9338 results for "cancer rna-seq"

in 34.55 milliseconds.

• Hereditary Cancer Diagnostics with I2HCP Data Access Comitee

  Dac EGAC00001001541

• Inherited Predisposition to Cancer Projects Data Access Committee

  Dac EGAC00001001565

• Immunogenomics of Colorectal Cancer Data Access Committee

  Dac EGAC00001001596

• UZ Ghent Prostate Cancer Team Data Access Committee

  Dac EGAC00001001608

• Cancer Alliance Data Access Committee

  Dac EGAC00001001641

• Primary tumor and metastatic breast cancer data access

  Dac EGAC00001001687

• Breast Cancer Single-Cell Data Access Committee

  Dac EGAC00001001974

• Data access committee breast cancer whole genome sequencing HRD

  Dac EGAC00001002286

• Leeds institute of Medical Research Bladder Cancer Research Group

  Dac EGAC00001002397

• MSKCC Colorectal Cancer Plasma WGS Data Access Comittee

  Dac EGAC00001002741

• Southern African Prostate Cancer Study (SAPCS) Data Access Committee

  Dac EGAC00001002768

• Netherlands Cancer Institute (NKI) - Beatriz Carvalho group

  Dac EGAC00001003134

• Cancer Team Data Access Committee

  Dac EGAC00001003407

• FunGeST - Functional Genomics from cancer research to personalized medicine

  Dac EGAC00001002924

• NOWAC blood-breast cancer Data Access Committee

  Dac EGAC01000000024

• PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

  Dac EGAC00001003503

• Aberrant EZHIP Expression Drives Tumorigenesis in Osteosarcoma

  Study EGAS00001007531

• Recurrent Somatic Mutations in CLL

  Study EGAS00001000070

• Leeds_Melanoma_Cohort

  Leeds Melanoma Cohort

  Study EGAS00001001158

• Genetic alterations in metastatic uveal melanoma

  Study EGAS00001003303

• Berlin Neuroblastoma Dataset

  Study EGAS00001004022

• Paired healthy & tumor organoid Biobank _B15PON

  Study EGAS00001005865

• OSCC WES + WGS Boot et al. 2020

  Study EGAS00001004376

• RNA sequencing of multiple myeloma identifies genes dysregulated by structural variants.

  Multiple myeloma is a disease of structural changes brought about by copy number abnormalities and translocations. Many of these changes result in super-enhancers being placed next to key oncogenes. Here, we have investigated which genes are commonly dysregulated by these changes.

  Study EGAS00001003411

• miRNA data for aSAH patients with or without subsequent vasospasm

  These files contain the normalized and raw count abundances miRNA for aSAH patients. These abundances were obtained using Next-Generation Sequencing after selection of the miRNA in the RNA biobank. In total, there are 28 VSP- and 28 VSP+ patients for two-time points. Normalized data were obtained by applying size factor and VSN normalizations as described in Pulcrano-Nicolas et al. Stroke 2018. Raw count data corresponding to the raw abundances of miRNA in aSAH patients.

  Dataset EGAD00001004185