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Mark J. Daly

Researcher at University of Helsinki

Publications -  831
Citations -  349468

Mark J. Daly is an academic researcher from University of Helsinki. The author has contributed to research in topics: Genome-wide association study & Population. The author has an hindex of 204, co-authored 763 publications receiving 304452 citations. Previous affiliations of Mark J. Daly include Cleveland Clinic Lerner Research Institute & Boston Children's Hospital.

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PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

TL;DR: This work introduces PLINK, an open-source C/C++ WGAS tool set, and describes the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation, which focuses on the estimation and use of identity- by-state and identity/descent information in the context of population-based whole-genome studies.
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The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

TL;DR: The GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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Haploview: analysis and visualization of LD and haplotype maps

TL;DR: Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.
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A global reference for human genetic variation.

Adam Auton, +517 more
- 01 Oct 2015 - 
TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.