12004 results for "cancer rna-seq"

in 15.97 milliseconds.

• Identification of molecule relationship between intravenous leiomyomatosis and uterus myoma

  Up to now, there are two hypothesis about the pathogenesis of the relationship of intravenous leiomyomatosis and uterine myoma. One theory suggests that the IVL comes from the smooth muscle cell in the vessel wall.The other theory indicates that the IVL derives from the uterine myometrium. However, limited to the technology, few studies have been deeply explore the underlying relation. In this study, we employ the RNA sequencing to explore the molecule relationship between IVL and uterus myoma. In order to identify the molecule relationship between IVl and uterine myoma we conducted transcriptome sequencing and bioinformaitc analysis

  Dataset EGAD00001003356

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015712

• Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia [scRNAseq]

  This dataset contains single-cell RNA, individually reference-aligned data from 203 individuals representing four Indonesian populations: the general urban population of Denpasar and the traditional community of Pedawa Village in Bali, as well as the traditional community of Yoboi Village (in Lake Sentani) and Sereh Village (individuals from highland Papua residing near Lake Sentani) in Papua. The dataset was produced as part of the Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia, a study aimed at characterizing how genetic background and environmental context shape immune cell states across diverse Indonesian communities.

  Dataset EGAD50000002385

• Population Architecture Using Genomics and Epidemiology (PAGE): Epidemiologic Architecture for Genes Linked to Environment (EAGLE) - BioVU Cancer Project

  As part of Population Architecture using Genomics and Epidemiology PAGE study (Phase I), the Epidemiologic Architecture using Genomics and Epidemiology (EAGLE I) project accessed both epidemiologic- and clinic-based collections. The epidemiologic-based collection of EAGLE I included the National Health and Nutritional Examination Surveys (NHANES), ascertained between 1991-1994 (NHANES III), 1999-2002, and 2007-2008. NHANES is a population-based cross-sectional survey now conducted every year in the United States to assess the health status of Americans at the time of ascertainment and to assess trends over the years of survey. Genetic NHANES consists of 19,613 DNA samples linked to thousands of variables including demographics, health and lifestyle variables, physical examination variables, laboratory variables, and exposures. NHANES is diverse with almost one-half of the samples (46.4%) coming from self-reported Mexican Americans and non-Hispanic blacks. In contrast to NHANES, BioVU is a clinic-based collection of >150,000 DNA samples from Vanderbilt University Medical Center linked to de-identified electronic medical records (EMRs). Approximately 12% of BioVU's overall DNA sample collection is from African American, Hispanic, and Asian patients. The overall goals of PAGE I and EAGLE I were broad and several-fold: Replicate genome-wide association study (GWAS)- identified variants in European Americans; Identify population-specific and trans-population genotype-phenotype associations; Identify genetic and environmental modifiers of these associations. NHANES is an excellent resource for the study of quantitative traits associated with common human diseases. However, given that the age range of NHANES spans childhood to late adulthood and not all diseases are surveyed, NHANES is less useful for the study of adult-onset diseases such as major cancers. Therefore, under American Recovery and Reinvestment Act (ARRA) funding, EAGLE as part of PAGE I defined eight major cancers sites for genetic analysis in BioVU, Vanderbilt's biorepository linked to de-identified EMRs. The eight major cancers defined for this study included melanoma, breast, ovarian, prostate, colorectal, lung, endometrial, and Non-Hodgkin's lymphoma (NHL). Cancer cases were defined using a combination of ICD-9 codes and tumor registry entries. Controls include BioVU participants without cancer and encompassing the age and gender distributions of cancer cases. Targeted genotyping of GWAS-identified variants for these diseases (124 SNPs) and ancestry informative markers (128 AIMs) was performed by the Center for Human Genetics Research Vanderbilt DNA Resources Core. After quality control, a total of 116 cancer-associated SNPs and 122 AIMs were available for downstream analyses.

  Study phs000559

• Methylated DNA immunoprecipitation sequencing of untreated and castration resistant prostate cancer

  Methylated DNA immunoprecipitation sequencing of 28 untreated prostate cancers, 11 castration resistant prostate cancers, and 12 benign prostatic hyperplasias.

  Dataset EGAD00001000610

• Colorectal cancer methylation profiling

  4 AC samples, each with adenoma, carcinoma and normal colon tissue (12 samples in total) were analysed on the Infinium MethylationEPIC BeadChip for copy number alteration analyses.

  Dataset EGAD00010001691

• WES bam files associated with HNSCC patients in the LIONESS study

  This dataset contains 85 WES bam/bai files of HNSCC cancer patients as part of with the LIONESS study

  Dataset EGAD50000001487

• Res1_PC9_exp2_MC_01_04_22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Study EGAS00001006170

• PREDICT

  PREDICT/Predicting individual response and resistance to VEGFR/mTOR pathway therapeutic intervention using biomarkers discovered through tumour functional genomics.

  Study EGAS00001000094

• Myeloma_Follow_up_Pilot

  Targeted capture of exonic and intronic regions of interest for the study of genomic alterations in multiple myeloma.

  Study EGAS00001000743