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

You might also read

Related Articles

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

Sort by
Same author

The neutrophil-to-lymphocyte ratio and incident chronic kidney disease in a community-based cohort: a prospective study.

Scientific reports·2026
Same author

A Rhizosphere-Derived β-glycosidase with Intrinsic Sequential Regioselectivity for Highly Efficient Production of Siamenoside I from Mogroside V.

Journal of agricultural and food chemistry·2026
Same author

Integrative genomic and transcriptomic analyses identify key regulators of skin pigmentation in Larimichthys crocea.

Comparative biochemistry and physiology. Part D, Genomics & proteomics·2026
Same author

Spatial distribution of the proteome in the human body and in cancers.

Nature·2026
Same author

Talaromyces marneffei infection of central nervous system in an immunocompetent child in a nonendemic area: a case report and literature review.

BMC pediatrics·2026
Same author

Characterization of the plasma metabolomic profile in infantile epileptic spasms syndrome.

Translational pediatrics·2026

Related Experiment Video

Updated: Nov 1, 2025

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

6.9K

AdaTiSS: a novel data-Adaptive robust method for identifying Tissue Specificity Scores.

Meng Wang1, Lihua Jiang1, Michael P Snyder1

  • 1Department of Genetics, Stanford University, Stanford, CA 94305, USA.

Bioinformatics (Oxford, England)
|June 19, 2021
PubMed
Summary

Accurately detecting tissue specificity (TS) in genes is crucial for understanding molecular functions. AdaTiSS offers a novel, robust, and data-adaptive method to identify tissue-specific gene expression, even with complex data heterogeneity.

More Related Videos

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
08:40

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Published on: April 8, 2016

13.1K
In Situ MHC-tetramer Staining and Quantitative Analysis to Determine the Location, Abundance, and Phenotype of Antigen-specific CD8 T Cells in Tissues
08:37

In Situ MHC-tetramer Staining and Quantitative Analysis to Determine the Location, Abundance, and Phenotype of Antigen-specific CD8 T Cells in Tissues

Published on: September 22, 2017

12.5K

Related Experiment Videos

Last Updated: Nov 1, 2025

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

6.9K
Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
08:40

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Published on: April 8, 2016

13.1K
In Situ MHC-tetramer Staining and Quantitative Analysis to Determine the Location, Abundance, and Phenotype of Antigen-specific CD8 T Cells in Tissues
08:37

In Situ MHC-tetramer Staining and Quantitative Analysis to Determine the Location, Abundance, and Phenotype of Antigen-specific CD8 T Cells in Tissues

Published on: September 22, 2017

12.5K

Area of Science:

  • Genomics and Bioinformatics
  • Molecular Biology
  • Computational Biology

Background:

  • Understanding tissue specificity (TS) of gene expression is vital for elucidating molecular functions across different tissues.
  • Public datasets like the Genotype-Tissue Expression (GTEx) project offer extensive gene expression data but present challenges due to multiple tissue comparisons and data heterogeneity.
  • Existing methods struggle to accurately identify tissue-specific genes, especially when dealing with outliers and non-standard expression patterns.

Purpose of the Study:

  • To develop a robust and data-adaptive method for accurately detecting tissue specificity (TS) in gene expression.
  • To address the challenges posed by data heterogeneity and unknown outlier distributions in large-scale gene expression datasets.
  • To provide a standardized approach for profiling TS for genes across various tissues.

Main Methods:

  • Developed a novel data-adaptive robust estimation approach (AdaReg) based on density-power-weight, suitable for unknown outlier distributions.
  • Utilized a Gaussian-population mixture model within a linear regression framework to identify tissue-specific gene expression.
  • Constructed the AdaTiSS algorithm by applying robust estimation procedures to account for gene expression heterogeneities and estimate population parameters.

Main Results:

  • The AdaReg approach effectively handles unknown outlier distributions and non-vanishing outlier proportions in gene expression data.
  • AdaTiSS successfully profiles tissue specificity for each gene and tissue, standardizing gene expression profiles.
  • The developed algorithm provides a robust and powerful new tool for defining and quantifying tissue-specific gene expression.

Conclusions:

  • Defining the expression population is key to accurately identifying tissue-specific genes.
  • AdaTiSS offers a significant advancement in TS detection by providing a robust, data-adaptive solution.
  • This method enhances the ability to build population-level information and quantify TS in complex biological datasets.