top of page


BioCodeKb - Bioinformatics Knowledgebase

Heterogeneity is a word that signifies diversity. The prefix hetero- means "other or different" while the prefix homo- means "the same." Heterogeneity is often used in contrast to homogeneity, which is when two or more people or things are alike.

Homogeneity and heterogeneity are concepts often used in the sciences and statistics relating to the uniformity in a substance or organism. A material or image that is homogeneous is uniform in composition or character (i.e. color, shape, size, weight, height, distribution, texture, language, income, disease, temperature, radioactivity, architectural design, etc.); one that is heterogeneous is distinctly nonuniform in one of these qualities.

Genetic heterogeneity occurs through the production of single or similar phenotypes through different genetic mechanisms. There are two types of genetic heterogeneity: allelic heterogeneity, which occurs when a similar phenotype is produced by different alleles within the same gene; and locus heterogeneity, which occurs when a similar phenotype is produced by mutations at different loci.

The production of the same or similar phenotypes (observed biochemical, physiological, and morphological characteristics of a person determined by his/her genotype) by different genetic mechanisms.

Marked genetic heterogeneity is correlated to multiple levels of causation in many common human diseases including cystic fibrosis, Alzheimer's disease, autism spectrum disorders, inherited predisposition to breast cancer and non-syndromic hearing loss. These levels of causation are complex and occur through:

(1) rare, individual mutations that when combined contribute to the development of common diseases

(2) the accumulation of many different rare, individual mutations within the same gene that contribute to the development of the same common disease within different individuals

(3) the accumulation of many different rare, individual mutations within the same gene that contribute to the development of different phenotypic variations of the same common disease within different individuals

(4) the development of the same common disease in different individuals through different mutations.

Increased understanding of the role of genetic heterogeneity and the mechanisms through which it produces common disease phenotypes will facilitate the development of effective prevention and treatment methods for these diseases.

Initial research on genetic heterogeneity was conducted using genetic linkage analyses, which map genetic loci of related individuals to identify genomic differences. Current research now relies largely on genome-wide association studies which examine the association of single-nucleotide polymorphisms (SNPs) to a particular disease in a population.

Heterogeneity can be conceptualized in different ways for different purposes, resulting in multiple definitions and operationalizations. Multiple conceptualizations, definitions, and operationalizations of heterogeneity allow for the investigation of different aspects of ecological patterns on different ecological processes. A key challenge in the quantification of spatial heterogeneity is its relation/response to scale (e.g., extent, grain size, and thematic resolution). Moreover, from an ecological perspective it is necessary to differentiate between functional and structural heterogeneity. Functional heterogeneity is defined with respect to particular ecological processes. In contrast, structural heterogeneity takes an “arbitrary,” or observer-oriented, perspective on the assessment of heterogeneity. Unlike functional heterogeneity measures, structural heterogeneity measures do not need to be “recalibrated” when dealing with each new species. Finally a distinction is required between heterogeneity arising from changes in continuous variables (such as canopy height) and that arising from categorical variables (such as land cover types). These two aspects of heterogeneity are sometimes referred to as either complexity or gradients (based on continuous variables) and variability, or patchiness (based on categorical variables), with both types of heterogeneity often co-occurring at different scales.


Need to learn more about Heterogeneity and much more?

To learn Bioinformatics, analysis, tools, biological databases, Computational Biology, Bioinformatics Programming in Python & R through interactive video courses and tutorials, Join BioCode.

bottom of page