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

Reserve:
DOI:
Title:
Description:	Background Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50–70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. Methods To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. Findings We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07–1·15, p=1·84 × 10−9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86–0·93, p=6·46 × 10−9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10−21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. Interpretation These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder.
Publisher:
Publication Date:
Keywords:

Study DOI Status Info

DOI: 10.15154/1528938
DataCite Status: Findable
NDAR Status: Error
DOI Registered with DataCite
Public URL Resolves at DOI

Select Subjects

Selected
No records found.

Investigators: Study Investigators	Johnson, Emma; Demontis D, Thorgeirsson TE, Walters RK, Polimanti R, Hatoum AS, Sanchez-Roige S, Paul SE, Wendt FR, Clarke TK, Lai D, Reginsson GW, Zhou H, He J, Baranger DAA, Gudbjartsson DF, Wedow R, Adkins DE, Adkins AE, Alexander J, Bacanu SA, Bigdeli TB, Boden J, Brown SA, Bucholz KK, Bybjerg-Grauholm J, Corley RP, Degenhardt L, Dick DM, Domingue BW, Fox L, Goate AM, Gordon SD, Hack LM, Hancock DB, Hartz SM, Hickie IB, Hougaard DM, Krauter K, Lind PA, McClintick JN, McQueen MB, Meyers JL, Montgomery GW, Mors O, Mortensen PB, Nordentoft M, Pearson JF, Peterson RE, Reynolds MD, Rice JP, Runarsdottir V, Saccone NL, Sherva R, Silberg JL, Tarter RE, Tyrfingsson T, Wall TL, Webb BT, Werge T, Wetherill L, Wright MJ, Zellers S, Adams MJ, Bierut LJ, Boardman JD, Copeland WE, Farrer LA, Foroud TM, Gillespie NA, Grucza RA, Harris KM, Heath AC, Hesselbrock V, Hewitt JK, Hopfer CJ, Horwood J, Iacono WG, Johnson EO, Kendler KS, Kennedy MA, Kranzler HR, Madden PAF, Maes HH, Maher BS, Martin NG, McGue M, McIntosh AM, Medland SE, Nelson EC, Porjesz B, Riley BP, Stallings MC, Vanyukov MM, Vrieze S; Psychiatric Genomics Consortium Substance Use Disorders Workgroup; Davis LK, Bogdan R, Gelernter J, Edenberg H, Stefansson K, Borglum AD, Agrawal A
Abstract:	Background Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50–70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. Methods To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. Findings We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07–1·15, p=1·84 × 10−9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86–0·93, p=6·46 × 10−9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10−21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. Interpretation These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder.
Results:	PubMed version of article
Documents:
DOI:	10.15154/1528938
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
2573	Adolescent Brain Cognitive Development Study (ABCD)	Adolescent Brain Cognitive Development (ABCD) / Connectome Coordination Facility (CCF)	11,864

Study Type:	Analysis
Cohorts:	Baseline - ABCD Cohort at baseline (11864) Age: 0 to 1,260 months Sex: Both
Measures:	Primary Measures: (3) Secondary Measures: (0)
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
2601	Baseline	ABCD Cohort at baseline	Both	0	1,260		11,864

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
ABCD dMRI DTI Full Part 1 - Version 01	Primary	11,811
ABCD dMRI DTI Full Part 2 - Version 01	Primary	11,811
Genomics Sample - Version 03	Primary	10,217

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

File DescriptionFilter by File Description	Audience
No records found.

LinkFilter by Link
No records found.

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.

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