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

Identifying Statistically Significant Differences: The F-Test01:14

Identifying Statistically Significant Differences: The F-Test

The F-test is used to compare two sample variances to each other or compare the sample variance to the population variance. It is used to decide whether an indeterminate error can explain the difference in their values. The underlying assumptions that allow the use of the F-test include the data set or sets are normally distributed, and the data sets are independent of each other. The test statistic F is calculated by dividing one variance by another. In other words, the square of one standard...
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance, comparing...
Probability Laws01:49

Probability Laws

Overview
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

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...
Behrens–Fisher Test00:57

Behrens–Fisher Test

The Behrens-Fisher test is a statistical method designed to address the Behrens-Fisher problem, which arises when comparing the means of two normally distributed populations with unequal variances. Unlike the Student's t-test, which assumes equal variances, the Behrens-Fisher test allows for mean comparison without this restrictive assumption. This flexibility makes it particularly valuable in scenarios where two independent samples exhibit normality but lack variance homogeneity.
This test is...

You might also read

Related Articles

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

Sort by
Same author

Linking genomic and proteomic signatures to brain amyloid burden: insights from GR@ACE/DEGESCO.

Functional & integrative genomics·2025
Same author

António Amorim (in memoriam).

Forensic science international. Genetics·2025
Same author

Forensic Science International: Genetics: Past, present, and future of the journal and the field.

Forensic science international. Genetics·2025
Same author

The multi-omics signatures of telomere length in childhood.

BMC genomics·2025
Same author

The ReAct project: Bayesian networks for assessing the value of the results given activity level propositions.

Forensic science international. Genetics·2025
Same author

Influence of ABCB1 polymorphisms on aripiprazole and dehydroaripiprazole plasma concentrations.

Scientific reports·2025
Same journal

KLINK: A program for kinship testing with pairwise linked STR markers.

Forensic science international. Genetics·2026
Same journal

Data-driven methods allow prediction of utility of DNA rework.

Forensic science international. Genetics·2026
Same journal

Quantitative DNA/RNA fragmentation assays for estimating the time since deposition (TsD) of bloodstains.

Forensic science international. Genetics·2026
Same journal

Ensaya: An ensemble age model for prediction of chronological age in adolescents and young adults.

Forensic science international. Genetics·2026
Same journal

Comparison of key diagnostics for probabilistic interpretation of STR mixture data generated with length-based and MPS methodologies.

Forensic science international. Genetics·2026
Same journal

Likelihood Ratios Given Activity-Level Propositions for DNA Transfer Evidence: Theoretical Foundations of the HaloGen Framework (Part I).

Forensic science international. Genetics·2026
See all related articles

Related Experiment Video

Updated: Jun 27, 2026

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization
13:55

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Published on: February 3, 2013

ISFG: Recommendations on biostatistics in paternity testing.

David W Gjertson1, Charles H Brenner, Max P Baur

  • 1Department of Biostatistics, UCLA School of Public Health, Box 951772, Los Angeles, CA 90095-1772, USA.

Forensic Science International. Genetics
|December 17, 2008
PubMed
Summary
This summary is machine-generated.

The International Society for Forensic Genetics

More Related Videos

FISH for Pre-implantation Genetic Diagnosis
07:34

FISH for Pre-implantation Genetic Diagnosis

Published on: February 23, 2011

Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform
09:30

Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform

Published on: August 17, 2022

Related Experiment Videos

Last Updated: Jun 27, 2026

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization
13:55

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Published on: February 3, 2013

FISH for Pre-implantation Genetic Diagnosis
07:34

FISH for Pre-implantation Genetic Diagnosis

Published on: February 23, 2011

Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform
09:30

Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform

Published on: August 17, 2022

Area of Science:

  • Forensic Genetics
  • Biostatistics
  • Population Genetics

Background:

  • The International Society for Forensic Genetics' Paternity Testing Commission (PTC) previously recommended using the likelihood ratio principle for paternity testing.
  • This established the paternity index (PI) as a key metric for biostatistical evaluations in genetic paternity investigations.
  • There was a need for updated, supplementary recommendations to align with ISO 17025 standards.

Purpose of the Study:

  • To provide five supplementary biostatistical recommendations for genetic paternity testing.
  • To enhance the accuracy and standardization of paternity index (PI) calculations.
  • To address complex scenarios and reporting standards in forensic genetics.

Main Methods:

  • Development of five supplementary biostatistical recommendations by the Paternity Testing Commission (PTC).
  • Clarification of genetic hypotheses and calculation principles for valid PIs.
  • Inclusion of population genetics data (allele frequencies, Y-chromosome, mtDNA, substructuring) and special case considerations (deficiency, reconstruction, immigration).

Main Results:

  • Five key recommendations are proposed to refine biostatistical analyses in paternity testing.
  • Recommendations cover fundamental concepts, population genetics, special circumstances, evidence against paternity, and reporting standards.
  • The proposed guidelines aim to standardize and improve the reliability of paternity index (PI) calculations.

Conclusions:

  • The PTC strongly recommends the adoption of these supplementary biostatistical guidelines.
  • These recommendations are intended for all laboratories conducting paternity testing.
  • Implementation will ensure a standardized and robust basis for biostatistical analysis in accordance with ISO 17025 standards.