Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

1.1K
Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
1.1K
Key Elements for Plant Nutrition02:35

Key Elements for Plant Nutrition

24.3K
Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the...
24.3K
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

758
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
758
Key Techniques in Microbiology01:19

Key Techniques in Microbiology

2.4K
Aseptic techniques prevent contamination, ensure experimental accuracy, and protect researchers and microbial cultures. These techniques are essential in clinical, industrial, and research settings where sterility is required.Maintaining Sterility in Laboratory PracticesScientists maintain sterility by sterilizing tools with heat or chemicals, disinfecting work surfaces, and handling cultures in controlled environments. Working near an open flame or within a laminar flow hood reduces the risk...
2.4K
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

1.6K
Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...
1.6K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.6K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

WDR12 and HIVEP3 are contributors to cognitive preservation in Amish SuperAgers.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same author

Basic Science and Pathogenesis.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Basic Science and Pathogenesis.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Basic Science and Pathogenesis.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Linkage and association of preserved cognitive function in the midwestern Amish at a higher genetic risk of Alzheimer's disease.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies known and novel cross-population and ancestry-specific associations as novel risk loci for Alzheimer's disease.

Genome biology·2025

Related Experiment Video

Updated: Feb 7, 2026

Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

551

PLINK: Key Functions for Data Analysis.

Susan H Slifer1

  • 1University of Miami Miller School of Medicine, Miami, Florida.

Current Protocols in Human Genetics
|July 25, 2018
PubMed
Summary
This summary is machine-generated.

PLINK is a comprehensive toolkit for genetic data analysis, including quality control (QC) and association mapping of single nucleotide variants (SNVs). This overview details PLINK

Keywords:
GWASNGSQCSNVassociationsoftware

More Related Videos

Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

6.5K
Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.4K

Related Experiment Videos

Last Updated: Feb 7, 2026

Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

551
Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

6.5K
Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.4K

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Large-scale genetic data analysis, including GWAS, WES, and WGS, necessitates robust processing pipelines.
  • Several open-source toolkits exist to facilitate genetic data analysis, with PLINK being a prominent example.

Purpose of the Study:

  • To provide a practical overview of PLINK's capabilities for genetic data analysis.
  • To highlight PLINK's strengths in quality control, data management, and association mapping.
  • To discuss limitations and suggest alternative approaches for advanced analyses.

Main Methods:

  • Review of PLINK (v1.90b) features for genetic data processing and analysis.
  • Evaluation of PLINK's utility in quality control (QC), data management, and association mapping.
  • Comparison with alternative tools for specific analytical needs.

Main Results:

  • PLINK offers comprehensive QC and analytical modules, particularly for single nucleotide variants (SNVs).
  • The latest version incorporates advanced statistical modeling, including mixed-model association analysis.
  • Alternative tools may provide more optimal solutions for certain complex genetic analyses.

Conclusions:

  • PLINK is a versatile tool for genetic data management and analysis, especially for SNVs.
  • Understanding PLINK's features, shortcuts, and limitations is crucial for effective genetic research.
  • Complementary tools can enhance the analysis of complex genetic datasets.