15130 results for "cancer studies using rna-seq"

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• Reference epigenome ADMSC02 h3k9me3 ChIP-Seq data generated from KEP study

  ADMSC02 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007366

• Reference epigenome ADMSC05 h3k4me1 ChIP-Seq data generated from KEP study

  ADMSC05 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007377

• Reference epigenome ADMSC06 h3k27Ac ChIP-Seq data generated from KEP study

  ADMSC06 h3k27Ac ChIP-Seq paired end data

  Dataset EGAD00001007381

• Reference epigenome ADMSC06 h3k4me1 ChIP-Seq data generated from KEP study

  ADMSC06 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007384

• Reference epigenome ADMSC07 h3k27Ac ChIP-Seq data generated from KEP study

  ADMSC07 h3k27Ac ChIP-Seq paired end data

  Dataset EGAD00001007388

• Reference epigenome ADMSC07 h3k27me3 ChIP-Seq data generated from KEP study

  ADMSC07 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007389

• Reference epigenome ADMSC06 h3k36me3 ChIP-Seq data generated from KEP study

  ADMSC06 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007383

• Reference epigenome KNIH007 miRNA-seq data generated from KEP study

  A KNIH007 miRNA-seq single end data for adipocytes

  Dataset EGAD00001002766

• Reference epigenome KNIH008 miRNA-seq data generated from KEP study

  A KNIH008 miRNA-seq single end data for adipocytes

  Dataset EGAD00001002767

• Reference epigenome ADMSC03 h3k27ac ChIP-Seq data generated from KEP study

  ADMSC03 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007368

• Reference epigenome SMC08 h3k4me1 ChIP-Seq data generated from KEP study

  SMC08 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007346

• Reference epigenome ADMSC02 input ChIP-Seq data generated from KEP study

  ADMSC02 input ChIP-Seq paired end data

  Dataset EGAD00001007367

• Reference epigenome Islet-derived-MSC04 miRNA-Seq data generated from KEP study

  Islet-derived-MSC04 miRNA-Seq single end data

  Dataset EGAD00001007184

• Reference epigenome SMC03 input ChIP-Seq data generated from KEP study

  SMC03 input ChIP-Seq paired end data

  Dataset EGAD00001007325

• Reference epigenome ADMSC03 h3k36me3 ChIP-Seq data generated from KEP study

  ADMSC03 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007369

• Reference epigenome ADMSC03 h3k4me1 ChIP-Seq data generated from KEP study

  ADMSC03 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007370

• Reference epigenome ADMSC03 h3k4me3 ChIP-Seq data generated from KEP study

  ADMSC03 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007371

• Reference epigenome ADMSC03 h3k9me3 ChIP-Seq data generated from KEP study

  ADMSC03 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007372

• Reference epigenome ADMSC03 input ChIP-Seq data generated from KEP study

  ADMSC03 input ChIP-Seq paired end data

  Dataset EGAD00001007373

• Reference epigenome ADMSC05 h3k27Ac ChIP-Seq data generated from KEP study

  ADMSC05 h3k27Ac ChIP-Seq paired end data

  Dataset EGAD00001007374

• Whole genome sequencing of 198 epileptic individuals.

  This dataset includes whole genome sequencing of 198 epileptic individuals. Libraries preparation and whole-genome sequencing: gDNA was cleaned up using ZR-96 DNA Clean & ConcentratorTM-5 Kit (Zymo) prior to being quantified using the Quant-iTTM PicoGreen dsDNA Assay Kit (Life Technologies) and its integrity assessed on agarose gels. Libraries were generated using the TruSeq DNA PCR-Free Library Preparation Kit (Illumina) according to the manufacturer’s recommendations. Libraries were quantified using the Quant-iTTM PicoGreen dsDNA Assay Kit (Life Technologies) and the Kapa Illumina GA with Revised Primers-SYBR Fast Universal kit (Kapa Biosystems). Average size fragment was determined using a LabChip GX (PerkinElmer) instrument. The libraries were denatured in 0.05N NaOH and diluted to 8pM using HT1 buffer. The clustering was done on a Illumina cBot and the flowcell was ran on a HiSeq 2500 for 2x125 cycles (paired-end mode) using v4 chemistry and following the manufacturer's instructions. A phiX library was used as a control and mixed with libraries at 0.01 level. Bioinformatics: The Illumina control software was HCS 2.2.58, the real-time analysis program was RTA v. 1.18.64. Program bcl2fastq v1.8.4 was used to demultiplex samples and generate fastq reads. The filtered reads were aligned to reference Homo_sapiens assembly b37. Each readset was aligned to creates a Binary Alignment Map file (.bam).

  Dataset EGAD00001004062

• Nasopharyngeal RNASeq Comparing SARS-CoV-2+ Patients and SARS-CoV-2 Negative Control Subjects

  The goal of this analysis was to compare RNAs enriched in the upper respiratory tract of SARS-CoV-2 patients and SARS-CoV-2 negative controls. RNA-sequencing of RNA isolated from the viral transport medium associated with nasopharyngeal swab samples from SARS-CoV-2+ patients and SARS-COV-2 negative controls.

  Study phs002433

• Genomic characterization of a patient with AGS and CdLS transcriptomic comparison of his monocytes against healthy and disease control samples

  In this study, we describe an extreme genetic phenotype of two simultaneous genetic lesions, leading to broad alterations in immunophenotype and transcriptome. Whole Exome Sequencing and RNA-Sequencing of CD14+ monocytes was performed on the case patient, and RNA-sequencing was also performed on disease (Systemic Lupus Erythematosus) and healthy controls.

  Study EGAS00001007829

• An Organoid Biobank of Rare Human Neuroendocrine Neoplasms Enables Genotype-Phenotype Mapping

  We performed whole genome sequencing and RNA-sequencing of neuroendocrine neoplasm. The aim of this study was to provide genetic landscape of neuroendocrine neoplasm, to construct available animal models, and to engineer neuroendocrine neoplasm from normal colon epithelium. The reference genomes used are GRCh37 for whole genome sequencing and GRCh38 for RNA-sequencing.

  Study JGAS000237

• Gene expression in brain (Schizophrenia) study

  The study included post-mortem brain tissue samples from 68 schizophrenia patients and 44 age and sex matched control subjects. Whole transcriptome poly-A selected paired-end RNA sequencing was performed on tissue from prefrontal cortex and orbitofrontal cortex. RNA expression differences were detected between case and control individuals, focusing both on single genes and pathways.

  Study EGAS00001004199

• TwinsUK_Whole_Skin_DNA_Methylation_Microarray_Data

  Whole-skin DNA Methylation profiled using Illumina Infinium HumanMethylation450 BeadChip Arrays. Methylation was quantified in beta values, which were normalised using the regRCPqn algorithm.

  Dataset EGAD00010002671

• ICGC PedBrain: RNA sequencing

  ICGC PedBrain: RNA sequencing

  Dataset EGAD00001000328

• HipSci - Healthy Normals - RNA Sequencing - May 2015

  HipSci - Healthy Normals - RNA Sequencing - May 2015

  Dataset EGAD00001001438

• RNA data for MMML (EGAS00001002422)

  RNA sequencing data for MMML (3 tumor samples and 1 gcbcell)

  Dataset EGAD00001003285

• ICGC MMML-seq Data Freeze March 2013 transcriptome sequencing

  ICGC MMML-seq Data Freeze March 2013 transcriptome sequencing

  Dataset EGAD00001000356

• Reference epigenome IPS02_N_NPC_mRNA-Seq data generated from KEP study

  A IPS02_N_NPC_mRNA-Seq paired end data for Neural progenitor cells(Nestin)

  Dataset EGAD00001003489

• Reference epigenome IPS02_N_NPC_smRNA-Seq data generated from KEP study

  A IPS02_N_NPC_smRNA-Seq single end data for Neural progenitor cells(Nestin)

  Dataset EGAD00001003502