Demo Data from EDBT 2026 / reviewers in the wild / expert
John M. Hickey
dblp:150/3386
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
3 papers |
Bioinformatics and computational biology · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › genomics › genotyping
genotype imputation |
0.4 | 1 | 2020 | AlphaFamImpute: high-accuracy imputation in full-sib families from genotype-by-sequencing data · Bioinform. 2020 |
Bioinformatics and computational biology › statistical genetics › haplotype analysis
genotype phasing |
0.4 | 1 | 2020 | AlphaFamImpute: high-accuracy imputation in full-sib families from genotype-by-sequencing data · Bioinform. 2020 |
Bioinformatics and computational biology › statistical genetics › haplotype analysis
haplotype phasing |
0.4 | 1 | 2020 | AlphaFamImpute: high-accuracy imputation in full-sib families from genotype-by-sequencing data · Bioinform. 2020 |
Bioinformatics and computational biology › statistical genetics › genomic prediction
genomic selection |
0.3 | 1 | 2018 | AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs · Bioinform. 2018 |
Bioinformatics and computational biology › population genetics
genetics |
0.2 | 1 | 2014 | AlphaMPSim: flexible simulation of multi-parent crosses · Bioinform. 2014 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.4hidden markov model · 0.4multi-objective optimization · 0.3evolutionary algorithm · 0.3coalescent simulation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | AlphaFamImpute: high-accuracy imputation in full-sib families from genotype-by-sequencing dataabstractSUMMARY: AlphaFamImpute is an imputation package for calling, phasing and imputing genome-wide genotypes in outbred full-sib families from single nucleotide polymorphism (SNP) array and genotype-by-sequencing (GBS) data. GBS data are increasingly being used to genotype individuals, especially when SNP arrays do not exist for a population of interest. Low-coverage GBS produces data with a large number of missing or incorrect naïve genotype calls, which can be improved by identifying shared haplotype segments between full-sib individuals. Here, we present AlphaFamImpute, an algorithm specifically designed to exploit the genetic structure of full-sib families. It performs imputation using a two-step approach. In the first step, it phases and imputes parental genotypes based on the segregation states of their offspring (i.e. which pair of parental haplotypes the offspring inherited). In the second step, it phases and imputes the offspring genotypes by detecting which haplotype segments the offspring inherited from their parents. With a series of simulations, we find that AlphaFamImpute obtains high-accuracy genotypes, even when the parents are not genotyped and individuals are sequenced at <1x coverage. AVAILABILITY AND IMPLEMENTATION: AlphaFamImpute is available as a Python package from the AlphaGenes website http://www.AlphaGenes.roslin.ed.ac.uk/AlphaFamImpute. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Andrew Whalen, Gregor Gorjanc, John M. Hickey |
Bioinform. | 3 |
| 2018 | AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programsabstractSummary: AlphaMate is a flexible program that optimizes selection, maintenance of genetic diversity and mate allocation in breeding programs. It can be used in animal and cross- and self-pollinating plant populations. These populations can be subject to selective breeding or conservation management. The problem is formulated as a multi-objective optimization of a valid mating plan that is solved with an evolutionary algorithm. A valid mating plan is defined by a combination of mating constraints (the number of matings, the maximal number of parents, the minimal/equal/maximal number of contributions per parent, or allowance for selfing) that are gender specific or generic. The optimization can maximize genetic gain, minimize group coancestry, minimize inbreeding of individual matings, or maximize genetic gain for a given increase in group coancestry or inbreeding. Users provide a list of candidate individuals with associated gender and selection criteria information (if applicable) and coancestry matrix. Selection criteria and coancestry matrix can be based on pedigree or genome-wide markers. Additional individual or mating specific information can be included to enrich optimization objectives. An example of rapid recurrent genomic selection in wheat demonstrates how AlphaMate can double the efficiency of converting genetic diversity into genetic gain compared to truncation selection. Another example demonstrates the use of genome editing to expand the gain-diversity frontier. Availability and implementation: Executable versions of AlphaMate for Windows, Mac and Linux platforms are available at http://www.AlphaGenes.roslin.ed.ac.uk/AlphaMate. Gregor Gorjanc, John M. Hickey |
Bioinform. | 2 |
| 2014 | AlphaMPSim: flexible simulation of multi-parent crossesabstractUNLABELLED: Multi-parent crosses of recombinant inbred lines exist in many species for fine-scale analysis of genome structure and marker-trait association. These populations encompass a wide range of crossing designs with varying potential. AlphaMPSim is a flexible simulation program that is efficiently designed for comparison of alternative designs for traits with varying genetic architectures and biallelic markers with densities up to full sequence. A large pool of founder haplotypes can be supplied by the user, or generated via integration with external coalescent simulation programs such as MaCS. From these, diverse founders for multi-parent designs can be generated automatically, and users can compare designs generated from diverse pedigrees. Full tracking of identity by descent status of alleles within the pedigree is undertaken, and output files are compatible with commonly available analysis packages in R. AVAILABILITY AND IMPLEMENTATION: Executable versions of AlphaMPSim for Mac and Linux and a user manual are available at http://www.roslin.ed.ac.uk/john-hickey/software-packages/. John M. Hickey, Gregor Gorjanc, Sarah Hearne, Bevan Emma Huang |
Bioinform. | 1 |