15059 results for "cancer studies using rna-seq"

in 14.86 milliseconds.

• Transcriptome analysis of iPSC-derived hepatocytes from Wilson's Disease patients and healthy controls

  To identify the differences in global gene expression patterns in WD-specific hepatocytes, we performed RNA-seq analysis. Six WD-specific hepatocytes and 6 healthy-donor (HD) hepatocytes were compared in total. The data suggested that our RNA-seq data were partially validated in the context of ATP7B deficiency and that these overlapped genes might be regulated by ATP7B deficiency among mammalian species in common.

  Study JGAS000382

• Transcriptomic subgroups in soft tissue tumors correlate with morphologic subtype, genomic features, and outcome

  We assessed gene expression (GGE) profiles and gene fusions as detected by transcriptome sequencing (RNA-seq) of 704 soft tissue tumors (STT) representing 56 different tumor types. Comparison with follow-up data identified transcriptional subclusters among sarcomas with complex genomes and among adipocytic tumors that correlated with metastasis-free survival and local recurrences, respectively. Thus, RNA-seq analysis of STT provides clinically important information.

  Study EGAS50000001472

• microRNA-seq of human serum from a longitudinal study of 66 women with no history of cancer

  This dataset includes microRNA sequencing data from 198 human serum samples, representing a subset of 66 women with no history of cancer who participated in the UKCTOCS study and with serum samples collected at three timepoints over a period of up to 5 years. Small RNA libraries prepared from the serum samples were sequenced with 50-bp single end reads on an Illumina HiSeq 2000 instrument. Data is provided as FASTQ files.

  Dataset EGAD00001004348

• Genetic Studies of Chronic Kidney Disease (CKD)

  The Genetic Studies of Chronic Kidney Disease (CKD) is an ongoing genetic research and biobanking protocol which aims to elucidate the genetic basis CKD. The study recruits patients seen at the Columbia University Medical Center (CUMC) Nephrology Division for the evaluation and care of CKD. All patients clinically diagnosed with CKD are eligible to participate; there are no inclusion or exclusion criteria related to age, sex/gender, and/or race/ethnicity. In addition to office visits, patients are recruited in contexts including perinatal care and nonprofit events for patients with various forms of CKD; recruitment tools include bilingual informational brochures, flyers, and consent forms. All individuals provide informed consent; for minors, signature of the parent/guardian is required. Consent includes: use of biosamples given for genetic studies, and the request to be re-contacted if medically actionable genetic findings are identified. In the case of the latter, such research-level findings are first validated in a clinically certified (CLIA) laboratory environment, using a second sample given by the individual at the time of re-contact; following CLIA validation, the individual is once again re-contacted, and, assuming he or she still desires return of these results, they can then be returned. Following the above consent process to participate in the study, individuals provide a single biosample (generally, a venous blood sample), from which DNA is extracted using standard protocols and used for genetic studies, such as exome sequencing. Basic clinical and demographic data, including sex/gender, age, and race/ethnicity are also collected. All data collected is stored in a secure computerized database, with patient samples anonymized using numerical identifiers; the relation of this identifier to patients' names is kept in a locked computer file in a centralized database. Electronic data complies with all HIPAA and other privacy and security regulations, and resides on a firewall server maintained by the CUMC IT department.

  Study phs001828

• BLUEPRINT RNA-seq data for rare cells in the haematopoietic lineages, from adult and cord blood samples.

  RNA-seq data for rare cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000284

• Genotype and exome data for an Australian Aboriginal population: a reference panel for health-based research

  Genetic analyses, including genome-wide association studies and whole exome sequencing (WES), provide powerful tools for the analysis of complex and rare genetic diseases. To date there are no reference data for Aboriginal Australians to underpin the translation of health-based genomic research. Here we provide a catalog of variants called after sequencing the exomes of 72 Aboriginal individuals to a depth of 20X coverage in 80% of the sequenced nucleotides. We determined 320,976 single nucleotide variants (SNVs) and 47,313 insertions/deletions using the Genome Analysis Toolkit. We had previously genotyped a subset of the Aboriginal individuals (70/72) using the Illumina Omni2.5 BeadChip platform and found 99% concordance at overlapping sites, which suggests high quality genotyping. Finally, we compared our SNVs to six publicly available variant databases, such as dbSNP and the Exome Sequencing Project, and 70,115 of our SNVs did not overlap any of the single nucleotide polymorphic sites in all the databases. Our data set provides a useful reference point for genomic studies on Aboriginal Australians.

  Study EGAS00001001585

• Genetic Predictors of Adverse Radiotherapy Effects (Gene-PARE)

  The goal of this study was to identify SNPs and CNPs that are associated with development of normal tissue toxicities resulting from radiotherapy for prostate cancer. The study population includes approximately 1,400 men treated with brachytherapy, external beam radiation therapy, or a combination of the two treatments, and assessed for adverse effects at baseline and following radiotherapy. Three toxicity endpoints were investigated using a two-stage GWAS approach: urinary morbidity, rectal bleeding and erectile dysfunction. The study sample was split into a discovery set (N=367) and a replication set (N=417), and an additional 647 samples, which were not part of this original cohort, were also included as an independent replication set. The replication set was developed via collaboration developed under the framework of the Radiogenomics Consortium (RGC). The long-term goal of this project, and other radiogenomics projects lead by the RGC, is two-fold: 1) Develop an assay capable of predicting which cancer patients are most likely to develop radiation injuries resulting from treatment with a standard RT protocol, and 2) Obtain information to assist with the elucidation of the molecular pathways responsible for radiation-induced normal tissue toxicities. These studies focus on multiple cancer types including prostate, breast, lung, and head and neck cancers.

  Study phs000772

• STAR outputs from RNA-seq

  STAR outputs from RNA-seq of 84 pancreatic neuroendocrine neoplasms, 10 normal islet samples and 4 cell line samples.

  Dataset EGAD00001006991

• WGS and RNA-Seq data from a GBM patient PT-BM8772

  WGS and RNA-Seq data from a GBM patient PT-BM8772

  Dataset EGAD00001008516

• WGS and RNA-Seq data from a GBM patient PT-WR7927

  WGS and RNA-Seq data from a GBM patient PT-WR7927

  Dataset EGAD00001008531

• WGS and RNA-Seq data from a GBM patient PT-GE7528

  WGS and RNA-Seq data from a GBM patient PT-GE7528

  Dataset EGAD00001008519

• WGS and RNA-Seq data from a GBM patient PT-RV2286

  WGS and RNA-Seq data from a GBM patient PT-RV2286

  Dataset EGAD00001008527

• WGS and RNA-Seq data from a GBM patient PT-GI2070

  WGS and RNA-Seq data from a GBM patient PT-GI2070

  Dataset EGAD00001008520

• WGS and RNA-Seq data from a GBM patient PT-JR9883

  WGS and RNA-Seq data from a GBM patient PT-JR9883

  Dataset EGAD00001008521

• WGS and RNA-Seq data from a GBM patient PT-ML9537

  WGS and RNA-Seq data from a GBM patient PT-ML9537

  Dataset EGAD00001008523

• Intellance-2: TruSight Tumor 170 panel based RNA-seq

  Intellance-2: TruSight Tumor 170 panel based RNA-seq

  Dataset EGAD00001007944

• RNA-Seq datasets in human islets cultured in high glucose conditions

  7 RNA-Seq datasets in human pancreatic islets from 7 donors, where islets were treated in high (11mM) glucose conditions

  Dataset EGAD00001005207

• RNA-Seq of pancreatic neuroendocrine tumors mutated in MEN1/DAXX/ ATRX

  RNA-Seq of of 11 primary pancreatic neuroendocrine tumors mutated in MEN1/DAXX/ ATRX used to identify molecular subtypes

  Dataset EGAD00001015695

• Smart-seq2 single-cell RNA-seq of human liver non-parenchymal cells

  Smart-seq2 single-cell RNA-seq of human liver non-parenchymal cells from lean and obese individuals

  Dataset EGAD00001010301

• WGS and RNA-Seq data from a GBM patient PT-HO0394

  WGS and RNA-Seq data from a GBM patient PT-HO0394

  Dataset EGAD00001004243

• WGS and RNA-Seq data from a GBM patient PT-CA2271

  WGS and RNA-Seq data from a GBM patient PT-CA2271

  Dataset EGAD00001004230

• WGS and RNA-Seq data from a GBM patient PT-TM5196

  WGS and RNA-Seq data from a GBM patient PT-TM5196

  Dataset EGAD00001004262

• WGS and RNA-Seq data from a GBM patient PT-GC1519

  WGS and RNA-Seq data from a GBM patient PT-GC1519

  Dataset EGAD00001004239

• WGS and RNA-Seq data from a GBM patient PT-VO7089

  WGS and RNA-Seq data from a GBM patient PT-VO7089

  Dataset EGAD00001004263

• WGS and RNA-Seq data from a GBM patient PT-MD9088

  WGS and RNA-Seq data from a GBM patient PT-MD9088

  Dataset EGAD00001004254