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

Response Surface Methodology01:16

Response Surface Methodology

128
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
128
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

546
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...
546
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

6.6K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
6.6K
Statgraphics01:10

Statgraphics

126
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
126
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

364
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
364
Quantitative Analysis01:12

Quantitative Analysis

291
Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...
291

You might also read

Related Articles

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

Sort by
Same author

Gene Expression Correlates with Disability and Pain Intensity in Patients with Chronic Low Back Pain and Modic Changes in a Sex-Specific Manner.

International journal of molecular sciences·2025
Same author

Identification and characterization of rare toll-like receptor 3 variants in patients with autoimmune Addison's disease.

Journal of translational autoimmunity·2020
Same author

Relatedness coefficients in pedigrees with inbred founders.

Journal of mathematical biology·2020
Same author

Coexistence of Congenital Adrenal Hyperplasia and Autoimmune Addison's Disease.

Frontiers in endocrinology·2019
Same author

Childhood lung function and the association with β2-adrenergic receptor haplotypes.

Acta paediatrica (Oslo, Norway : 1992)·2013
Same author

Pet keeping and tobacco exposure influence CD14 methylation in childhood.

Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology·2012

Related Experiment Video

Updated: Jun 28, 2025

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
09:51

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

15.4K

shinyseg: a web application for flexible cosegregation and sensitivity analysis.

Christian Carrizosa1, Dag E Undlien1, Magnus D Vigeland2

  • 1Department of Medical Genetics, Oslo University Hospital and University of Oslo, 0424 Oslo, Norway.

Bioinformatics (Oxford, England)
|April 10, 2024
PubMed
Summary

Shinyseg is a new web application that simplifies clinical cosegregation analysis for identifying genetic variants. It enhances evidence robustness assessment and aids in clinical interpretation.

More Related Videos

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.2K
Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

3.5K

Related Experiment Videos

Last Updated: Jun 28, 2025

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
09:51

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

15.4K
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.2K
Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

3.5K

Area of Science:

  • Genetics
  • Bioinformatics
  • Clinical Genetics

Background:

  • Cosegregation analysis is crucial for identifying pathogenic genetic variants but faces implementation challenges.
  • Existing software has limitations in scope, user-friendliness, and robustness assessment of evidence.
  • Assessing the robustness of cosegregation evidence is vital due to reliance on uncertain estimates.

Purpose of the Study:

  • To introduce shinyseg, a comprehensive web application for clinical cosegregation analysis.
  • To streamline penetrance specification using liability classes or epidemiological data.
  • To incorporate sensitivity analyses for evaluating cosegregation evidence robustness and support clinical interpretation.

Main Methods:

  • Development of a web application named shinyseg.
  • Implementation of streamlined penetrance specification using liability classes or epidemiological data (risks, hazard ratios, age of onset distribution).
  • Integration of sensitivity analyses to assess the robustness of cosegregation evidence.

Main Results:

  • Shinyseg provides a user-friendly platform for clinical cosegregation analysis.
  • The application facilitates robust penetrance specification and evidence assessment.
  • It offers enhanced support for clinical interpretation of genetic variant data.

Conclusions:

  • Shinyseg addresses the limitations of existing tools for cosegregation analysis.
  • The application improves the reliability and interpretability of genetic variant identification.
  • Shinyseg is a valuable tool for researchers and clinicians in genetic diagnostics.