15037 results for "cancer studies using rna-seq"

in 18.67 milliseconds.

• UK10K_OBESITY_GS

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The GS samples are part of the Obesity group and will undergo exome sequencing.

  Study EGAS00001000242

• De novo assembly of 150 Danish genomes reveals rich structural complexity

  Most known genetic variation in human genomes has been called from comparison of short reads to the reference genome, an approach biased against finding complex variation. We sequenced 150 individuals from 50 parent-offspring trios with multiple insert-size libraries to very high coverage. We show that each genome could be independently de novo assembled into a small number of high-quality scaffolds (median N50 > 21 Mb), each of quality comparable to long read assemblies while being very cost-effective. We show that our variant call set from comparing de novo assemblies is far more complete in terms of complex variation than previous studies. Importantly, even the complex 4-5 Mb extended MHC region was assembled and resolved into haplotypes, revealing >700kb novel sequence in this important region of the genome, and major parts of the Y chromosome including some palindromes were assembled with high accuracy. Finally, we show that our variant call-set allows for the genotyping of many more complex variants when used as a reference-panel for imputation into SNP-chip data or into previously resequenced genomes.

  Study EGAS00001002108

• Massively parallel functional dissection of schizophrenia associated non-coding genetic variants

  Schizophrenia (SCZ) is a severe mental disorder affecting 1% of the world population. SCZ is characterized by an underlying genetic architecture that is highly polygenic. Genome wide association studies have identified thousands of genetic variants that are statistically linked to the disease. However, the translation of these associations into insights on the pathomechanisms has been challenging because the causal genetic variants, their molecular function, and their target genes remain largely unknown. To address these questions, we combined induced pluripotent stem cell technology with a massively parallel variant annotation pipeline (MVAP) to functionally characterize 35,000 SCZ associated non-coding genetic variants. This approach identified a set of 620 (1.7%) single nucleotide polymorphisms as functional on the molecular level in a highly cell type and condition specific fashion. Subsequent multi-modal integration of epigenomic data combined with CRISPR screening in human neurons enabled us to systematically translate SCZ variant associations into target genes, biological processes, and ultimately alterations of neuronal physiology. These results provide a new high-resolution map of functional variant-gene combinations and offer comprehensive biological insights into the developmental context and stimulus dependent molecular processes modulated by SCZ genetic variation beyond statistical association.

  Study EGAS00001007542

• Khoe-San genomes reveal unique variation and confirm deepest population divergence in Homo sapiens

  The southern African indigenous Khoe-San populations harbor the most divergent lineages of all living peoples. Exploring their genomes is key to understanding deep human history. We sequenced 25 full genomes from five Khoe-San populations, revealing many novel variants, that 25% of variants are unique to the Khoe-San, and that the Khoe-San group harbors the greatest level of diversity across the globe. In line with previous studies, we found several gene-regions with extreme values in genome-wide distributions, potentially caused by natural selection early in the modern human lineage and more recent in time. These gene-regions included immunity-, sperm-, brain-, diet- and muscle-related genes. When accounting for recent admixture, all Khoe-San groups display genetic diversity approaching the levels in other African groups and a reduction in effective population size starting around 100,000 years ago. Hence, all human groups show a reduction in effective population size commencing around the time of the Out-of-Africa migrations, which coincides with changes in the paleoclimate records, changes that potentially impacted all humans at the time.

  Study EGAS00001004459

• Genomewide Association Study of Inflammatory Bowel Disease

  WTCCC genome-wide case-control association study for Inflammatory Bowel Disease (IBD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000006

• WTCCC case-control study for Rheumatoid Arthritis

  WTCCC genome-wide case-control association study for Rheumatoid Arthritis (RA) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000011

• WTCCC case-control study for Type 1 Diabetes

  WTCCC genome-wide case-control association study for Type 1 Diabetes (T1D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000014

• WTCCC case-control study for Type 2 Diabetes

  WTCCC genome-wide case-control association study for Type 2 Diabetes (T2D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000016

• WTCCC case-control study for Coronary Artery Disease

  WTCCC genome-wide case-control association study for Bipolar disorder (CAD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000003

• Trynka_sceQTL_genotypes

  Blood samples were obtained from 119 healthy individuals of British ancestry. Genomic DNA was isolated from a suspension of PBMCs from each individual using a DNA isolation kit (Qiagen). Genotyping was then performed using the Infinium CoreExome-24 (v1.3) chip (Illumina).

  Dataset EGAD00010002291