14988 results for "cancer studies using rna-seq"

in 23.40 milliseconds.

• SCLC tumor sequencing

  In this study we have sequenced the tumor of 28 Small Cell Lung Cancer patients.

  Study EGAS00001003985

• Single_cell_RNA_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008271

• PEACE (Posthumous Evaluation of Advanced Cancer Environment) whole exome sequencing data

  PEACE (Posthumous Evaluation of Advanced Cancer Environment) whole exome sequencing data

  Dataset EGAD00001015763

• MP2PRT: Evaluation of an Inflammation Polygenic Risk Score (iPRS) to Predict Cancer Related Cognitive Impairment and Fatigue in Patients Receiving Chemotherapy for Non-Metastatic Breast Cancer in URCC0701 and URCC10055

  This study is a secondary analysis of cancer related cognitive impairment (CRCI) and cancer related fatigue (CRF) among participants in URCC0701 and URCC10055 from the University of Rochester NCI Community Oncology Research Program (NCORP) Research Base. CRCI and CRF are common, troublesome, and dose-limiting toxicities reported by patients undergoing breast cancer chemotherapy that have an etiologic basis linked to low-grade systemic inflammation. Chronic, low-grade systemic inflammation is, in part, genetically determined with common single nucleotide polymorphisms (SNPs) capturing variation across individuals. This study aimed to 1) determine whether an inflammation polygenic risk score (iPRS) is associated with CRCI or CRF, 2) determine whether the relationship between the iPRS and CRCI or CRF is modified by exercise at the time of cancer treatment, 3) identify SNPs associated with serum cytokines measured at the time of cancer treatment, and 4) identify novel CRCI- and CRF-associated risk SNPs via genome-wide association analyses. We found that there was a significant inverse correlation between the iPRS and change in fatigue score from pre-chemotherapy to post-chemotherapy while there was no statistically significant association between the iPRS and cognitive impairment score. The inverse relationship between the iPRS and fatigue may be explained in part by the finding that the iPRS was also significantly associated with greater pre-chemotherapy fatigue, suggesting that women with a genetic predisposition to low-grade systemic inflammation (i.e., high iPRS) have more fatigue at the time of breast cancer diagnosis and, therefore, are less likely to worsen over the course of treatment. In contrast, women with a low iPRS had significantly less fatigue pre-chemotherapy and a significant worsening of fatigue from pre- to post-chemotherapy. The relationship between the iPRS and fatigue remained after adjustment for patient and cancer treatment covariates and was most pronounced in women who reported regularly exercising for at least 6 months prior to starting their cancer treatment. Exploratory genome-wide analysis identified a novel risk locus on chromosome chr6q27, tagged by rs9365961, associated with CRCI. This locus is upstream of TBXT, which encodes an embryonic nuclear transcription factor previously associated with susceptibility to neural tube defects. The genome-wide SNP data, patient-reported CRCI and CRF outcome measures, and covariate data used in this analysis are available through dbGaP.

  Study phs003688

• VIKING Health Study - Shetland 30X WGS

  30x whole genome sequencing of samples from the VIKING Health Study - Shetland. 500 DNA samples were sequenced using the Illumina HiSeq X system. FASTQ files are deposited

  Dataset EGAD00001005378

• HumanMethylation450_NL

  This dataset includes IDAT files from 2,790 blood samples. The samples were profiled using the Illumina Infinium HumanMethylation450 (450k) BeadChip.

  Dataset EGAD00010001938

• Methylation profiling of sarcoma and TFCP2-rearranged rhadomyosarcoma samples

  Methylation profiling of 345 sarcoma and TFCP2-rearranged rhadomyosarcoma samples, using the approach described "Genomic, transcriptomic, functional, and mechanistic characterization of rhabdomyosarcoma with FUS-TFCP2 or EWSR1-TFCP2 fusions"

  Dataset EGAD00010002451

• SECRETO Oral metagenome

  The dataset comprises data for n=329 participants who underwent saliva sampling. Shotgun metagenomic paired-end sequencing was conducted using the Illumina NovaSeq 6000 platform, and the resulting files are in FASTQ format.

  Dataset EGAD50000000283

• Guardant ctDNA

  This data table represents each patient molecular response based on ctDNA (using Guardant 360) percentage at baseline and cycle 3 day 1

  Dataset EGAD50000001339

• LBC1936 gvcfs

  1075 members of the LBC1936 were sequenced using the Illumina HiSeq X platform. This dataset contains the gvcfs.

  Dataset EGAD00001006414

• Somatic mutations called from whole-exome sequencing of PSCCE

  We performed whole-exome sequencing on 46 pairs of PSCCE and matched normal sample. Somatic mutations were called using MuTect2.

  Dataset EGAD00001006743

• New Caledonia low-coverage whole-genome sequencing data

  Mapped sequence reads in BAM format for 64 individuals reporting Kanak ancestry recruited in New Caledonia sequenced at four times target coverage using the Illumina HiSeq 4000 platform.

  Dataset EGAD00001002665

• 666PG genomic rearrangements

  Genomic rearrangement calls generated using Delly in VCF format from the CPCGene 666PG study

  Dataset EGAD00001006146

• multi regional whole exome sequencing of gastric adenocarcinoma

  Multiregional whole-exome sequencing was done using 48 tumor samples (range: 4-10 tumor samples/patient) from 9 patients with adenocarcinomas of the stomach and gastroesophageal junction (GC)

  Dataset EGAD00001006251

• Exome reads

  One sample of human genomic DNA. DNA extracted from whole blood. Reads obtained using an exome enrichment kit (Truseq, Illumina) and sequencing of 100bp paired-end reads on a HiSeq 2500 sequencing system (Illumina).

  Dataset EGAD00001003841

• Southern African Human Genome Programme dataset

  The SAHGP characterises the genomes of 24 individuals (8 Coloured and 16 black southeastern Bantu-speakers) using deep whole genome sequencing (WGS).

  Dataset EGAD00001003791