Search Results - EGA European Genome-Phenome Archive

Reference epigenome SMC09 mRNA-Seq data generated from KEP study

SMC09 mRNA-Seq paired end data

Dataset EGAD00001007176

oxBS-seq for APL

Oxidative bisulfite sequencing (oxBS-Seq) for APL

Dataset EGAD00001008135

Dataset for iAMP21 scRNA-seq

10x Genomics 5' library scRNA-seq data for 4 iAMP21 patients

Dataset EGAD00001009504

Dataset for NSCLC-RNA

Rare cancer sequencing data of 45 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

Dataset EGAD00001008846

RNA sequencing reads

Paired-end, ribosome depleted, total RNA Sequencing

Dataset EGAD00001004327

Small RNA (<100 bases in length) were purified from total RNA using miRNeasy kit (Qiagen), then sequenced. Libraries were prepared at the Genomics Platform of the Cochin Institute, following the TruSeq small RNA protocol (Illumina), starting from 1 µg of high quality total RNA. Single read (1 × 75 bp) sequencing was performed on a Nextseq 500 platform (Illumina). FASTQ sequences were aligned on miRBase v.2052, then counted with STAR (v.2.5.2a).

Dataset EGAD00001004998

Transcriptome_analysis_of_LCM_samples_

We aim to set up a RNA pipeline for LCM samples to study transcriptome landscape of tumor and normal tissues. RNA was extracted from Lazer capture micro-dissection tissues and cDNA libraries were prepared with SMARTseq2 protocol. Libraries are pooled to be sequenced.

Study EGAS00001003862

ICGC MMML-seq Data Freeze March 2013 transcriptome sequencing

Dataset EGAD00001000356

McGill EMC Release 4 for assay "Bisulfite-seq"

McGill EMC Release 4 for assay "Bisulfite-seq": Methylation profiling by high-throughput sequencing

Dataset EGAD00001001289

McGill EMC Release 4 for assay "mRNA-seq"

McGill EMC Release 4 for assay "mRNA-seq": Transcriptome profiling by high-throughput sequencing

Dataset EGAD00001001291

McGill EMC Release 4 for assay "smRNA-seq"

McGill EMC Release 4 for assay "smRNA-seq": Transcriptome profiling by high-throughput sequencing

Dataset EGAD00001001292

Reference epigenome CKD23_C_Mesan_mRNA-Seq data generated from KEP study

A CKD23_C_Mesan_mRNA-Seq paired end data for Mesangial cells(kidney)

Dataset EGAD00001003481

Reference epigenome CKD27_C_Mesan_mRNA-Seq data generated from KEP study

A CKD27_C_Mesan_mRNA-Seq paired end data for Mesangial cells(kidney)

Dataset EGAD00001003484

Reference epigenome OB57_D_PreA_mRNA-Seq data generated from KEP study

A OB57_D_PreA_mRNA-Seq paired end data for Preadipocyte(fat)

Dataset EGAD00001003487

Reference epigenome OB56_N_PreA_smRNA-Seq data generated from KEP study

A OB56_N_PreA_smRNA-Seq single end data for Preadipocytes(fat)

Dataset EGAD00001003495

Reference epigenome OB57_D_PreA_smRNA-Seq data generated from KEP study

A OB57_D_PreA_smRNA-Seq single end data for Preadipocyte(fat)

Dataset EGAD00001003496

Reference epigenome CKD23_C_Mesan_smRNA-Seq data generated from KEP study

A CKD23_C_Mesan_smRNA-Seq single end data for Mesangial cells(kidney)

Dataset EGAD00001003497

Reference epigenome CKD27_C_Mesan_smRNA-Seq data generated from KEP study

A CKD27_C_Mesan_smRNA-Seq single end data for Mesangial cells(kidney)

Dataset EGAD00001003500

Histone marks

EZH2, H3K4me3, H3K27ac and H3K27me3 ChIP-seq data consisting of fastq single-end reads from peripheral blood CLL cells

Dataset EGAD00001004063

Reference epigenome KNIH010 mRNA-seq data generated from KEP study

A KNIH010 mRNA-seq paired end data for podocytes

Dataset EGAD00001002176

Reference epigenome KNIH011 mRNA-seq data generated from KEP study

A KNIH011 mRNA-seq paired end data for podocytes

Dataset EGAD00001002177

Reference epigenome KNIH010 miRNA-seq data generated from KEP study

A KNIH010 miRNA-seq single end data for podocytes

Dataset EGAD00001002769

Reference epigenome KNIH011 miRNA-seq data generated from KEP study

A KNIH011 miRNA-seq single end data for podocytes

Dataset EGAD00001002770

Reference epigenome Pancreas-Islet06 miRNA-Seq data generated from KEP study

Pancreas-Islet06 miRNA-Seq single end data

Dataset EGAD00001007187

Reference epigenome Pancreas-Islet07 miRNA-Seq data generated from KEP study

Pancreas-Islet07 miRNA-Seq single end data

Dataset EGAD00001007188

Reference epigenome Pancreas-Islet08 miRNA-Seq data generated from KEP study

Pancreas-Islet08 miRNA-Seq single end data

Dataset EGAD00001007189

Reference epigenome Fat-adipocyte03 miRNA-Seq data generated from KEP study

Fat-adipocyte03 miRNA-Seq single end data

Dataset EGAD00001007190

Reference epigenome Fat-adipocyte04 miRNA-Seq data generated from KEP study

Fat-adipocyte04 miRNA-Seq single end data

Dataset EGAD00001007191

Reference epigenome Fat-adipocyte05 miRNA-Seq data generated from KEP study

Fat-adipocyte05 miRNA-Seq single end data

Dataset EGAD00001007192

Reference epigenome Islet-derived_MSC08 miRNA-Seq data generated from KEP study

Islet-derived_MSC08 miRNA-Seq single end data

Dataset EGAD00001007882

Reference epigenome Islet-derived_MSC08 mRNA-Seq data generated from KEP study

Islet-derived_MSC08 mRNA-Seq paired end data

Dataset EGAD00001007879

Reference epigenome Islet-derived_iPSC04 mRNA-Seq data generated from KEP study

Islet-derived_iPSC04 mRNA-Seq paired end data

Dataset EGAD00001007880

Reference epigenome Islet-derived_MSC06 miRNA-Seq data generated from KEP study

Islet-derived_MSC06 miRNA-Seq single end data

Dataset EGAD00001007881

Reference epigenome Islet-derived_iPSC04 miRNA-Seq data generated from KEP study

Islet-derived_iPSC04 miRNA-Seq single end data

Dataset EGAD00001007883

scRNA-seq of placental immune cells

scRNA-seq analysis of 384 placental immune cells

Dataset EGAD00001010040

STAG1-ChIP-Seq of STAG2-mutated and cohesin wildtype adult AMLs

ChIPseq targeting the cohesin subunit STAG1 in STAG2-mutated AMLs or cohesin wildtype AMLs

Dataset EGAD00001011206

The Environmental Determinants of Diabetes in the Young Study (TEDDY)

Study Overview The Environmental Determinants of Diabetes in the Young (TEDDY) Study is a longitudinal study that investigates genetic and genetic-environmental interactions, including gestational events, childhood infections, dietary exposures, and other environmental factors after birth, in relation to the development of islet autoimmunity and type 1 diabetes (T1D). A consortium of six clinical centers assembled to participate in the development and implementation of the study to identify environmental triggers for the development of islet autoimmunity and T1D in genetically susceptible individuals. Beginning in 2004, the TEDDY study screened over 400,000 newborns for high-risk HLA-DR, DQ genotypes from both the general population and families already affected by T1D. The TEDDY study enrolled around 8,676 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) in the 15-year prospective follow-up. Participants are followed every three months for islet autoantibody (IA) measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive participants continue to be followed at three month intervals and autoantibody negative participants are followed at six-month intervals. In addition to the analysis of autoantibodies, additional data and sample collection are performed at each visit. Parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. Additional information on the TEDDY study is available in the following articles: Rewers et al., 2008, PMID: 19120261 and Hagopian et al., 2006, PMID: 17130573. Details of the TEDDY protocol can be found in Hagopian et al., 2011, PMID: 21564455. TEDDY data currently available in dbGaP include: gene expression, SNPs, exome, microbiome (gut, nasal, and plasma), RNA sequencing, and whole genome sequencing. For more information on TEDDY Study version history please refer to TEDDY Study dbGaP README File. ImmunoChip SNP DNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for SNP genotyping. Genotyping was performed by the Center for Public Health Genomics at the University of Virginia using the Illumina ImmunoChip SNP array, which contains around 196,000 SNPs from 186 regions associated with 12 autoimmune diseases (Hadley et al., 2015, PMID: 26010309). Data cleaning and validation included the removal of subjects with a low call rate (< 5% SNPs missing) and differences in reported sex and prior genotyping at the TEDDY HLA laboratory. Additionally, SNPs with a low call rate or Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements, were removed from the final dataset (Törn et al., 2015, PMID: 25422107).TEDDY-T1DExome ArrayDNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for genotyping. Genotyping was performed by the University of Virginia using the Illumina TEDDY-T1DExome array. The TEDDY-T1DExome array is a custom chip that contains 550,601 markers from the Infinium CoreExome-24 v1.1 BeadChip and an additional 90,214 tagSNPs specifically selected by the TEDDY investigators based on their associations with nutrients, vitamins, type 2 diabetes, autoimmune diseases, body-mass index, or other exposures and phenotypes measured by TEDDY study.The Illumina GenTrain2 algorithm was used for genotype calling. Sample quality control metrics included sample call rate, heterozygosity rate and concordance of gender between the information reported and genotyped. Gene Expression The TEDDY study collected peripheral blood for the extraction of total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA (200 ng) was further used for cRNA amplification and labeling with biotin using Target Amp cDNA synthesis kit (Epicenter catalog no. TAB1R6924). Labeled cRNA was hybridized to the Illumina HumanHT-12 Expression BeadChips based on the manufacturer's instructions. The HumanHT-12 Expression BeadChip provides coverage for more than 47,000 transcripts and known splice variants across the human transcriptome. Microbiome The TEDDY microbiome study aimed to characterize the longitudinal development of the microbiome, including bacteria, viruses and other microorganisms in the gut, plasma, and nasal cavity of prediabetic and diabetic subjects compared to autoantibody negative non-diabetic subjects. Stool samples used were collected monthly from 3 to 48 months, after which stool samples were collected every 3 months. Nasal swab samples were collected every 3 months starting at 9 months of age until 48 months, after which nasal swabs were collected every 6 months. Plasma samples were collected every 3 months starting at 3 months of age until 48 months, after which plasma samples were collected every 6 months. If the subject was autoantibody positive at 48 months then they remained on the 3 month collection interval for nasal swab and plasma samples. Samples underwent 16s rRNA gene sequencing, DNA and viral RNA metagenomics shotgun sequencing, and sequencing of the internal transcribed spacer (ITS) regions. Additional information on the TEDDY microbiome data is available in the following articles: Vatanen et al., 2018, PMID: 30356183, Stewart et al., 2018, PMID: 30356187, and Vehik et al., 2020, PMID: 31792456. RNA Sequencing The TEDDY study aimed to characterize the transcriptome in subjects with islet autoimmunity and type 1 diabetes compared to matched control subjects. Peripheral blood was collected to extract total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA was then sent to the Broad Institute for the generation of the TEDDY RNA sequencing (RNA-Seq) data. The RNA samples were prepped using Superscript III reverse transcriptase and Illumina's TruSeq Stranded mRNA Sample Prep Kit. The TruSeq libraries were run on the Illumina HiSeq2500 platform. Whole Genome Sequencing The TEDDY study aimed to conduct deep whole genome sequencing and examine the genomic variations in subjects with islet autoimmunity and type 1 diabetes compared to matched autoantibody negative and non-diabetic children. DNA from whole blood was obtained from TEDDY children for whole genome sequencing. The WGS data were generated on the Illumina HiSeq X Ten system.

Study phs001442

9296 results for "cancer rna-seq"

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