller CNVs (median size 18 kb) were transmitted preferentially from the mother (136 maternal versus 100 paternal, p = 0.02), although this bias occurred irrespective of affected status. The excess burden of inherited CNVs among probands was driven primarily by sibling pairs with discordant social-behavior phenotypes (p < 0.0002, measured by Social Responsiveness Scale [SRS] score), which contrasts with families where the phenotypes were more closely matched or less extreme (p > 0.5). Finally, we found enrichment of brain-expressed genes unique to probands, especially in the SRS-discordant group (p = 0.0035). In a combined model, our inherited CNVs, de novo CNVs, and de novo single-nucleotide variants all independently contributed to the risk of autism (p < 0.05). Taken together, these results suggest that small transmitted rare CNVs play a role in the etiology of simplex autism. Importantly, the small size of these variants aids in the identification of specific genes as additional risk factors associated with ASD. 1644 / 1644 Secondary Analysis Shared
Recurrent de novo mutations implicate novel genes underlying simplex autism risk. Autism spectrum disorder (ASD) has a strong but complex genetic component. Here we report on the resequencing of 64 candidate neurodevelopmental disorder risk genes in 5,979 individuals: 3,486 probands and 2,493 unaffected siblings. We find a strong burden of de novo point mutations for these genes and specifically implicate nine genes. These include CHD2 and SYNGAP1, genes previously reported in related disorders, and novel genes TRIP12 and PAX5. We also show that mutation carriers generally have lower IQs and enrichment for seizures. These data begin to distinguish genetically distinct subtypes of autism important for aetiological classification and future therapeutics. 1182 / 6400 Primary Analysis Shared
Rare-Variant Extensions of the Transmission Disequilibrium Test: Application to Autism Exome Sequence Data Many population-based rare-variant (RV) association tests, which aggregate variants across a region, have been developed to analyze sequence data. A drawback of analyzing population-based data is that it is difficult to adequately control for population substructure and admixture, and spurious associations can occur. For RVs, this problem can be substantial, because the spectrum of rare variation can differ greatly between populations. A solution is to analyze parent-child trio data, by using the transmission disequilibrium test (TDT), which is robust to population substructure and admixture. We extended the TDT to test for RV associations using four commonly used methods. We demonstrate that for all RV-TDT methods, using proper analysis strategies, type I error is well-controlled even when there are high levels of population substructure or admixture. For trio data, unlike for population-based data, RV allele-counting association methods will lead to inflated type I errors. However type I errors can be properly controlled by obtaining p values empirically through haplotype permutation. The power of the RV-TDT methods was evaluated and compared to the analysis of case-control data with a number of genetic and disease models. The RV-TDT was also used to analyze exome data from 199 Simons Simplex Collection autism trios and an association was observed with variants in ABCA7. Given the problem of adequately controlling for population substructure and admixture in RV association studies and the growing number of sequence-based trio studies, the RV-TDT is extremely beneficial to elucidate the involvement of RVs in the etiology of complex traits. 567 / 567 Primary Analysis Shared
Multiplex Targeted Sequencing Identifies Recurrently Mutated Genes in Autism Spectrum Disorders Abstract: Exome sequencing studies of autism spectrum disorders (ASDs) have identified many de novo mutations but few recurrently disrupted genes. We therefore developed a modified molecular inversion probe method enabling ultra-low-cost candidate gene resequencing in very large cohorts. To demonstrate the power of this approach, we captured and sequenced 44 candidate genes in 2446 ASD probands. We discovered 27 de novo events in 16 genes, 59% of which are predicted to truncate proteins or disrupt splicing. We estimate that recurrent disruptive mutations in six genes-CHD8, DYRK1A, GRIN2B, TBR1, PTEN, and TBL1XR1¿may contribute to 1% of sporadic ASDs. Our data support associations between specific genes and reciprocal subphenotypes (CHD8-macrocephaly and DYRK1A-microcephaly) and replicate the importance of a B-catenin-chromatin-remodeling network to ASD etiology. 3262 / 3262 Primary Analysis Shared
The contribution of de novo coding mutations to autism spectrum disorder 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 2426 / 9456 Secondary Analysis Shared
Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. In addition to cohorts of Parents (N=418), Siblings (N=50), and Probands (N=209), the publication publication describes a subset of male (N=47) and female (N=26) autistic subjects, with significant impairment and intellectual disability, and with cognitive impairment, respectively. These subsets have been defined based on hi/low IQ value in Supplementary Table 1 from the publication. Publication Abstract: It is well established that autism spectrum disorders (ASD) have a strong genetic component; however, for at least 70% of cases, the underlying genetic cause is unknown. Under the hypothesis that de novo mutations underlie a substantial fraction of the risk for developing ASD in families with no previous history of ASD or related phenotypes--so-called sporadic or simplex families--we sequenced all coding regions of the genome (the exome) for parent-child trios exhibiting sporadic ASD, including 189 new trios and 20 that were previously reported. Additionally, we also sequenced the exomes of 50 unaffected siblings corresponding to these new (n = 31) and previously reported trios (n = 19), for a total of 677 individual exomes from 209 families. Here we show that de novo point mutations are overwhelmingly paternal in origin (4:1 bias) and positively correlated with paternal age, consistent with the modest increased risk for children of older fathers to develop ASD. Moreover, 39% (49 of 126) of the most severe or disruptive de novo mutations map to a highly interconnected l-catenin/chromatin remodelling protein network ranked significantly for autism candidate genes. In proband exomes, recurrent protein-altering mutations were observed in two genes: CHD8 and NTNG1. Mutation screening of six candidate genes in 1,703 ASD probands identified additional de novo, protein-altering mutations in GRIN2B, LAMC3 and SCN1A. Combined with copy number variant (CNV) data, these results indicate extreme locus heterogeneity but also provide a target for future discovery, diagnostics and therapeutics. 677 / 677 Primary Analysis Shared
* Data not on individual level