Quantitative genetic tools

Create Alert Alert. Share This Paper. Background Citations. Methods Citations. Figures, Tables, and Topics from this paper. Citation Type. Has PDF. Publication Type. More Filters. Journal of the science of food and agriculture. Tolerance in Peach. Frontiers in Plant Science. QTL mapping for brown rot Monilinia fructigena resistance in an intraspecific peach Prunus persica L. Git stats commits. Failed to load latest commit information. View code. Population and Quantitative GENetic toolbox pqgen calculates population and quantitative genetic statistics from genomic data.

Preparing an input file pqgen by default expects an input file in an extended bed format: chrom start end name GT.

Must be enclosed in single quotes, spaces must be escaped e. Tab delimited by default. By default, statistics are output per chromosome. Comments are included on estimates of genetic correlation between resistance and phenotypic traits e.

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Sign In or Create an Account. Sign In. Advanced Search. Search Menu. Article Navigation. Close mobile search navigation Article Navigation. See Coronavirus Updates for information on returning to campus, and more. The Quantitative Genomics Training is a two-day intensive training of seminars and hands-on analytical sessions to provide an overview of concepts, methods, and tools for whole-genome and transcriptome analyses in human health studies.

Subscribe for updates on registration and scholarship dates, deadlines, and announcements. Genome-wide association studies have discovered tens of thousands of loci significantly associated with complex traits. However, the majority of these loci are located outside of protein-coding regions making it difficult to determine the causal gene or the mechanism through which the phenotype is affected.

With whole-genome and RNA sequencing becoming increasingly accessible and feasible to conduct large-scale analyses, we can use different quantitative genomics methods to address these challenges in human health studies. This two-day intensive workshop will provide a rigorous introduction to several different techniques to analyze whole-genome sequencing and transcriptome data.

Led by a team of experts in statistical genomics and bioinformatics, who have developed their own methods to analyze such data, the training will integrate seminar lectures with hands-on computer lab sessions to put concepts into practice.

The training will focus on reviewing existing approaches based on predicted expression association with traits, colocalization of causal variants, and Mendelian Randomization, including discussion on how they relate to each other, and their advantages and limitations. Emphasis will also be given to reviewing integrative sequence based association studies for whole-genome sequencing data, and functional annotation of variants in noncoding regions of the genome.

By the end of the workshop, participants will be familiar with the following topics:.