NIMH Data Archive - Data

helpcenter.ndastudy.view-cohort

NDA Study - View Cohort

The View Cohort shows the Study cohort characteristics which will includes the name, type, sex and age in months range criteria. Note that age and sex restrict the data that can be added to the cohort. Medical criteria and phenotype are also included. Of particular importance on this page are any comments related to included subjects, which may be different than published results, often attributed to data sharing consent.

Frequently Asked Questions

How do I know the characteristics of the cohort?

The appropriate Medical Criteria, Phenotype, and Sub Type defined by the Study Owner are highlighted. The option trees are automatically expanded so the highlighted options are immediately viewable.

Glossary

Age Range

Age is expressed in months from 0 (birth) to 1200 (100 years old).
Medical Criteria

NDA defines Medical Criteria as a diagnostically based determination of an individual's disease or condition.
Phenotype

NDA defines Phenotype as any physical, morphologic, or biochemical characteristics that are observable in an individual.
Sub Types

NDA defines Sub Type as a subordinate condition or disease that further characterizes an individual.
Cohort Name

A user defined name for the cohort with a 200 character limit.
Cohort Type

Cohort Type options include Baseline, Control, and Test.
Cohort Comments

Comments further characterize the cohort beyond the options provided in the interface to define the cohort.
Cohort Subjects

The Cohort Subjects provides the number of unique subjects for whom data have been associated with the cohort.
Cohort

Summarizes the characteristics of a group of research subjects. The subject count is noted in parentheses.

Contact NDA Help Desk

Study DOI

DOI:
Title:
Description:	Autism spectrum disorder (ASD) is a neurodevelopmental disorder that causes deficits in cognition, communication and social skills. ASD, however, is a highly heterogeneous disorder. This heterogeneity has made identifying the etiology of ASD a particularly difficult challenge, as patients exhibit a wide spectrum of symptoms without any unifying genetic or environmental factors to account for the disorder. For better understanding of ASD, it is paramount to identify potential genetic and environmental risk factors that are comorbid with it. Identifying such factors is of great importance to determine potential causes for the disorder, and understand its heterogeneity. Existing large-scale datasets offer an opportunity for computer scientists to undertake this task by utilizing machine learning to reliably and efficiently obtain insight about potential ASD risk factors, which would in turn assist in guiding research in the field. In this study, decision tree algorithms were utilized to analyze related factors in datasets obtained from the National Database for Autism Research (NDAR) consisting of nearly 3000 individuals. We were able to identify 15 medical conditions that were highly associated with ASD diagnoses in patients; furthermore, we extended our analysis to the family medical history of patients and we report six potentially hereditary medical conditions associated with ASD. Associations reported had a 90% accuracy. Meanwhile, gender comparisons highlighted conditions that were unique to each gender and others that overlapped. Those findings were validated by the academic literature, thus opening the way for new directions for the use of decision tree algorithms to further understand the etiology of autism.
Publisher:
Publication Date:
Keywords:

Study DOI Status Info

DOI: 10.15154/1518655
DataCite Status: Findable
NDAR Status: Registered
DOI Registered with DataCite
Public URL Resolves at DOI

Select Subjects

Selected
No records found.

Investigators: Study Investigators	Hassan, Mariam; Mokhtar, Hoda
Abstract:	Autism spectrum disorder (ASD) is a neurodevelopmental disorder that causes deficits in cognition, communication and social skills. ASD, however, is a highly heterogeneous disorder. This heterogeneity has made identifying the etiology of ASD a particularly difficult challenge, as patients exhibit a wide spectrum of symptoms without any unifying genetic or environmental factors to account for the disorder. For better understanding of ASD, it is paramount to identify potential genetic and environmental risk factors that are comorbid with it. Identifying such factors is of great importance to determine potential causes for the disorder, and understand its heterogeneity. Existing large-scale datasets offer an opportunity for computer scientists to undertake this task by utilizing machine learning to reliably and efficiently obtain insight about potential ASD risk factors, which would in turn assist in guiding research in the field. In this study, decision tree algorithms were utilized to analyze related factors in datasets obtained from the National Database for Autism Research (NDAR) consisting of nearly 3000 individuals. We were able to identify 15 medical conditions that were highly associated with ASD diagnoses in patients; furthermore, we extended our analysis to the family medical history of patients and we report six potentially hereditary medical conditions associated with ASD. Associations reported had a 90% accuracy. Meanwhile, gender comparisons highlighted conditions that were unique to each gender and others that overlapped. Those findings were validated by the academic literature, thus opening the way for new directions for the use of decision tree algorithms to further understand the etiology of autism.
Results:	Article published in Informatics in Medicine Unlocked, July 2019.
Documents:
DOI:	10.15154/1518655
Data Usage: Study Data Usage	Secondary Analysis

In this NDA Study, data were analyzed or curated from the following NDA Collection(s):

ID	Collection	Permission Group	Subjects
1	UIC ACE: Translational Studies of Insistence on Sameness in Autism	NIMH Data Archive	303
2046	Development of a new autism screening tool for traditionally underserved families	NIMH Data Archive	251
1250	Screening and Diagnostic Measures in Toddlers with ASD	NIMH Data Archive	243
2021	Multimodal Developmental Neurogenetics of Females with ASD	NIMH Data Archive	207
2368	Clinical and Immunological Investigations of Subtypes of Autism	NIMH Data Archive	200
2020	Adaptive Interventions for Minimally Verbal Children with ASD in the Community	NIMH Data Archive	149
2063	Epidemiological Research on Autism in Jamaica - Phase II	NIMH Data Archive	135
1600	Early Autism Risk Longitudinal Investigation (EARLI) Network	NIMH Data Archive	134
2022	The Social Brain in Schizophrenia and Autism Spectrum Disorders	NIMH Data Archive	121
2066	The CHARGE Study: Childhood Autism Risks From Genetics and the Environment	NIMH Data Archive	96
2013	Magnetoencephalographic studies of lexical processing and abstraction in autism	NIMH Data Archive	77
2072	Intrinsic Brain Architecture of Young Children with Autism While Awake and Asleep	NIMH Data Archive	73
1946	Autism Risk, Prenatal Environmental Exposures, and Pathophysiologic Markers	NIMH Data Archive	69
2557	Environmental Influence on Infant Microbiome Development and ASD Symptoms	NIMH Data Archive	68
2288	The Autism Biomarkers Consortium for Clinical Trials	NIMH Data Archive	66
2030	Electrophysiological Response to Executive Control Training in Autism	NIMH Data Archive	65
1955	Characterizing mechanistic heterogeneity across ADHD and Autism	NIMH Data Archive	63
2003	Autism: Social and Communication Predictors in Siblings (Landa) AND Effects of Active Motor and Social Training on Developmental Trajectories in Infants at High-risk for Autism Spectrum Disorders (Libertus)	NIMH Data Archive	62
2025	Minimally Verbal ASD: From Basic Mechanisms to Innovative Interventions	NIMH Data Archive	61
2093	Sporadic Mutations and Autism Spectrum Disorders	NIMH Data Archive	60
2070	Eyeblink conditioning in school-aged children with ASD	NIMH Data Archive	54
2075	Mapping Thalamocortical Networks Across Development in ASD	NIMH Data Archive	53
1985	Evaluating the Time-Dependent Unfolding of Social Interactions in Children with Autism	NIMH Data Archive	50
2129	Biological Determinants of Brain Variation in Autism	NIMH Data Archive	48
2292	Molecular Mechanisms of Atypical Habituation in Autism Spectrum Disorders	NIMH Data Archive	47
2052	Peers, Play and Performance to Improve Social Interaction in Autism	NIMH Data Archive	45
2080	Smart Early Screening for Autism and Communication Disorders in Primary Care	NIMH Data Archive	44
2067	Targeting GABA-A for the Treatment of Social Disability in Young Adults with Autism Spectrum Disorders: A Phase II Proof of Mechanism Trial	NIMH Data Archive	44
2049	Efficacy of Relationship Development Intervention and Parent-Implemented Applied Behavior	NIMH Data Archive	40
2179	Neural markers of shared gaze during simulated social interactions in ASD \-Modal Automated Assessment of Behavior during Social Interactions in Children with ASD	NIMH Data Archive	39
2183	Identifying Biomarkers for Early Detection of Prosody Disorders in ASD using Electroglottography	NIMH Data Archive	38
2026	Biomarkers of Developmental Trajectories and Treatment in ASD	NIMH Data Archive	38
2293	Components of Emotional Processing in Toddlers with ASD	NIMH Data Archive	38
2014	The Neural Substrates of Higher-Level Learning in Autism	NIMH Data Archive	33
2028	Mechanisms of Risk and Resilience in ASD: Ontogeny, Phylogeny and Gene Disruption	NIMH Data Archive	33
2036	Intervention effects of intensity and delivery style for toddlers with ASD	NIMH Data Archive	30
2112	Services to enhance social functioning in adults with autism spectrum disorder	NIMH Data Archive	29
2322	Electrophysiologic Studies of Language Impairment in ASD (Years 6-10)	NIMH Data Archive	27
2060	Dysfunction of Sensory Inhibition in Autism	NIMH Data Archive	23
2011	Toward Outcome Measurement of Anxiety in Youth with Autism Spectrum Disorders	NIMH Data Archive	23
2108	Neural Phenotypes of Females with Autism Spectrum Disorder	NIMH Data Archive	22
2095	The neurophysiology of sensory processing and multisensory integration in ASD	NIMH Data Archive	21
2012	Optimization of Fidelity Procedures for Pivotal Response Training in Autism	NIMH Data Archive	19
2386	Efficacy of the Direct Instruction Language for Learning Program to Promote Expressive and Receptive Language in Children with Autism Spectrum Disorder	NIMH Data Archive	17
2077	Gaze Modification Strategies for Toddlers with ASD	NIMH Data Archive	15
2266	Inhibitory dysfunction in autism	NIMH Data Archive	15
2845	Attentional, temperamental, and physiological process underlying anxiety in preschoolers with ASD	NIMH Data Archive	14
2062	Verbal/non-verbal asynchrony in adolescents with high-functioning Autism	NIMH Data Archive	14
2253	Neurophenotypic Trajectories and Behavioral Outcomes in Autism Spectrum Disorder	NIMH Data Archive	13
2055	Silvio O. Conte Center for Oxytocin and Social Cognition	NIMH Data Archive	12
2281	Predictors of Cognitive Development in Autism Spectrum Disorder	NIMH Data Archive	11
2250	A feasibility study for prevention and safety training for children with autism	NIMH Data Archive	11
2006	Impairments of Theory of Mind disrupt patterns of brain activity	NIMH Data Archive	11
2272	Developing an Automated Emotion Training System	NIMH Data Archive	10
2358	Neural networks for attention to internal and external sensory cues in ASD	NIMH Data Archive	10
2442	Emergence and Stability of Autism in Fragile X Syndrome	NIMH Data Archive	9
1888	Emergence and Stability of Autism in Fragile X Syndrome	NIMH Data Archive	9
2197	The role of vasopressin in the social deficits of autism	NIMH Data Archive	9
1900	Neurobehavioral Research on Infants at Risk for SLI and Autism	NIMH Data Archive	8
2282	Cognitive Enhancement Therapy for Adult Autism Spectrum Disorder	NIMH Data Archive	8
2009	Study of Oxytocin in Autism to Improve Reciprocal Social Behaviors (SOARS-B)	NIMH Data Archive	7
2354	Neurodevelopment of cognitive control in autism: adolescence to young adulthood	NIMH Data Archive	7
2017	Wireless EEG System for Training Attention and Eye Movement in ASD	NIMH Data Archive	6
2169	Human Clinical Trial of IGF-1 in Children with Idiopathic ASD	NIMH Data Archive	6
2291	The Autistic Brain Over 45: The Anatomic, Functional, and Cognitive Phenotype	NIMH Data Archive	6
2312	Multimodel Assessment of Social Process Systems across Neurodevelopmental Disorders	NIMH Data Archive	6
2335	The role of parent phenotype in parent-mediated language interventions for autism	NIMH Data Archive	6
2342	Cognitive and Neural Flexibility in Autism	NIMH Data Archive	6
2460	Emergence, Stability and Predictors of Anxiety in Fragile X Syndrome	NIMH Data Archive	6
2035	Autism Genetics, Phase II: Increasing Representation of Human Diversity	NIMH Data Archive	5
1965	Longitudinal Studies of Autism Spectrum Disorders: From 2 to 23	NIMH Data Archive	5
2005	Pivotal Response Treatment for Infants at Risk for ASD: A Pilot Intervention	NIMH Data Archive	5
2440	Development of Behavioral and Neural Biomarkers for Autism Spectrum Disorder Using a Genetically Defined Subtype	NIMH Data Archive	4
2834	Neuronal Correlates of Autistic Traits in ADHD and Autism	NIMH Data Archive	4
2251	Developmental Synaptopathies Associated with TSC, PTEN and SHANK3 Mutations	NIMH Data Archive	4
2198	Pivotal Response Treatment Package for Young Children with Autism	NIMH Data Archive	4
2192	Piloting Treatment with Insulin-Like Growth Factor-1 in Phelan-McDermid Syndrome	NIMH Data Archive	4
2027	A Longitudinal MRI Study of Infants at Risk for Autism (ACE 2)	NIMH Data Archive	3
2773	Teaching Academic Success Skills to Middle School Students with Autism Spectrum Disorders (ASD) with Executive Functioning Deficits	NIMH Data Archive	3
2076	1/3 to 3/3 Treatment of anxiety in autism spectrum disorder	NIMH Data Archive	2
3034	Developing an intervention to improve independent functioning and health and reduce victimization risk for adults with autism	NIMH Data Archive	2
2828	Sensory consequences of action in children with autism spectrum disorders	NIMH Data Archive	2
2929	Social-communicative deficits in Autism Spectrum Disorder as measured by mGluR5 positron emission tomography	NIMH Data Archive	2
2254	The neurobiological basis of heterogeneous social and motor deficits in ASD	NIMH Data Archive	2
2415	Sensory Integration Therapy in Autism: Mechanisms and Effectiveness	NIMH Data Archive	2
2285	Integrity and Dynamic Processing Efficiency of Networks in ASD	NIMH Data Archive	2
2555	A longitudinal study of brain development in children with autism	NIMH Data Archive	2
19	Longitudinal MRI Study of Infants at Risk for Autism	NIMH Data Archive	2
2821	Cellular, molecular, and functional imaging approaches to understanding early neurodevelopment in autism	NIMH Data Archive	2
2043	Autism Spectrum Disorder - Inflammatory Subtype: Molecular Characterization	NIMH Data Archive	1
2776	Co-occurring ADHD in young children with ASD: Precursors, detection, neural signatures, and early treatment	NIMH Data Archive	1
2702	The Autism MEAL Plan: A Parent Training Curriculum to Manage Eating Aversions and Limited Variety among Children with Autism	NIMH Data Archive	1
2683	Examining Stress and Arousal Across Pubertal Development in ASD	NIMH Data Archive	1
2559	Neural Mechanisms of CBT for Anxiety in Children with Autism Spectrum Disorder	NIMH Data Archive	1
2556	Behavioral Economic Measures of Sensitivity to Social Reward in Children with ASD	NIMH Data Archive	1
2441	Structural and Functional Characteristics of XYY - Relationship to ASD	NIMH Data Archive	1
3056	Testing the Bottom-Up vs Top-Down Imbalance Hypothesis of ASD	NIMH Data Archive	1
2351	Arousal Tendencies and Individual Differences in Children with Autism Spectrum Disorder	NIMH Data Archive	1
2262	Comparing Behavioral Assessments Using Telehealth for Children with Autism	NIMH Data Archive	1
3022	Electrophysiological Markers for Interventions in Phelan-McDermid Syndrome and Idiopathic Autism	NIMH Data Archive	1

Study Type:	Analysis
Cohorts:	Test - ADOS-2 (3382) Age: 0 to 744 months Sex: Both
Measures:	Primary Measures: (5) Secondary Measures: (2)
Data Analysis:

helpcenter.ndastudy.summary-tab

NDA Study - Summary Tab

An NDA Study describes an analysis, pipeline result, or curated data release - including the cohorts, measures, and methods - referencing the underlying source data in the NDA. Once the data is referenced and the study is shared, the underlying data will not change. It will be immutable allowing others to access those data without change into near perpetuity. Only the assessments (i.e. typically rows in a database) and outcome measures (i.e. columns in a database) included in the study are shared. By sharing data this way (e.g. specific outcome measures by subject/timepoint) an ongoing project's other unpublished data - typically other research aims - will remain embargoed according to a project's established data sharing schedule (see collection).

When a study is created, a Digital Object Identifier (DOI) is reserved by the NDA, but will not be active. Once the study is shared, the DOI will then be issued and if associated with a publication, the NDA DOI will be linked to the publication's DOI.

Frequently Asked Questions

How can I get access to an NDA Study if I am involved in creating/modifying the NDA Study?

The individual listed as an Investigator on the General tab of the NDA Collection and any individuals defined as administrators can be provided this privilege. When the study is shared, all of those that have approved access to the data are given read-only access.

Glossary

Abstract

The Abstract of the publication or other public disclosure of analysis results. The publication abstract is automatically imported when creating a new NDA Study from a Create Study link associated with a Publication listed in a Collection. The field is editable.
Documents

Provides links to additional documentation to help explain the NDA Study.
Cohort

Summarizes the characteristics of a group of research subjects. The subject count is noted in parentheses.
Data Analysis

Summarizes the Data Analysis methods used.
Data Usage

Identifies the NDA Study as a Primary Analysis or Secondary Analysis.
Digital Object Identifier (DOI)

A persistent and unique identifier that is issued for each NDA Study that may increase the visibility of a researcher's work. Authors are expected to reference the location of data in the publication using the DOI.
Download Button

Adds all data from the current Collection or NDA Study to the Filter Cart.
Investigators

The authors of the publication or other public disclosure of analysis results. The publication's authors are automatically imported when creating a new NDA Study from a Create Study link associated with a Publication listed in a Collection. The field is editable and uses a last name, first name format with multiple names separated by semicolons.
Primary Analysis

Primary Analysis is one of the Data Use types NDA recognizes for NDA Studies. It indicates that the NDA Study's creator was involved in the collection of the data (in whole or in part) used in the NDA Study. In other words, at least some and potentially all of the data used was originally collected by the creator of the NDA Study. A Primary Analysis Study.
NDA Study Owner

The NDA user, who does not necessarily have to be one of the Investigators listed in the NDA Study, primarily involved in creating the NDA Study who is serving as the point of contact. The NDA user who creates the NDA Study is automatically assigned as the Study Owner.
Private

The term 'Private' generally means not available to others; however, there are some slightly different meanings based on what is Private. The default state for an NDA Collection, NDA Study, Supporting Documentation, and data is Private and, therefore, accessible only to those users with appropriate Privileges so it will not be viewable and searchable publicly. A Collection may be Shared while the data and Supporting Documentation remain Private.
Results

Provides a link to the publication or other public disclosure of analysis results defined in the NDA Study.
Secondary Analysis

Secondary Analysis is one of the Data Use types NDA recognizes for NDA Studies. It indicates that the NDA Study's creator was not involved in the collection of the data (in whole or in part) used in the NDA Study, but was involved in the analysis of those data. In other words, none of the data used was originally collected by the creator of the NDA Study. A Secondary Analysis Study will provide an Attribution Report listing the Collections and the researchers responsible for collecting and depositing the original data.
Study Type

The NDA Study Type can be either Analysis (i.e. often associated with a computational pipeline), Clinical Trial, Finding (i.e. a result associated with a publication, or Release (i.e. a dataset release, often annually) to indicate the type of work defined in the NDA Study. Studies, once shared do not change.
Analysis Study Type

The Analysis Study Type is primarily used to share a pipeline; however, it could be used to share a statistical analysis or method.
Release Study Type

A static, curated data set.
Finding Study Type

The Finding Study Type associates data to a publication or some type of result.
Clinical Trial Study Type

A Clinical Trial Study is a finding specific to a clinical trial.
Study ID Number

The Study ID number is a unique three digit number routinely expressed as S### that is assigned by the NDA.
Study State

The Study State indicates whether the Study is viewable, searchable, and if the associated data can be accessed by users with appropriate data access Permissions. The default Study State is Private, which means that only the Collection Owner and users with Read Only Privileges. Only the Study Owner can Share the Study.
Study Title

The Study Title is generally the title of the publication or other public disclosure of analysis results. The publication title is automatically imported when creating a new NDA Study from a Create Study link associated with a Publication listed in a Collection. The field is editable.
Edit Button

The Edit Button allows a user to modify or add information once authenticated and if the user has appropriate permissions.
Return Button (Study)

The Return Button brings the user back to the Data from Papers page.
Sex

Sex is defined at birth and can only be Male or Female. In some places in the NDA, we incorrectly used the data_element name of Gender. Users are encouraged to review definitions and not make assumptions based upon a data element name.
Data Use Limitations

Data Use Limitations (DULs) describe the appropriate secondary use of a dataset and are based on the original informed consent of a research participant. NDA only accepts consent-based data use limitations defined by the NIH Office of Science Policy.
Permission Group

Access to shared record-level data in NDA is provisioned at the level of a Permission Group. NDA Permission Groups consist of one or multiple NDA Collections that contain data with the same subject consents.

Contact NDA Help Desk

IDFilter by ID	TypeFilter by Type	NameFilter by Name	SexFilter by Sex	Age FromFilter by Age From	Age ToFilter by Age To	CommentsFilter by Comments	SubjectsFilter by Subjects	Actions
1037	Test	ADOS-2	Both	0	744	All subjects available in the ace_fammedhist01, ace_subjmedhist01, and diagnosed by the Autism Diagnostic Observation Schedule, 2nd Edition at the time when data was obtained were included in the study, however some subjects were eliminated during the pre-processing stage.	3,382

helpcenter.ndastudy.cohorts-tab

NDA Study - Cohorts Tab

The Cohort Tab allows users to view the cohorts for the NDA Study that were defined by the Study Owner. Cohorts identify general cohort characteristics (such as sex, age in months, and phenotype by medical criteria, phenotype, and subtype). Once a cohort is defined by the collection owner, subject data are then added through the NDA filter cart, but only subjects that meet the cohort's criteria (e.g. age restrictions and sex). Note too that a subject/age can exist only in one cohort.

Frequently Asked Questions

What should I do if all data can not be included in an analysis?

Some subjects may not have consented for data sharing so it is not necessarily true that all data from all subjects is available through the NDA Study. If some data or subjects are missing, note this in the Comments section of the cohort definition. Additionally, the NDA provides subjects that are excluded from the analysis for whatever reason (e.g. different aim, dropped out of the study, etc.). The reason for exclusion of subjects should be made in the comments section.

Glossary

Age Range

Age is expressed in months from 0 (birth) to 1200 (100 years old).
Download Button

Adds all data from the current Collection or NDA Study to the Filter Cart.
Owner Email

The email address of the Study Owner, which may be used to contact the Investigators involved in the NDA Study and/or the associated publication.
Private

The term 'Private' generally means not available to others; however, there are some slightly different meanings based on what is Private. The default state for an NDA Collection, NDA Study, Supporting Documentation, and data is Private and, therefore, accessible only to those users with appropriate Privileges so it will not be viewable and searchable publicly. A Collection may be Shared while the data and Supporting Documentation remain Private.
Analysis Study Type

The Analysis Study Type is primarily used to share a pipeline; however, it could be used to share a statistical analysis or method.
Clinical Trial Study Type

A Clinical Trial Study is a finding specific to a clinical trial.
Finding Study Type

The Finding Study Type associates data to a publication or some type of result.
Release Study Type

A static, curated data set.
Edit Button

The Edit Button allows a user to modify or add information once authenticated and if the user has appropriate permissions.
Return Button (Study)

The Return Button brings the user back to the Data from Papers page.
Study Title

The Study Title is generally the title of the publication or other public disclosure of analysis results. The publication title is automatically imported when creating a new NDA Study from a Create Study link associated with a Publication listed in a Collection. The field is editable.
Sex

Sex is defined at birth and can only be Male or Female. In some places in the NDA, we incorrectly used the data_element name of Gender. Users are encouraged to review definitions and not make assumptions based upon a data element name.
Cohort Comments

Comments further characterize the cohort beyond the options provided in the interface to define the cohort.
Cohort Name

A user defined name for the cohort with a 200 character limit.
Cohort Subjects

The Cohort Subjects provides the number of unique subjects for whom data have been associated with the cohort.
Cohort Type

Cohort Type options include Baseline, Control, and Test.
Cohort

Summarizes the characteristics of a group of research subjects. The subject count is noted in parentheses.

Contact NDA Help Desk

MeasureFilter by Measure	Type of Outcome	Subjects
ACE Family Medical History - Version 01	Secondary	791
ACE Subject Medical History - Version 01	Secondary	817
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 1 - Version 01	Primary	1,139
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 2 - Version 01	Primary	791
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 3 - Version 01	Primary	1,212
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 4 - Version 01	Primary	459
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Toddler Module - Version 01	Primary	360

Select	Data ElementFilter by Data Element	Primary/Secondary
No records found.

helpcenter.ndastudy.measures-tab

NDA Study - Measures Tab

As defined by the Study Owner, the Measures Tab lists the Data Structures from the NDA Data Dictionary used in the Study and whether they are Primary or Secondary measures. The NDA supports individual data structures, which would be an entire assessment (e.g. Mullen Scales of Early Learning) or individual data elements, which are preferred. To view the actual data definition for the defined Data Structure, click on the Measure name and the definition will open in another browser tab. For data elements, clicking on the 'i' informational icon, a popup of the description, value range, and any notes will be provided. Those that are authenticated may view the actual data in tabular form, supporting the cohort of the study.

Frequently Asked Questions

What is the benefit of adding Data Elements instead of just the Data Structure?

Defining the Data Elements and whether they are used as a Primary or Secondary outcome helps to further characterize the data used in the analysis. Furthermore, when you select Edit Measure at the Data Element level you will see and can further define the subject/age records specific to that measure and cohort.

Glossary

Analysis Study Type

The Analysis Study Type is primarily used to share a pipeline; however, it could be used to share a statistical analysis or method.
Clinical Trial Study Type

A Clinical Trial Study is a finding specific to a clinical trial.
Download Button

Adds all data from the current Collection or NDA Study to the Filter Cart.
Finding Study Type

The Finding Study Type associates data to a publication or some type of result.
Measures

Summarizes the count of Primary and Secondary Measures (data structures) used in the NDA Study's analysis.
Release Study Type

A static, curated data set.
Measures Status

Defines whether the Data Structure or Data Element is considered Primary or Secondary in the analysis.
Study ID Number

The Study ID number is a unique three digit number routinely expressed as S### that is assigned by the NDA.
NDA Study Owner

The NDA user, who does not necessarily have to be one of the Investigators listed in the NDA Study, primarily involved in creating the NDA Study who is serving as the point of contact. The NDA user who creates the NDA Study is automatically assigned as the Study Owner.
Study State

The Study State indicates whether the Study is viewable, searchable, and if the associated data can be accessed by users with appropriate data access Permissions. The default Study State is Private, which means that only the Collection Owner and users with Read Only Privileges. Only the Study Owner can Share the Study.
Study Title

The Study Title is generally the title of the publication or other public disclosure of analysis results. The publication title is automatically imported when creating a new NDA Study from a Create Study link associated with a Publication listed in a Collection. The field is editable.
Study Type

The NDA Study Type can be either Analysis (i.e. often associated with a computational pipeline), Clinical Trial, Finding (i.e. a result associated with a publication, or Release (i.e. a dataset release, often annually) to indicate the type of work defined in the NDA Study. Studies, once shared do not change.
Measures Subjects

Defines the number of subjects who data was used in the analysis for the identified measure (Data Structure or Data Element).
Edit Button

The Edit Button allows a user to modify or add information once authenticated and if the user has appropriate permissions.
Return Button (Study)

The Return Button brings the user back to the Data from Papers page.
Data Dictionary

The NDA Data Dictionary provides an electronic definition for each measure, questionnaire, assessment, etc that can be accepted into the NDA.
Data Element

Intended to be re-used as much as possible to honor harmonization standards, a Data Element is an individual item (variable/field) within a Data Structure that represents a question/field on an assessment or a discrete data point.
Data Structure

A defined organization and group of Data Elements to represent an electronic definition of a measure, assessment, questionnaire, or collection of data points. Data structures that have been defined in the NDA Data Dictionary are available at https://nda.nih.gov/general-query.html?q=query=data-structure

Contact NDA Help Desk

Observational

Controlled

Arms/Comparison

Arms/Comparison
- ADHD subphenotypes with co-occurring irritability
- ASD subphenotypes
- Behavioral
  - Behavioral
  - Placebo
- Brain imaging
- Cohorts
  - Case
  - Control
  - Healthy Variation
  - Healthy Variation
  - Mixed
- DNA methylation
- Dietary Supplement
  - Dietary Supplement
  - Placebo Comparator
- Drug
  - Active Comparator
  - High Dose
  - Low Dose
  - Normal Dose
  - Placebo Comparator
- Exposure
- Genomics
  - Bulk RNA-Seq
  - ChIP seq
  - Control
  - Polygenic Risk Score
  - SNP–expression associations
  - Single-Nucleus RNASequencing
  - Study Cohort
  - Whole Genome Sequencing
  - genome-wide DNA methylation analysis
- N/A
- Procedure
  - Procedure
  - Sham
- Psychopathological profiles
- Subgroup associated differentially methylated genes and pathways
- mRNA expression microarray

Description

Description
- Observation
  - Global molecular perspective
  - Direct
  - Disguised
  - Human
  - Indirect
  - Mechanical
  - Non-Disguised
  - Non-Structured
  - Structured
- Observational Model
  - Case Only
  - Case/Control
  - Defined Population
  - Family Based
  - Natural History
- Primary Purpose
  - Diagnostic
  - Prevention
  - Screening
  - Supportive Care
  - Treatment
- Settings
  - Contrived
  - Natural
- Time Perspective
  - Cross-Sectional
  - Longitudinal
  - Prospective
  - Retrospective
  - Retrospective/Prospective

Intervention

Intervention
- Behavioral
  - Picture Exchange communication system (PECS)
  - Questionnaires
  - Social Recreational
  - Speech Therapy
  - Training Sessions
- Dietary Supplement
  - Choline supplement
  - Garcinia mangostana Linn (mangosteen) pericarp
  - Melatonin
- Drug
  - Acetyl-Choline Esterase Inhibitors
  - Atomoxetine
  - CM-AT
  - Donepezil hydrochloride
  - Galantamine
  - Klonopin
  - haloperidol decanoate
  - paliperidone palmitate
- EEG
- Genomics
  - Cell Counting
  - ChIP seq
  - Construct Polygenic scores
  - Gene expression microarray
  - Gene regulation/microarray
  - Genotyping/microarray
  - RNA-Seq
  - Single-Nucleus RNASequencing
  - Targeted Sequencing
  - Whole Exome Sequencing
  - Whole Genome Sequencing
  - genome-wide DNA methylation analysis
- Medical Claims
- N/A
- Procedure
  - Acupressure treatments and NAET treatments
  - Acupuncture
  - EEG
  - Eye tracking
  - Hippotherapy
  - Hyperbaric Oxygen Therapy (HBOT)
  - MRI
  - Physical Examination
  - Platelet binding
  - dMRI
  - fMRI
- Screen Time
- Writing
- structural MRI

helpcenter.ndastudy.types-tab

NDA Study - Types Tab

The Arms/Comparison, Description, and Intervention Type options defined by the NDA Study Owner for either an Observational Study or Controlled Study can be viewed on this tab and are highlighted in yellow. The NDA allows those that define a Study to define their own arms, descriptions or intervention types as needed, however, to support harmonization, these must first be approved by the NDA prior to sharing the study.

Frequently Asked Questions

How do I know the Study Type?

The appropriate Arms/Comparison, Description, and Intervention information is highlighted based on whether the Study Owner identified the Study Type as Observational or Controlled. The option trees are automatically expanded so the highlighted options are immediately viewable and there is no need to expand all items to check for highlighted options.

Glossary

Analysis Study Type

The Analysis Study Type is primarily used to share a pipeline; however, it could be used to share a statistical analysis or method.
Clinical Trial Study Type

A Clinical Trial Study is a finding specific to a clinical trial.
Owner Email

The email address of the Study Owner, which may be used to contact the Investigators involved in the NDA Study and/or the associated publication.
Private

The term 'Private' generally means not available to others; however, there are some slightly different meanings based on what is Private. The default state for an NDA Collection, NDA Study, Supporting Documentation, and data is Private and, therefore, accessible only to those users with appropriate Privileges so it will not be viewable and searchable publicly. A Collection may be Shared while the data and Supporting Documentation remain Private.
Shared

The term 'Shared' generally means available to others; however, there are some slightly different meanings based on what is Shared. A Shared NDA Study is viewable and searchable publicly regardless of the user's role or whether the user has an NDA account. A Shared NDA Study does not necessarily mean that data used in the NDA Study have been shared as this is independently determined. Data are shared according the schedule defined in a Collection's Data Expected Tab and/or in accordance with data sharing expectations in the NDA Data Sharing Terms and Conditions. Additionally, Supporting Documentation uploaded to a Collection may be shared independent of whether data are shared.
Finding Study Type

The Finding Study Type associates data to a publication or some type of result.
Study ID Number

The Study ID number is a unique three digit number routinely expressed as S### that is assigned by the NDA.
Release Study Type

A static, curated data set.
NDA Study Owner

The NDA user, who does not necessarily have to be one of the Investigators listed in the NDA Study, primarily involved in creating the NDA Study who is serving as the point of contact. The NDA user who creates the NDA Study is automatically assigned as the Study Owner.
Study State

The Study State indicates whether the Study is viewable, searchable, and if the associated data can be accessed by users with appropriate data access Permissions. The default Study State is Private, which means that only the Collection Owner and users with Read Only Privileges. Only the Study Owner can Share the Study.
Study Title

The Study Title is generally the title of the publication or other public disclosure of analysis results. The publication title is automatically imported when creating a new NDA Study from a Create Study link associated with a Publication listed in a Collection. The field is editable.
Study Type

The NDA Study Type can be either Analysis (i.e. often associated with a computational pipeline), Clinical Trial, Finding (i.e. a result associated with a publication, or Release (i.e. a dataset release, often annually) to indicate the type of work defined in the NDA Study. Studies, once shared do not change.
Edit Button

The Edit Button allows a user to modify or add information once authenticated and if the user has appropriate permissions.
Return Button (Study)

The Return Button brings the user back to the Data from Papers page.

Contact NDA Help Desk

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Genotyping/NGS

Data Transformation, QA/QC
- Autosome Heterozygosity
- Chromosomal Aberration Screening
- Cluster Plots of Probe Intensities
- Derivative Log Ratio Spread
- Family-Based QC
- Gender Misidentification
- LD pruning
- Multidimensional Outlier Detection
- Percentile-Based Winsorizing
- Population Stratification Correction
- QA Filtering
  - Call rates
  - HWE
  - Minor Allele Frequency (MAF)
- Quartile Summary Statistics
- Wave Detection and Correction
Genetic Model
- Additive model
- Allele test
- Dominant model
- Genotypic test
- Recessive model
Genotype Statistics by Marker and Sample
- Allele count
- Call rate
- FIsher's exact test for HWE p-value
- Genotype count
- Global sample test
- Hardy-Weinberg Equilibrium (HWE) p-value
- Minor allele frequency
- Signed HWE Correlation R
Linkage and Haplotype Analysis
- Haplotype Association Testing
- Haplotype Block analysis
- Haplotype frequency estimation
  - Case/Control Association
  - Composite Haplotype Method
  - Expectation Maximization
- LD plot
N/A
NGS Analysis
- ChIP seq
- Discovery of mosaic variants
- Discovery of mosaic variants
- Discovery of structural variants
- Gene expression microarray
- RNA-seq
  - Gene expression
- Rare Variant Burden and Association Testing
- Single-Nucleus RNASequencing
- Variant annotation
  - SnpEff Annotations
  - dbNSFP Annotations
- Variant filtering
  - Annotation tracks
  - De novo variants
  - Functional prediction
  - GERP Score
  - Gene tracks
  - Grantham Score
  - Inherited variants
  - PolyPhen-2 Prediction
  - Probe tracks
  - SIFT
  - phyloP
- Variant validation
  - Independent microarray experiments
  - Long-range PCR
  - Massive parallel amplicon sequencing
  - Multiplex ligation-dependent probe amplification
  - PCR
  - Sanger sequencing
  - Sequenom assay
  - Targeted aCGH
  - qPCR
- genome-wide DNA methylation analysis
Software
- ANNOVAR
- BWA
- BeadExpress
- BeadStudio
- CASAVA
- CNAM
- CNV Prediction
- CNVnator
- CoNIFER
- DNAStar
- FBAT
- FreeBayes
- GATK
- GCTA
- Golden Helix
- MosaicForecast
- MosaicHunter
- OmicSoft
- PLINK
- PennCNV
- Picard Tools
- QuantiSNP
- SAMtools
- SPLIT-READ
- Sequencher
- Seurat
- SnpEff
- SpectralGEM
- Strelka2
- XHMM
- dbNSFP
- iPattern
- mrsFAST
Test Correction
- Benjamini-Hochberg
- Bonferroni adjustment
- FDR
- Full scan permutation
- Single value permutation
Test Statistics
- Analysis of deviance
- Cohran-Armitage test
- Correlation/Trend test
- F-test
- Fisher's exact test
- Kolmogorov-Smirnov
- Linear regression
- Logistic regression
- Odds ratio
- Pearson's chi-square test
Type
- CNV
- Exome Sequencing
- GWAS
- Haplotype
- Linkage
- RNA-Seq
  - Splice isoform assembly and annotation
  - Strand-specific dUTP
- ROH
- SNP
- Single Cell DNA Sequencing
- Targeted Sequencing
- Whole Genome sequencing

Microarray/Protein Analysis

Algorithm
- ANOVA
- Bayesian Method
- Cluster Analysis
  - Hierarchical
  - Partition
- Mann-Whitney U test
- Pearson's correlation
- Permutation
- Two Group Comparison
Illumina Infinium HumanMethylation27K Beadchip
- Illumina Infinium HumanMethylation27K Beadchip
Illumina Infinium MethylationEPIC BeadChip
- Illumina Infinium HumanMethylation450 BeadChip
N/A
Normalization Method
- Global
- LOWESS
- Robust-Linear model
Pathway Analysis
- Genetic
- Identification of co-expressed gene pairs
- Identification of co-regulated gene pairs
- Metabolic
- Neural
- Protein Interaction
Significance
- FDR
  - <1%
  - <10%
  - <5%
- p-value
  - <0.001
  - <0.01
  - <0.05
Software
- ADM-2 Algorithm
- Acuity
- DAPPLE
- GeneMANIA
- GeneSpring
- GenomeStudio
- Gingko
- Ginkgo
- IPA
- MatLab
- SAM
- TM4 - MeV MultiExperiment Viewer
Type
- Antibody
- Comparative Genomic Hybridization
- Gene Expression
- Methylation
- RPPM

Neuro Signal Recordings

Criteria
- Anatomical
- Functional
DIPY
Experiment
- BOLD Contrast
  - Echo planar T2-weighted gradient echo sequence
  - T2-sensitive echo planar imaging pulse sequence
- High resolution anatomical volume
  - Coplanar high-resolution T2-weighted echo planar imaging volume
  - T1-weighted 3D-MPRAGE pulse sequence
    - T1-weighted 3D-MEMPRAGE pulse sequence
- Number of Scans
  - 4
  - 6
- Order
  - Non-random
  - Randon
- Stimuli
  - Still images
    - Image description
  - Taste
  - Video clips of movements
- Timing
  - Image
    - 750ms/750ms blank
  - Visual Stimulation
    - 9s/6s blank
- Type
  - Motor
    - Action Execution
    - Imitation
  - Taste
  - Visual
    - Movement Observation Experiment
- Visual Field
  - Left
  - Right
Method
- General linear model
- Mean Absolute Error
- Region of Interest
- Residual Error
- Statistical Parameter Mapping
Model
- Dynamic Causal Modelling
- Expected hemodynamic response
- Inverted Encoding
- Mean percentage signal change
- Single response time-course
- Within-subject response variability
N/A
Preprocessing and correction
- 3D motion correction
- Artifact Removal
- Extraction
  - Cortical Surface
    - Inner Cortical Surface
    - Outer Cortical Surface
  - Gray Matter Surface
- Gaussian filter
- Inflating
  - Gray matter
- Intensity
- Intensity
  - Correction
  - Normalization
- Removal
  - Skull
- Segmenting
  - Cerebrospinal Fluid
  - Gray matter
  - White matter
- Temporal high-pass filtering
  - Cutoff frequency
    - 10 cycles/scan
    - 6 cycles/scan
  - Orthogonal projection
  - Trilinear interpolation
Processing
- Alignment / Orientation
  - Image reorientation to match standard template images
  - Rigid-body linear registration algorithm
- Image Normalization
  - Field Based Correction
  - Fifth-order polynomial nonlinear warping
- Tractography
Scanner
- General Electric 1.5T
- General Electric 3.0T MR750
- General Electric 3.0T MRI with an Advanced Magnetic Resonance Imaging upgrade for echo planar imaging (EPI)
- Philips 3.0T Achieva
- Philips 3.0T Ingenia
- Siemens 1.5T
- Siemens 3.0T Prisma MRI
- Siemens 3T Allegra MRI
- Siemens 3T Skyra
- iScan microarray scanner (Illumina)
Significance, correction
- Bonferroni method
- FDR
  - 0.01
  - 0.05
- Monte Carlo Simulation
- Network Based Statistics
- Percentile
  - above 95th
  - below 5th
- Threshold-Free Cluster Enhancement (TFCE)
- p-value
  - 0.001
  - 0.01
  - 0.05
Software
- AFNI
- BET
- BXH/XCEDE Tools
- Brain Voyager
- CIVET 2.1
- Connectome Workbench
- DIPY
- FSL
- FreeSurfer
- Horos
- MIPAV
- MMPS
- MMPS
- OsiriX
- SCILPY
- SPM
- Tractoflow
- fMRIPrep
Statistical Test
- ANOVA
- Linear regression
- Mixed effects model
- Randomization test
- T-test
  - paired
  - unpaired
Transformation
- Linear
- Linear
- Non-Linear
- Reverse Linear
- Talairach coordinate system
Type
- ASL
- CT
- DOT
- DTI
- EEG
- Eye Tracking
- MRI
- Magnetoencephalography
- PET
- Spectroscopy
- dMRI
- eDTI
- fMRI
- rs-fMRI
- sMRI-T1
- sMRI-T1
- sMRI-T2
- task-fMRI
rs-fMRI
sMRI-T1
sMRI-T2

Statistical

Comorbidity rates
Initial Transformation
- Categorical
- Inverse
- Log
- Normalization
- Square root
Machine Learning
Method
- ANCOVA
- ANOVA
- Analysis of Covariance Structural Equation Modeling
- Bayesian Probabilistic Principal Components Analysis
- Binomial test
- Canonical correlation analysis
- Chi-square test
- Convolutional Neural Network
- Correlation
- Decision tree algorithm
- Factor analysis
- Fisher Exact Test
- Fisher's Least Significant Difference Test
- Graph Theory
- Hidden Markov model
- Item Response Theory
- Kaplan-Meier
- Kruskal-Wallis test
- Latent Discrepancy Score Model
- MSWD
- Mann-Whitney U
- Mediation Analysis
- Meta-analysis
- Mixed Effects model
  - Linear mixed effects regression model
  - Mixed Effect Logistic Regression Model
  - Mixed Effect Negative Binomial Regression Model
- Monte Carlo
- Network Analysis
- Ordinary Least Squares Estimation
- Pearson correlation
- Penalized Least Squares Estimation
- Polynomial regression model
- Positive Predictive Value
- Regression analysis
  - Logistic regression
  - Quantile regression
- Sensitivity/Specificity
- Spearman's rank correlation
- Student's t-test
- Survival Analysis
- Time series analysis
- Wald Test
- Weighted Least Squares Estimation
- Wilcoxon Rank Sum test
Prevalence rates
Propensity score matching
Qualitative Content Analysis
Significance
- FDR
  - <1%
  - <10%
  - <15%
  - <2%
  - <5%
- Network Based Statistics
- Permutation test
- Sensitivity
  - 80%
  - 90%
  - 95%
- Specificity
  - 100%
  - 90%
  - 95%
- p-value
  - <0.001
  - <0.01
  - <0.02
  - <0.05
Software
- Bioconductor
- Custom Python Script
- Custom R Markdown Script
- DIFAS v.5.0
- FSL
- Fisher's Least Significant Difference Test
- FreeSurfer QDEC
- GenomeStudio software
- JASP
- Jupyterlab
- MS' Excel
- MatLab
  - MatLab Main
  - SurfStat
- Mplus
  - Mplus v5.0
  - Mplus v6.0
- R-project
- SAS
- SPM12
- SPSS
- STATA
- Stan
- Weka
- fmriprep
- metilene
Structural Equation Model
Twin Modeling

helpcenter.ndastudy.data-analysis-tab

NDA Study - Data Analysis Tab

The Data Analysis Tab provides information on the type(s) of data analysis used in the NDA Study as defined by the Study Owner. The NDA allows those that define a Study to include their own data analysis methods as needed, however, to support harmonization, these must first be approved by the NDA prior to sharing the study. Additionally, files and links to other websites are also supported here as those documents generally, but not necessarily, relate to data analysis methods.

Frequently Asked Questions

How do I know which data analysis options were used in the NDA Study?

The appropriate Genotyping/NGS, Microarray/Protein Analysis, Neuro Signal Recordings, and Statistical options used by the researcher are highlighted in yellow. The option trees are automatically expanded so the highlighted options are immediately viewable so there is no need to expand all items to check for highlighted options.

Glossary

Download Button

Adds all data from the current Collection or NDA Study to the Filter Cart.
Owner Email

The email address of the Study Owner, which may be used to contact the Investigators involved in the NDA Study and/or the associated publication.
Private

The term 'Private' generally means not available to others; however, there are some slightly different meanings based on what is Private. The default state for an NDA Collection, NDA Study, Supporting Documentation, and data is Private and, therefore, accessible only to those users with appropriate Privileges so it will not be viewable and searchable publicly. A Collection may be Shared while the data and Supporting Documentation remain Private.
Shared

The term 'Shared' generally means available to others; however, there are some slightly different meanings based on what is Shared. A Shared NDA Study is viewable and searchable publicly regardless of the user's role or whether the user has an NDA account. A Shared NDA Study does not necessarily mean that data used in the NDA Study have been shared as this is independently determined. Data are shared according the schedule defined in a Collection's Data Expected Tab and/or in accordance with data sharing expectations in the NDA Data Sharing Terms and Conditions. Additionally, Supporting Documentation uploaded to a Collection may be shared independent of whether data are shared.
Study ID Number

The Study ID number is a unique three digit number routinely expressed as S### that is assigned by the NDA.
NDA Study Owner

The NDA user, who does not necessarily have to be one of the Investigators listed in the NDA Study, primarily involved in creating the NDA Study who is serving as the point of contact. The NDA user who creates the NDA Study is automatically assigned as the Study Owner.
Study State

The Study State indicates whether the Study is viewable, searchable, and if the associated data can be accessed by users with appropriate data access Permissions. The default Study State is Private, which means that only the Collection Owner and users with Read Only Privileges. Only the Study Owner can Share the Study.
Study Title

The Study Title is generally the title of the publication or other public disclosure of analysis results. The publication title is automatically imported when creating a new NDA Study from a Create Study link associated with a Publication listed in a Collection. The field is editable.
Analysis Study Type

The Analysis Study Type is primarily used to share a pipeline; however, it could be used to share a statistical analysis or method.
Clinical Trial Study Type

A Clinical Trial Study is a finding specific to a clinical trial.
Finding Study Type

The Finding Study Type associates data to a publication or some type of result.
Release Study Type

A static, curated data set.
Study Type

The NDA Study Type can be either Analysis (i.e. often associated with a computational pipeline), Clinical Trial, Finding (i.e. a result associated with a publication, or Release (i.e. a dataset release, often annually) to indicate the type of work defined in the NDA Study. Studies, once shared do not change.
Edit Button

The Edit Button allows a user to modify or add information once authenticated and if the user has appropriate permissions.
Return Button (Study)

The Return Button brings the user back to the Data from Papers page.

Contact NDA Help Desk

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