11801 results for "cancer rna-seq"

in 12.16 milliseconds.

• Acute myeloid leukemia sequencing data

  This study contains tumor DNA and RNA sequencing data for 1 AML patient

  Study EGAS00001006354

• Ancestry and somatic profile predict acral melanoma origin and prognosis – RNA

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015756

• Type 2 Diabetes Starr County GWAS and Exome Sequencing

  The T2D Seq GWAS Starr County Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs001166 T2D Seq GWAS Starr County Cohort. phs000143 CIDR T2D Hanis phs001099 T2D GENES Starr County

  Study phs001166

• Type 2 Diabetes in African Americans, GWAS and Exome Sequencing

  The T2D Seq GWAS AA Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001167 T2D Seq GWAS AA Cohort. phs000140 CIDR T2D Bowdens phs001102 T2D GENES AA

  Study phs001167

• Evolving Cell States and Oncogenic Drivers during the Progression of IDH-Mutant Gliomas

  The study aims to understand the changes in cell states during the progression of IDH mutant gliomas. We generated scATAC-seq data from tumor samples of patients with IDH mutant gliomas, ranging from grade 2 to grade 4, including both IDH mutant oligodendroglioma and IDH mutant astrocytoma samples. Additionally, we have generated scRNA-seq data from patient-derived organoids that were treated with a DNMT1 inhibitor.

  Study phs003697

• Gene regulation of human stimulated and cultured CD4+ Treg cells

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs) stimulated using PMA and ionomycin or cultured without stimulus for 18 hours. It includes whole genome sequence data for ChM-seq (18 H3K4me3, 20 H3K27ac and 3 inputs), ATAC-seq (42 samples) and whole transcriptome (39 samples). All individuals were genotyped using coreExome Illumina SNP chip array (included in EGAS00001003516).

  Study EGAS00001003515

• DAC for "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling"

  This is the DAC for the study "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling" of PD Dr. Aurélie Ernst (a.ernst@dkfz.de) B420, DKFZ.

  Dac EGAC50000000452

• ATAC-seq samples from 9 cHL cell lines

  The dataset contains 21 ATAC-seq samples from 9 cHL cell lines. Files within the dataset are raw fastq files for each cell line.

  Dataset EGAD50000001273

• WGS seq data (56 tumor/control pairs) for study EGAS00001001394

  Part of WGS seq data of Maligant Lymphoma study (ICGC)

  Dataset EGAD00001001673

• IVF MeDIP-seq bam files

  Bam files consisting of aligned MeDIP-seq reads from cord blood cells and cord blood mononuclear cells of twins conceived through in vitro fertilisation

  Dataset EGAD00001003158