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Integrate GWAS, eQTL and mQTL data to identify Alzheimer’s Disease-related genes. Homo sapiens

NIAID Data Ecosystem2026-03-11 收录

阿尔茨海默病基因研究

多组学数据整合

数据链接：

https://www.ncbi.nlm.nih.gov/bioproject/PRJNA556959 数据链接链接失效反馈

官方服务：

资源简介：

AD GWAS data and cis-eQTL mQTL data(brain)

应用场景：

创建时间：

2019-07-27

作物育种优化

多组学数据整合

We explored genomics, transcriptomics (mRNA and sRNA) and metabolomics of maize parent lines as predictors for agronomic performance of single-cross hybrids. Our results indicate that the merit of any

NIAID Data Ecosystem80

Integration analysis of three omics data using penalized regression methods: An application to bladder cancer (expression). Homo sapiens

膀胱癌机制

多组学数据整合

Omics data integration is becoming necessary to investigate the still unknown genomic mechanisms of complex diseases. During the integration process, many challenges arise such as data heterogeneity,

NIAID Data Ecosystem60

Additional file 2 of Protein–protein interaction network-based integration of GWAS and functional data for blood pressure regulation analysis

遗传调控

多组学数据整合

Additional file 2. The BP-associated RHCP-coding genes and their attributes.

NIAID Data Ecosystem40

Combined arrayCGH and SNP-loss of heterozygosity analysis in cervical cancer. Homo sapiens

宫颈癌基因组学

多组学数据整合

BACKGROUND: Cervical carcinoma develops as a result of multiple genetic alterations. Different studies investigated genomic alterations in cervical cancer mainly by means of metaphase comparative geno

NIAID Data Ecosystem70

Integrative Genome-wide Analysis of Glioblastoma.

胶质母细胞瘤基因组学

多组学数据整合

Glioblastoma multiforme shows multiple chromosomal aberrations, the impact of which on gene expression remains unclear. To investigate this relationship and to identify putative initiating genomic eve

NIAID Data Ecosystem40

Integrate GWAS, eQTL and mQTL data to identify Alzheimer’s Disease-related genes. Homo sapiens

资源简介：

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