DNA Phenotyping Tools

HIrisPlex-S Eye, Hair and Skin Colour DNA Phenotyping Webtool

Manfred Kayser at Erasmus Medical Center provides an interactive website to predict eye, hair and skin colour from DNA, based on SNaPshot data, using the IrisPlex (6 SNPs), HIrisPlex (24 SNPs) and HIrisPlex-S (41 SNPs) systems. https://hirisplex.erasmusmc.nl/ HIrisPlex-S Manual Furthermore, Susan Walsh at IUPUI in Indiana has developed lab tools and R scripts for processing NGS data for HIrisPlex-S analysis: https://walshlab.sitehost.iu.edu/pages/tools.html L. Chaitanya, K. Breslin, S. Zuñiga, L. Wirken, E. Pospiech, M. Kukla-Bartoszek, T. Sijen, P. de Knijff, F. Liu, W. Branicki, M. Kayser, S. Walsh. The HIrisPlex-S system for eye, hair and skin colour prediction from DNA: Introduction and forensic developmental validation. Forensic Science International Genetics 2018. 35:123-135. https://doi.org/10.1016/j.fsigen.2018.04.004 S. Walsh, L. Chaitanya, K. Breslin, C. Muralidharan, A. Bronikowska, E. Pospiech, J. Koller, L. Kovatsi, A. Wollstein, W. Branicki, F. Liu, M. Kayser, Global skin colour prediction from DNA. Human Genetics, 2017. 136:847-863. https://doi.org/10.1007/s00439-017-1808-5 S. Walsh, L. Chaitanya, L. Clarisse, L. Wirken, J. Draus-Barini, L. Kovatsi, H. Maeda, T. Ishikawa, T. Sijen, P. de Knijff, W. Branicki, F. Liu, M. Kayser, Developmental validation of the HIrisPlex system: DNA-based eye and hair colour prediction for forensic and anthropological usage. Forensic Science International: Genetics. 2014. 9:150-61. https://doi.org/10.1016/j.fsigen.2013.12.006

Snipper App Suite

Snipper is a web portal designed by the University of Santiago de Compostela hosting a suite of applications allowing you to classify an AIM profile as belonging to one of several populations (Europe, East Asia, Africa, America, Oceania), and other types of classification. Alternatively, it will let you input your own training set file to attempt to classify an AIM profile. The portal will also allow you to carry out some complementary tasks like plotting your populations and profile, design an optimal training set, and simulating profiles from your training set file. Snipper will accept an Excel .xlsx file as input.

1. Classification as Europe-East Asia-Africa-America-Oceania (34 SNPs, 46 # Indels, or both sets).
2. Classification as individual having black-intermediate-white skin.
3. Classification as individual having fair-dark or red-blond-brown-black hair.
4. Classification as individual having blue-greenhazel-brown eyes.
5. Classification with a custom Excel file of populations.
6. Prediction of age using DNA methylation.

http://mathgene.usc.es/snipper/ C. Phillips, A. Salas, J. J. Sánchez, M. Fondevila, A. Gómez-Tato, J. Álvarez-Dios, M. Calaza, M. Casares de Cal, D. Ballard, M. V. Lareu, Á. Carracedo and The SNPforID Consortium. Inferring ancestral origin using a single multiplex assay of ancestry-informative marker SNPs. Forensic Sci Int Genet. 2007, 1(3-4):273-280. https://doi.org/10.1016/j.fsigen.2007.06.008 C. Phillips, W. Parson, B. Lundsberg, C. Santos, A. Freire-Aradas, M. Torres, M. Eduardoff, C. Børsting, P. Johansen, M. Fondevila, N. Morling, P. Schneider; the EUROFORGEN-NoE Consortium, Á. Carracedo, M.V. Lareu. Building a forensic ancestry panel from the ground up: The EUROFORGEN Global AIM-SNP set. Forensic Sci Int Genet. 2014; 11: 13-25. https://doi.org/10.1016/j.fsigen.2014.02.012 M. Eduardoff, T.E. Gross, C. Santos, M. de la Puente, D. Ballard, C. Strobl, C. Børsting, N. Morling, L. Fusco, C. Hussing, B. Egyed, L. Souto, J. Uacyisrael, D. Syndercombe Court, Á. Carracedo, M.V. Lareu, P.M. Schneider; EUROFORGEN-NoE Consortium; W. Parson, C. Phillips. Inter-laboratory evaluation of the EUROFORGEN Global ancestry-informative SNP panel by massively parallel sequencing using the Ion PGM™. Forensic Sci Int Genet. 2016, 23:178-189. https://doi.org/10.1016/j.fsigen.2016.04.008 C. Phillips, C. Santos, M. Fondevila, Á. Carracedo, M.V. Lareu. Inference of Ancestry in Forensic Analysis I: Autosomal Ancestry-Informative Marker Sets. Methods Mol Biol. 2016, 1420: 233-253. https://doi.org/10.1007/978-1-4939-3597-0_18 C. Santos, C. Phillips, A. Gomez-Tato, J. Alvarez-Dios J, Á. Carracedo, M.V. Lareu. Inference of Ancestry in Forensic Analysis II: Analysis of Genetic Data. Methods Mol Biol. 2016, 1420: 255-285. https://doi.org/10.1007/978-1-4939-3597-0_19

Structure software

The program Structure from the Pritchard Lab at Stanford University is a free software package for using multi-locus genotype data to investigate population structure. Its uses include inferring the presence of distinct populations, assigning individuals to populations, studying hybrid zones, identifying migrants and admixed individuals, and estimating population allele frequencies in situations where many individuals are migrants or admixed. It can be applied to most of the commonly-used genetic markers, including SNPS, microsatellites, RFLPs and AFLPs. https://web.stanford.edu/group/pritchardlab/structure.html N.A. Rosenberg and P. Donnelly, J.K. Pritchard, M. Stephens. 2000. Association mapping in structured populations. Am J. Hum Genet. 67:170-181. https://doi.org/10.1086/302959 J.K. Pritchard, M. Stephens and P. J. Donnelly. Inference of population structure using multilocus genotype data. 2000. Genetics 155: 945-959. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1461096/

GenoGeographer - A tool for genogeographic inference

A likelihood ratio test (LRT) has been derived by the Dept. of Mathematical Sciences, Aalborg University, to judge whether there is at least one population in a reference database that is “sufficiently close” to a profile's “true” genogeographic population. The LRT is a measure of absolute concordance between a profile and a population, rather than a relative measure of the profile's likelihood in two populations (the LR). The LRT is similar to a Fisher's exact test, which means that the varying sample sizes of the reference populations in the database is explicitly included in the calculations, and makes fewer assumptions than for LR calculations. The methodology has been implemented in an free open source interactive platform, GenoGeographer, that enables the forensic geneticist to make explorative analyses, produce various graphical outputs together with evidential weight computations. http://genogeographer.org/ https://cran.r-project.org/web/packages/genogeographer/index.html T. Tvedebrink, P. Svante Eriksen, H. Smidt Mogensen, N. Morling 2017. GenoGeographer – A tool for genogeographic inference. Forensic Sci. Int. Genet. Suppl. Ser. 6:e463–e465 https://doi.org/10.1016/j.fsigss.2017.09.196 Mogensen HS, Tvedebrink T, Børsting C, Pereira V, Morling N. 2020 Ancestry prediction efficiency of the software GenoGeographer using a z-score method and the ancestry informative markers in the Precision ID Ancestry Panel. Forensic Sci Int Genet. 44:102154. https://doi.org/10.1016/j.fsigen.2019.102154