14982 results for "cancer studies using rna-seq"

in 15.26 milliseconds.

• Netherlands Cancer Institute (NKI) - Wilbert Zwart Group

  Dac EGAC00001002618

• Breast Cancer Single-Cell Data Access Committee

  Dac EGAC00001002691

• Computational Cancer Genomics and Tumor Evolution Group

  Dac EGAC00001002722

• Netherlands Cancer Institute (NKI) - Jos Jonkers Group

  Dac EGAC00001002749

• Netherlands Cancer Institute (NKI) - Wilbert Zwart Group

  Dac EGAC00001002782

• Netherlands Cancer Institute (NKI) - Jos Jonkers Group

  Dac EGAC00001002848

• Cancer Genomics of the Kidney - Targeted Sequencing

  Dac EGAC00001003091

• Cancer Genome Database Data Access Committee (CGDB_DAC)

  Dac EGAC01000000002

• Netherlands Cancer Institute (NKI) - Beatriz Carvalho group

  Dac EGAC00001003134

• DAC for Castleman. National Cancer Centre Singapore.

  Dac EGAC00001003328

• UCSF prostate cancer genomics data access committee

  Dac EGAC00001002685

• Genomic landscape of DS-ALL

  Study EGAS00001006600

• Genetic landscape of ENKTCL

  Study EGAS00001006906

• Breast cancer sequencing data

  Study EGAS00001007336

• Non-invasive bladder cancer cfDNA dataset DAC

  Dac EGAC50000000790

• GSCAN GWAS Meta-analysis of Tobacco and Alcohol use (GSCAN-GWAS)

  This study was a meta-analysis of genome-wide association study (GWAS) of substance use across 1.2 million total participants with European ancestry (some phenotypes are based on fewer participants). The phenotypes were chosen to represent different stages and kinds of substance use from initiation (age of smoking initiation) to regular use (cigarettes per day and drinks per week) to cessation (smoking cessation). For each of those phenotypes, collaborators shared their GWAS summary statistics, which were then meta-analyzed using a method that incorporates into the meta-analytic weighting the sample size, allele frequency and imputation quality score.

  Study phs001809