12312 results for "cancer rna-seq"

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• DNA-seq from plasma of 14 liver transplantation patients

  DNA-seq from plasma of 14 liver transplantation patients

  Dataset EGAD00001004590

• mRNA-Seq dataset

  mRNA-Seq, HiSeq 2000 dataset of the Cell-line use case

  Dataset EGAD00001002250

• Reference epigenome IPS-NPC02 h3k4me3 ChIP-Seq data generated from KEP study

  IPS-NPC02 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007288

• Paired-end snATAC-seq analysis of the 3D spatially mapped GBM samples.

  Dataset contains 11 paired-end snATAC-seq samples from 4 patients.

  Dataset EGAD00001010313

• HCA_Reproductive_Tract_Adult_RNA

  HCA Reproductive Tract Adult RNA

  Study EGAS00001006636

• Bulk RNA sequencing of ALS patients

  We performed RNA sequencing to screen for alternative splicing alterations in patients with ALS to identify those linked to ALS pathology.

  Study JGAS000851

• RNA Sequencing of paediatric patients with B lymphoblastic leukemia

  RNA sequencing was performed on 148 Bone marrow of peripheral blood samples of paediatric patients with B-ALL.

  Study EGAS00001004532

• reChIP-seq reveals widespread bivalency of H3K4me3 and H3K27me3 in CD4+ memory T-Cells

  Identification of genomic loci exhibiting the physical co-localization of two distinct DNA-associated proteins remains a technical challenge. To tackle this challenge we have developed a novel reChIP-seq approach that enriches for two distinct DNA-associated proteins in an unbiased and genome-wide manner. We illustrate the utility of our approach by identifying nucleosomes bivalently modified by H3K4me3 and H3K27me3 in primary human CD4+ central memory T-cells (TCMs). We unravel widespread bivalency of many unmethylated CpG-rich regions in TCMs overlapping with transcriptional start sites of developmental regulators. Furthermore, reChIP-seq uncovers two yet unobserved classes of bivalency, where either H3K4me3 or H3K27me3 is mixed with low but detectable bivalency. We provide evidence that bivalency is established by an interplay between genome and epigenome and thus attains stability. Our described reChIP-seq approach augments conventional ChIP-seq and is broadly applicable in the study of co-localization of DNA-associated proteins to unravel the intricate possibilities of combinatorial action.

  Study EGAS00001001568

• RNA sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia (set 2)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one TCF3::PBX1 ALL patient (ALLT-376). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002578

• RNA sequencing data of pediatric KMT2A-rearranged acute lymphoblastic leukemia (set 3)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one KMT2A-r ALL patient (ALLT-375). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002581

• RNA sequencing data of pediatric ETV6::RUNX1 acute lymphoblastic leukemia (set 5)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one ETV6::RUNX1 ALL patient (ALLT-380). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002591

• RNA sequencing data of pediatric B-other acute lymphoblastic leukemia (set 3)

  The dataset includes RNA sequencing FASTQ files from diagnostic tumor samples of two B-other ALL patients (ALLT-369, ALLT-378). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor samples were sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002600

• 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

• MiRNome_pituitary_adenoma

  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

• Genomic Analysis of Follicular Lymphoma

  We included tumors from newly diagnosed or untreated follicular lymphoma in this study. Samples consented to the University of Iowa and Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE) were included for data sharing. RNA was extracted from 1) CD19 sorted B cells from tumor cell suspension frozen in dimethyl sulfoxide (DMSO; RNA Tumor B Cell, n=77), 2) tumor cell suspensions frozen in DMSO (RNA Tumor DMSO, n=78), and 3) tumor tissue sections frozen in optimal cutting temperature compound (OCT; RNA Tumor OCT, n=53). For RNA sequencing, library preparation was done using the Illumina TruSeq RNA Exome Kit and sequenced with 100 nucleotide paired-end reads using the HiSeq 4000. DNA was extracted from 1) tumor cell suspensions frozen in DMSO (DNA Tumor DMSO, n=78), 2) tumor tissue sections frozen in OCT (DNA Tumor OCT, n=33), and 3) germline DNA from peripheral blood (n=102) and from normal tissue adjacent tumor (n=9). For whole exome sequencing (WES), library preparation was done using the Agilent SureSelect XT kit and sequenced with 100 nucleotide paired-end reads using the Illumina HiSeq 4000.

  Study phs002989

• scRaCH-seq data targeting BTK and SF3B1

  Data set for scRaCH-seq manuscript. We base call the fast5 using guppy.

  Dataset EGAD50000000235

• Reference epigenome ADMSC04_smRNA-Seq data generated from KEP study

  A ADMSC04_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003870

• dataset_CML_chipseq_pairend_fastq

  BMI1 ChIP-seq on human K562

  Dataset EGAD00001002061

• dataset_CML_chipseq_pairend_bam

  BMI1 ChIP-seq on human K562

  Dataset EGAD00001002062

• Reference epigenome ADMSC02 mRNA-Seq data generated from KEP study

  ADMSC02 mRNA-Seq paired end data

  Dataset EGAD00001007151

• Reference epigenome ADMSC05 miRNA-Seq data generated from KEP study

  ADMSC05 miRNA-Seq single end data

  Dataset EGAD00001007177

• Reference epigenome ADMSC06 miRNA-Seq data generated from KEP study

  ADMSC06 miRNA-Seq single end data

  Dataset EGAD00001007178

• Reference epigenome ADMSC07 miRNA-Seq data generated from KEP study

  ADMSC07 miRNA-Seq single end data

  Dataset EGAD00001007179

• Reference epigenome ADMSC08 miRNA-Seq data generated from KEP study

  ADMSC08 miRNA-Seq single end data

  Dataset EGAD00001007180

• Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

  Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

  Study EGAS00001005530