15167 results for "cancer studies using rna-seq"

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• Germline WES data of children with pathogenic mutations in cancer predisposing genes

  This data set includes bam files (aligned to hg38) from the germline of children who have pathogenic mutations in cancer predisposing genes

  Dataset EGAD00001009854

• Evolution of the cancer epigenome in myeloproliferative neoplasms. (2019-04-01)

  Evolution of the cancer epigenome in myeloproliferative neoplasms. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004879

• Ovarian cancer cfDNA dataset

  The dataset contains 23 ovarian cancer and 2 healthy control urine cfDNA samples. Shallow WGS was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001010848

• Whole genome sequencing of 98 tumour-normal pairs for the pancreatic neuroendocrine cancer project

  Whole genome sequencing of 98 tumour-normal pairs for the PAEN-AU pancreatic neuroendocrine cancer project.

  Dataset EGAD00001002684

• The complexity of tobacco smoke induced mutagenesis in head and neck cancer - structural variation vcf files (Mutographs)

  The complexity of tobacco smoke induced mutagenesis in head and neck cancer - structural variation vcf files (Mutographs)

  Dataset EGAD00001015389

• The complexity of tobacco smoke induced mutagenesis in head and neck cancer - copy number variants (Mutographs)

  The complexity of tobacco smoke induced mutagenesis in head and neck cancer - copy number variants (Mutographs)

  Dataset EGAD00001015390

• Xenograft BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001336

• Dynamics of genomic clones in breast cancer patient xenografts at single cell resolution

  Dynamics of genomic clones in breast cancer patient xenografts at single cell resolution

  Dataset EGAD00001001066

• There are 80 Brain cancer cases in this study and belong to GBM-CN project.

  There are 80 Brain cancer cases （160 samples）in this study and belong to GBM-CN project.

  Dataset EGAD00001003218

• The genetic structure of Norway

  The aim of the present study was to describe the genetic structure of the Norwegian population using genotypes from 6369 unrelated individuals with detailed information about places of residence. Using standard single marker- and haplotype-based approaches, we report evidence of two regions with distinctive patterns of genetic variation, one in the far northeast, and another in the south of Norway, as indicated by fixation indices, haplotype sharing, homozygosity and effective population size. We detect and quantify a component of Uralic Sami ancestry that is enriched in the North. On a finer scale, we find that rates of migration have been affected by topography like mountain ridges. In the broader Scandinavian context, we detect elevated relatedness between the mid- and northern border areas towards Sweden. The main finding of this study is that despite Norway’s long maritime history and as a former Danish territory, the region closest to mainland Europe in the south appears to have been the most isolated region in Norway, highlighting the open sea as a barrier to gene flow into Norway.

  Study EGAS00001004826

• Whole-genome sequencing of rare disease patients in a national healthcare system

  Most patients with rare diseases do not receive a molecular diagnosis and the aetiologicalvariants and mediating genes for more than half such disorders remain to be discovered. Weimplemented whole-genome sequencing (WGS) in a national healthcare system to streamlinediagnosis and to discover unknown aetiological variants, in the coding and non-coding regionsof the genome. In a pilot study for the 100,000 Genomes Project, we generated WGS data for13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to1,138 of the 7,065 patients with detailed phenotypic data. We identified 95 Mendelianassociations between genes and rare diseases, of which 11 have been discovered since 2015and at least 79 are confirmed aetiological. Using WGS of UK Biobank1, we showed that rarealleles can explain the presence of some individuals in the tails of a quantitative red blood cell(RBC) trait. Finally, we reported 4 novel non-coding variants which cause disease through thedisruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates asynergy by using WGS for diagnosis and aetiological discovery in routine healthcare.

  Study EGAS00001004364

• 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

• PacBio WGS based analysis of complex chromosomal rearrangements

  The dataset consists of a single sample whereby the genomic DNA was analysed using PacBio WGS at 30x coverage to assess the breakpoint sites of complex chromosomal rearrangements.

  Dataset EGAD00001015593

• 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

• Lactate metabolism in cancer stem cell fate regulation

  Tumors arise as a result of uncontrolled cell proliferation driven by mutations in the signaling pathways that regulate the balance between cell division and differentiation. Despite of that, in the tumor, cancer stem cells seem to retain their capability to differentiate, which can lead to differential chemotherapy response. We previously showed that intestinal stem cells and differentiated cells display specific metabolic features and that they interact through metabolites. Moreover, we found that altering mitochondrial metabolism is sufficient to lead and define stem cell differentiation. In cancer, cellular metabolism is highly derailed. However, how metabolic changes in the cancer cell contribute to cell fate decisions remains unknown. Recently, the crosstalk between metabolism and epigenetics has emerged as one of the players in tumor development. Here we aim to address the impact of the altered metabolism of cancer cells on their epigenome as a regulatory axis of cell identity and fate. We use human-derived tumor organoids where we introduce genetic encoded fluorescent-based reporters to visualize cell identity and metabolism at single cell level. We combine 4D live imaging with a recently developed machine learning method to re-construct cell-lineages, trace stem cell state and metabolic changes during tumor organoid development. We find that, mimicking the tumor metabolic microenvironment (Warburg effect-driven low-glucose high-lactate) leads to changes cellular metabolism and histone acetylation. Strikingly, these alterations provoke profound changes in tumor development by increasing the population of cancer stem cells and their proliferation and differentiation dynamics.

  Study EGAS50000000063