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

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

17.1K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
17.1K
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

13.9K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
13.9K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.4K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
12.4K

You might also read

Related Articles

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

Sort by
Same author

Potentially burdensome end-of-life care for colorectal cancer decedents: A retrospective cohort study.

Palliative & supportive care·2026
Same author

Older adults with advanced chronic illness and emergency department care: the hermeneutic stories of Bill, Edie and Nicole.

BMC geriatrics·2026
Same author

Building Patient Capabilities for Using Virtual Care: A Document Analysis of Patient Support Resources and Guidance.

Journal of patient experience·2026
Same author

Applying Change Models and Methods During a Period of Vast Digital Transformation: A Systematic Review of Practice in Healthcare.

The International journal of health planning and management·2026
Same author

Specific service readiness for sick child health services and its relationship with quality of care and user experience in eight low-and middle-income countries.

BMC health services research·2026
Same author

Closing the Gap to Interventions for Tuberous Sclerosis Complex-Associated Neuropsychiatric Disorders (TAND): Protocol for a Longitudinal Study of TAND Severity, Predictors, and Caregiver Well-Being (TANDem-2).

JMIR research protocols·2026

Related Experiment Video

Updated: May 30, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.1K

MixDeR: A SNP mixture deconvolution workflow for forensic genetic genealogy.

Rebecca Mitchell1, Michelle Peck2, Erin Gorden2

  • 1National Bioforensic Analysis Center, National Biodefense Analysis and Countermeasures Center, Operated by Battelle National Biodefense Institute for the US. Department of Homeland Security Science and Technology Directorate, 8300 Research Plaza, Fort Detrick, MD 21702, USA.

Forensic Science International. Genetics
|January 25, 2025
PubMed
Summary

MixDeR is a new R package and Shiny app that deconvolutes mixed single nucleotide polymorphism (SNP) profiles. This enables the use of two-person mixtures for forensic genetic genealogy (FGG) applications.

Keywords:
Forensic genetic genealogy (FGG)Investigative genetic genealogy (IGG)KintelligenceMixturesSNPsSoftware

More Related Videos

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

38.9K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.2K

Related Experiment Videos

Last Updated: May 30, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.1K
Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

38.9K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.2K

Area of Science:

  • Forensic Science
  • Genetics
  • Bioinformatics

Background:

  • Next-generation sequencing (NGS) facilitates forensic DNA profiling using single nucleotide polymorphisms (SNPs).
  • Forensic genetic genealogy (FGG) applications are increasingly important but face challenges with mixed DNA samples.
  • Current FGG algorithms are primarily designed for single-source profiles, limiting analysis of complex forensic samples.

Purpose of the Study:

  • To develop a computational workflow for deconvoluting mixed SNP profiles for FGG.
  • To enable the analysis of two-person DNA mixtures in forensic casework.
  • To create a user-friendly tool for laboratories expanding FGG capabilities.

Main Methods:

  • Developed MixDeR, an R package and Shiny application for SNP profile deconvolution.
  • Integrated MixDeR with ForenSeq Kintelligence® genotyping data and EuroForMix (EFM) for deconvolution.
  • Filtered EFM outputs to generate single-source genotypes compatible with GEDmatch® PRO.
  • Included optional metrics for workflow testing and validation.

Main Results:

  • MixDeR successfully deconvolutes two-person SNP mixtures.
  • The workflow produces inferred single-source genotypes formatted for FGG database searches.
  • The R package and Shiny app provide a flexible, offline solution for laboratories.
  • Optional validation metrics aid in assessing workflow performance.

Conclusions:

  • MixDeR enhances the utility of FGG by enabling the analysis of mixed DNA samples.
  • The tool is accessible to laboratories with varying levels of bioinformatic expertise.
  • MixDeR supports the expansion of forensic genetic genealogy applications in casework.