Genomics

Dataset Information

0

Ena-DATASET-DTU-01-02-2017-10:47:25:397-764 - samples


ABSTRACT: Alignment of Genome Denmark Phase II dataset to GRCh38. The dataset consists of 150 Danish individuals (50 trios) sequenced to 80X. The BAM-file contains data from multiple libraries created from one individual with libraries of 180, 500, 800, 2000, 5000, 10000 and 20000 bp. The libraries were created using standard Illumina protocols for paired end reads (180-800bp libraries) and mate pair libraries (2kb-20kb).

PROVIDER: EGAD00001003157 | EGA |

REPOSITORIES: EGA

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Publications

Sequencing and de novo assembly of 150 genomes from Denmark as a population reference.

Maretty Lasse L   Jensen Jacob Malte JM   Petersen Bent B   Sibbesen Jonas Andreas JA   Liu Siyang S   Villesen Palle P   Skov Laurits L   Belling Kirstine K   Theil Have Christian C   Izarzugaza Jose M G JMG   Grosjean Marie M   Bork-Jensen Jette J   Grove Jakob J   Als Thomas D TD   Huang Shujia S   Chang Yuqi Y   Xu Ruiqi R   Ye Weijian W   Rao Junhua J   Guo Xiaosen X   Sun Jihua J   Cao Hongzhi H   Ye Chen C   van Beusekom Johan J   Espeseth Thomas T   Flindt Esben E   Friborg Rune M RM   Halager Anders E AE   Le Hellard Stephanie S   Hultman Christina M CM   Lescai Francesco F   Li Shengting S   Lund Ole O   Løngren Peter P   Mailund Thomas T   Matey-Hernandez Maria Luisa ML   Mors Ole O   Pedersen Christian N S CNS   Sicheritz-Pontén Thomas T   Sullivan Patrick P   Syed Ali A   Westergaard David D   Yadav Rachita R   Li Ning N   Xu Xun X   Hansen Torben T   Krogh Anders A   Bolund Lars L   Sørensen Thorkild I A TIA   Pedersen Oluf O   Gupta Ramneek R   Rasmussen Simon S   Besenbacher Søren S   Børglum Anders D AD   Wang Jun J   Eiberg Hans H   Kristiansen Karsten K   Brunak Søren S   Schierup Mikkel Heide MH  

Nature 20170726 7665


Hundreds of thousands of human genomes are now being sequenced to characterize genetic variation and use this information to augment association mapping studies of complex disorders and other phenotypic traits. Genetic variation is identified mainly by mapping short reads to the reference genome or by performing local assembly. However, these approaches are biased against discovery of structural variants and variation in the more complex parts of the genome. Hence, large-scale de novo assembly i  ...[more]

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