Abstract
BackgroundAdmixed populations arise when two or more previously isolated populations interbreed. A powerful approach to addressing the genetic complexity in admixed populations is to infer ancestry. Ancestry inference including the proportion of an individual’s genome coming from each population and its ancestral origin along the chromosome of an admixed population requires the use of ancestry informative markers (AIMs) from reference ancestral populations. AIMs exhibit substantial differences in allele frequency between ancestral populations. Given the huge amount of human genetic variation data available from diverse populations, a computationally feasible and cost-effective approach is becoming increasingly important to extract or filter AIMs with the maximum information content for ancestry inference, admixture mapping, forensic applications, and detecting genomic regions that have been under recent selection.ResultsTo address this gap, we present MI-MAAP, an easy-to-use web-based bioinformatics tool designed to prioritize informative markers for multi-ancestry admixed populations by utilizing feature selection methods and multiple genomics resources including 1000 Genomes Project and Human Genome Diversity Project. Specifically, this tool implements a novel allele frequency-based feature selection algorithm, Lancaster Estimator of Independence (LEI), as well as other genotype-based methods such as Principal Component Analysis (PCA), Support Vector Machine (SVM), and Random Forest (RF). We demonstrated that MI-MAAP is a useful tool in prioritizing informative markers and accurately classifying ancestral populations. LEI is an efficient feature selection strategy to retrieve ancestry informative variants with different allele frequency/selection pressure among (or between) ancestries without requiring computationally expensive individual-level genotype data.ConclusionsMI-MAAP has a user-friendly interface which provides researchers an easy and fast way to filter and identify AIMs. MI-MAAP can be accessed at https://research.cchmc.org/mershalab/MI-MAAP/login/.
Highlights
Admixed populations arise when two or more previously isolated populations interbreed
Prioritizing ancestry informative markers (AIMs) using various feature selection methods is of paramount significance in studies of population structure and to map risk loci via admixture mapping [8]
We extend the two-way ancestry analysis into multi-way ancestry classification, and present a user-friendly web-based tool called Marker Informativeness for Multi-Ancestry Admixed Populations, Marker informativeness for multi-ancestry admixed populations (MI-MAAP), to facilitate selection of informative SNPs in multi-admixed population using 1000 Genomes Project, Human Genome Diversity Project as well as user-generated data
Summary
Workflow of MI-MAAP MI-MAAP was designed as a web-based tool for analyzing the marker informativeness in multi-ancestry admixed populations. Users have two types of input options: a) users can input a chromosome, SNP list or a single gene they are interested in from public databases (e.g., 1000 Genomes Project, International Haplotype Map (HapMap), Human Genome Diversity Project (HGDP) and Exome Aggregation Consortium (ExAC) [3,4,5, 10]; b) users can upload their own SNP data files that include the population-specific allele frequency or genotype information. Clicking an SNP ID out of the result table redirects to a new page on which the selected attribute information is displayed in a tabulated format These attribute data are obtained by either directly querying a local API, or providing the hyperlinks to external resources which are shown as the corresponding database logos. Because of the variation of the LEI score across different sets of populations, we recommend using an iterative approach to find the optimal set of SNPs that meet the acceptable decision criteria specific to research questions
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