15028 results for "cancer studies using rna-seq"

in 16.39 milliseconds.

• Mate Pair Sequencing data for Molecular Characterization of ETMRs

  This dataset contains Mate Pair Sequencing data from 15 samples from 13 patients. Mate pair DNA library preparation was carried out using the Illumina MP v.2 reagents and protocol. In brief, fragmentation of genomic DNA was performed using a Hydroshear device to an insert size of 4.5 kb followed by sequencing with Illumina HiSeq 2000 instruments resulting in 30 Fastq files (paired end).

  Dataset EGAD00001006207

• Evolution_of_the_cancer_epigenome_in_myeloproliferative_neoplasms_

  Evolution of the cancer epigenome in myeloproliferative neoplasms.

  Study EGAS00001001941

• Multi-omics RNA profiling of glioblastoma patient tissues

  Multi-omics profiling of paired primary and recurrent glioblastoma patient tissues

  Dataset EGAD00010001895

• TXT_CD138N_15

  TPM matrices of counts from RNA sequencing (RNAseq) from longitudinal CD138(–) BM fractions.

  Dataset EGAD00001011145

• SNF_RNAseq_CD138n_20f

  TPM matrices of counts from RNA sequencing (RNAseq) from baseline CD138(–) BM fractions.

  Dataset EGAD00001011142

• Count Me In (CMI): The Angiosarcoma (ASC) Project (CMI-ASCproject)

  Count Me In - The Angiosarcoma Project: A Patient-Partnered Research Initiative to Accelerate Research in a Rare Sarcoma The Angiosarcoma Project (ASCproject) is a research study that directly engages angiosarcoma patients online and empowers them to accelerate cancer research by sharing medical information and clinical samples. Angiosarcoma is an exceedingly rare soft tissue sarcoma with an incidence of ~300 newly diagnosed cases per year in the United States. This low incidence has impeded large-scale research efforts in this disease that are strongly needed to catalyze research and improve clinical outcomes. The Angiosarcoma Project, launched in March 2017, has demonstrated the feasibility of directly engaging geographically dispersed patients to democratize research and establish a large patient cohort to characterize the genomic and clinical landscape of a rare disease. Angiosarcoma patients living in the US or Canada can access the study and consent online through an online portal (ASCproject.org). Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. All received tumor samples are subjected to centralized histological re-review by an expert pathologist to confirm a diagnosis of angiosarcoma. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided updates on the study.

  Study phs001931

• DAC for Direct Detection of Early-stage Cancers Using Circulating Tumor DNA

  Dac EGAC00001000701

• EGAD00010000612

  Celiac disease North Indian samples using Immunochip

  Dataset EGAD00010000612

• EGAD00010000688

  glioma normal samples using 250K

  Dataset EGAD00010000688

• EGAD00010000682

  glioma samples tumor using 250K

  Dataset EGAD00010000682

• EGAD00010000684

  glioma normal samples using cytoscan

  Dataset EGAD00010000684

• EGAD00010000686

  glioma samples tumor using cytoscan

  Dataset EGAD00010000686

• EGAD00010000714

  aplastic anemia samples tumor using 250K

  Dataset EGAD00010000714

• EGAD00010000395

  Myeloma case sample genotype using Affymetrix SNP6.0

  Dataset EGAD00010000395

• EGAD00010000510

  Matched control samples using HumanOmni1-Quad

  Dataset EGAD00010000510

• EGAD00010000514

  Case samples using SNP 6.0 Array

  Dataset EGAD00010000514

• EGAD00010000542

  Cusihg's syndrome normal samples using 250K

  Dataset EGAD00010000542

• EGAD00010000544

  Cusihg's syndrome tumor samples using 250K

  Dataset EGAD00010000544

• saudi_qc_data

  Genotyped case and control sampes using HumanExome Beadchip

  Dataset EGAD00010000872

• MAGE

  MAGEcontrol samples using omni 2.5M

  Dataset EGAD00010001612

• Rapid, economical diagnostic classification of ATRT molecular subgroup using NanoString nCounter platform

  Study EGAS00001007470

• Targeted sequencing of 13131 older individuals, using 750-gene panel

  Study EGAS00001005316

• Exome_sequencing_of_healthy_twins_volunteers (replication_set)

  TwinsUK whole exome sequencing using NimbleGen SeqCap EZ

  Dataset EGAD00001001382

• Exome_sequencing_of_healthy_twins_volunteers (discovery_set)

  TwinsUK whole exome sequencing using NimbleGen 2.1M SeqCap

  Dataset EGAD00001001383

• UK_RCC_GWAS

  Renal cell carcinoma (RCC) cases comprised adult patients with histologically proven RCC were collected through two sources within the UK. First, 856 cases from SORCE, a MRC collection of surgically treated RCC cases ascertained through UK clinical oncology centres. Second, 189 RCC cases collected through the ICR and Royal Marsden NHS Hospitals Trust. Cases included 590 clear cell carcinomas (CCCs), 42 papillary carcinomas (PCs), 33 chromophobe carcinomas (CCs) and 19 mixed or other histological subtypes. DNA was extracted from EDTA-venous blood samples using the conventional methods and quantified using PicoGreen (Invitrogen). Cases were genotyped using the Human OmniExpress-12 BeadChip according to the manufacturer's recommendations (Illumina Inc, San Diego, CA, USA). After strict QC, 944 cases were retained. Data provided in plink format. Controls used were data from the Wellcome Trust Case Control Consortium 2 (WTCCC2) 1958 birth cohort and the UK Blood Service Control Group (available as EGAS00000000028). 

  Dataset EGAD00010002310