15037 results for "cancer studies using rna-seq"

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• Elucidation of the pathomechanism of inflammatory muscle diseases using multi-omics analysis

  This study aims to elucidate the pathomechanism of inflammatory muscle disease. We performed multi-omics analysis of muscle biopsy samples from the patients.

  Study JGAS000636

• WES_dataset2

  Twenty-six EATLs and 22 additional cases of MEITLs (among which 5 had only tumoral tissue available) were sequenced using the xgen research panels v1.0 and v2.0 from IDT DNA (Newark, New Jersey, USA).

  Dataset EGAD50000001621

• Dataset for desmoplastic small round cell tumor - WGS

  This dataset contains 25 WGS sequencing samples of patients with desmoplastic small round cell tumor. Sequencing was performed on Illumina HiSeq X and NovaSeq 6000 using Illumina TruSeq Nano DNA Kit. The sequencing was always paired.

  Dataset EGAD50000000911

• Pediatric study using genome sequencing

  This study used whole genome sequencing to assess genome variants from DNA from pediatric individuals seen in genetics clinic who were thought to have genetic conditions.

  Study EGAS00001005553

• ESGI - Whole Genome Sequencing of samples from the Croatian isolated populations (2017-11-22)

  Whole genome sequencing of sampels from isolated populations from Croatia. The samples are sequenced using the Illumina HiSeq X Ten system. This dataset contains all the data available for this study on 2017-11-22.

  Dataset EGAD00001003812

• Low pass whole genome sequencing of CACRC

  Genome-wide copy number profiling was performed using low-pass whole genome sequencing on archival non-dysplastic mucosa (n=9), low-grade dysplasia (LGD; n=30), high-grade dysplasia (HGD; n=13), mixed LGD/HGD (n=7) and CA-CRC (n=19).

  Dataset EGAD00001004270

• cfDNA mutation analysis using TAPAS in plasma and urine

  A 2.077Mb (57306 probes) personalised capture panel [Tailored Panel Sequencing (TAPAS)] was designed based upon the somatic SNVs identified by WES of RCC patient FF and FFPE tissue samples and applied to cfDNA in plasma and urine.

  Dataset EGAD00001005813

• Chromatin Profiling in Twins (2019-08-21)

  50 lymphoblastoid cell lines of adult female Twins which are part of the MuTHER study, subjected to Chromatin Immunoprecipitation using an antibody for H3K4me1. H3K4me1 peaks mark distal regulatory elements. . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005274

• Oxford Nanopore whole genome sequencing of two patients with congenital disease

  BAM files with sequencing reads derived from Oxford Nanopore MinION whole genome sequencing of two DNA samples from lymphoblastoid cell lines from two patients with congenital disease. Samples were prepared using 1D and 2D library preps.

  Dataset EGAD00001003511

• Whole exome sequencing of 76 individuals with familial atrial fibrillation

  Whole exome sequencing of 76 individuals with familial atrial fibrillation. BAM files have been aligned with BWA meme algorithm. Fastq files were filtered and trimmed using cutadapt. Samples have been sequnced on an Illumina 2500 machine.

  Dataset EGAD00001004333

• Human Evolution 3

  The mtDNA and Y chromosome of up to 15 Australian Aborigines, concentrating on individuals with indigenous lineages, will be sequenced using the standard whole-genome sequencing followed by filtering out of autosomal and X sequences, so that only mtDNA and the Y chromosome will be analysed and released.

  Dataset EGAD00001001373

• Variants from a subset of genes from WES of adult AML patient samples

  Dataset comprises one vcf file containing variants from a list of genes (DNA repair and metabolism associated genes) subset from WES of an adult AML cohort. The cohort contains 145 patient samples. WES was performed using Illumina platform.

  Dataset EGAD00001008700

• Mutation analysis of 10 genes in plasma DNA of RCC patients

  Mutation analysis of 10 frequently mutated genes in renal cell carcinoma (BAP1, KDM5C, MET, MTOR, PBRM1, PIK3CA, PTEN, SETD2, TP53, VHL) in plasma DNA of RCC patients using a custom QIASeq panel (MonRec Cohort)

  Dataset EGAD00001005806

• HV31 - De novo assembly of eight immune system regions

  De novo assembly of eight immune system regions for individual HV31, generated using a multi-platform pipeline. A full description of the generation of these assemblies can be found at https://doi.org/10.1101/2021.02.03.429586.

  Dataset EGAD00001007050

• WGS data subfolder for normal tissue from multifocal ileal NETs study

  This dataset includes linked-read whole-genome sequencing data from the normal ileal of the patient. The normal sample was sequenced using the 10x Genomics linked-read whole-genome sequencing (WGS) approach.

  Dataset EGAD00001008491

• GRAIL Metadata

  Metadata summarizes participants (n=198), samples (n=396), basic clinical information, and analysis. analysis1: raw sequencing reference alignment files (bam/bai) analysis2: error-corrected sequencing reference alignment files (bam/bai) analysis3: variant calling using error-corrected sequencing reference alignment (vcf)

  Dataset EGAD00001005302

• HV31 - PacBio long-read circular consensus (CCS) senquencing

  PacBio long-read circular consensus (CCS) sequencing data for individual HV31 generated on PacBio Sequel II instrument, using size-selected (10-15 kb) DNA from CD14+ monocytes, to a sequencing depth of ~12×. Sequencing was performed at the Wellcome Sanger Institute.

  Dataset EGAD00001006979

• Hangzhou Cancer study

  Dac EGAC00001000765

• IBD-dysplasia

  Study EGAS00001003767

• Singapore gastric cancer WGS

  Dac EGAC00001000888

• Colorectal cancer samples

  Dac EGAC00001002808

• Leeds Cancer Genomics

  Dac EGAC00001003010

• GCP study

  Study EGAS00001004959

• Brain Cancer Center Committee

  Dac EGAC00001003523

• The tissue origin of highly elevated cell-free DNA in patients with and without cancer

  Forty years ago, the first measurements of cell free DNA (cfDNA) from cancer patients revealed that its total concentration was often elevated compared to healthy controls. The basis for this increase, and in particular the source of the extra cfDNA in such patients, has never been determined. To address this issue, we assessed methylation patterns of cfDNA from 57 individuals, 34 of whom had unequivocally elevated cfDNA concentrations (i.e., >15 ng/mL of plasma). We found that the excess cfDNA in cancer patients did not come from either neoplastic cells or surrounding cells from the tumor's tissue of origin. Instead, 80% of the cfDNA was derived from neutrophils, B cells or T cells, with neutrophils accounting for ~2/3. B cells contributed more than T cells despite the great excess of T cells over B cells in the blood. To see if this result was generalizable to other clinical situations in which elevated cfDNA concentrations have been described, we evaluated nine patients before and one day following surgery. After surgical resection, cfDNA concentration increased by an average of 16.1-fold, as expected. The majority of this increase (55%) was contributed by leukocytes, though damaged hepatocytes contributed a substantial minority (31% of increase). These data suggest that the elevated concentrations of cfDNA in cancer patients, as with patients after surgery, arises largely from dying leukocytes—not from the neoplastic cells or the tissue of origin of the cancer.

  Study EGAS00001005400