PT  - JOURNAL ARTICLE
AU  - Project MinE ALS Sequencing Consortium
AU  - Wouter Van Rheenen
AU  - Sara L. Pulit
AU  - Annelot M. Dekker
AU  - Ahmad Al Khleifat
AU  - William J. Brands
AU  - Alfredo Iacoangeli
AU  - Kevin P. Kenna
AU  - Maarten Kooyman
AU  - Russell L. McLaughlin
AU  - Bas Middelkoop
AU  - Matthieu Moisse
AU  - Raymond D. Schellevis
AU  - Aleksey Shatunov
AU  - William Sproviero
AU  - Gijs H.P. Tazelaar
AU  - Rick A.A. Van der Spek
AU  - Perry T.C. Van Doormaal
AU  - Kristel R. Van Eijk
AU  - Joke J.F.A. van Vugt
AU  - A. Nazli Basak
AU  - Jonathan D. Glass
AU  - Orla Hardiman
AU  - Winston Hide
AU  - John E Landers
AU  - Jesus S. Mora
AU  - Karen E. Morrison
AU  - Wim Robberecht
AU  - Stephen Newhouse
AU  - Christopher E. Shaw
AU  - Pamela J. Shaw
AU  - Philip Van Damme
AU  - Michael A. Van Es
AU  - Ammar Al-Chalabi
AU  - Leonard H. Van den Berg
AU  - Jan H. Veldink
TI  - Project MinE: study design and pilot analyses of a large-scale whole genome sequencing study in amyotrophic lateral sclerosis
AID  - 10.1101/152553
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 152553
4099  - http://biorxiv.org/content/early/2017/06/20/152553.short
4100  - http://biorxiv.org/content/early/2017/06/20/152553.full
AB  - The most recent genome-wide association study in amyotrophic lateral sclerosis (ALS) demonstrates a disproportionate contribution from low-frequency variants to genetic susceptibility of disease. We have therefore begun Project MinE, an international collaboration that seeks to analyse whole-genome sequence data of at least 15,000 ALS patients and 7,500 controls. Here, we report on the design of Project MinE and pilot analyses of newly whole-genome sequenced 1,264 ALS patients and 611 controls drawn from the Netherlands. As has become characteristic of sequencing studies, we find an abundance of rare genetic variation (minor allele frequency < 0.1 %), the vast majority of which is absent in public data sets. Principal component analysis reveals local geographical clustering of these variants within The Netherlands. We use the whole-genome sequence data to explore the implications of poor geographical matching of cases and controls in a sequence-based disease study and to investigate how ancestry-matched, externally sequenced controls can induce false positive associations. Also, we have publicly released genome-wide minor allele counts in cases and controls, as well as results from genic burden tests.