eQTLrSNPWe describe a statistical method for prioritizing candidate causal noncoding single nucleotide polymorphisms (SNPs) in regions of the genome that are detected as trait-associated in a population-based genome-wide association study (GWAS). Our method's key step is to combine, within a ...
下列哪些不是TWAS设计的步骤 A、在eQTL数据中算出对应于该基因的所有的cis-SNPs的一个权重 B、把权重代入到GWAS的数据当中,得到预测基因表达值 C、将预测的基因表达值和复杂疾病或性状建立关联分析 D、利用GWAS中基因表达数据,得到预测的基因表达值
The Sherlock analysis [33] is a powerful Bayesian statistical method that incorporates GWAS summary data with eQTL data to systematically discover the cis- or trans-regulatory effects of SNPs on risk genes implicated in the complex trait of interest. The procedures of this method as follows: Sherl...
A.在eQTL数据中算出对应于该基因的所有的cis-SNPs的一个权重B.利用GWAS中基因表达数据,得到预测的基因表达值C.把权重代入到GWAS的数据当中,得到预测基因表达值D.将预测的基因表达值和复杂疾病或性状建立关联分析E.将GWAS的基因表达值与复杂疾病或性状建立关联分析相关...
Here we create a normal prostate tissue-specific eQTL data set and apply this data set to previously identified prostate cancer (PrCa)-risk SNPs in an effort to identify candidate target genes. The eQTL data set is constructed by the genotyping and RNA sequencing of 471 samples. We focus on...
Master regulatory sites – eQTL-SNPs with simultaneous impact on the expression of at least five genes.Katharina, SchrammCarola, MarziClaudia, SchurmannMaren, CarstensenEva, ReinmaaReiner, BiffarGertrud, EcksteinChristian, GiegerHansJörgen, Grabe...
State-specific effects of eQTL SNPs.Xinli HuHyun KimTowfique RajPatrick J. BrennanGosia TrynkaNikola TeslovichKamil SlowikowskiWeiMin ChenSuna OnengutClare BaecherAllan
TWAS设计主要分为下面哪三步 A、在eQTL数据中算出对应于该基因的所有的cis-SNPs的一个权重 B、把权重代入到GWAS的数据当中,得到预测基因表达值 C、将预测的基因表达值和复杂疾病或性状建立关联分析 D、利用GWAS中基因表达数据,得到预测的基因表达值
In support of these findings, we show that the top-ranked SNPs are associated with treatment responses to anti-PD-1 therapy in melanoma and non-small cell lung cancer. This study creates a unique and pioneering resource of prognostic germline variants with the potential to modulate immune ...