11935 results for "cancer rna-seq"

in 17.53 milliseconds.

• ChIP-seq for 10 samples

  This dataset contains ChIP-seq data generated from two patient-derived xenograft (PDX) models. For each model, sequencing data are provided from input control (n=1), IgG control (n=2), and FOXF1 immunoprecipitation (n=2). All the 10 samples are in bam file type.

  Dataset EGAD50000001786

• Targeted sequencing of genes recurrently mutated in AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: ? Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. ? Correlation of prognosis with driver mutations and potentially gene-gene interactions ? Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ?personalised? prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Dataset EGAD00001000606

• MMP-seq tumor samples, UDG treated (FASTQ)

  MMP-seq tumor samples, UDG treated (FASTQ)

  Dataset EGAD00001001104

• MethylScan data of plasma samples

  10ng from each cfDNA sample was used as the input material. For gDNA samples, 1.5-2ug each was first sonicated by Covaris R230 system (Woburn, MA). Next, size-selection with 0.8x-1.5x two-step Ampure XP beads was performed to enrich the 150-200bp fragments. 200ng of the size-selected gDNA was used as input material. The pre-capture library construction was performed with NEB UltraII DNA library prep kit for Illumina (Ipswich, MA) and the adapter was the methylated EM-seq adapter. Before the first PCR amplification, the gDNA samples were subjected to bisulfite conversion by QIAGEN Epitect kit, and cfDNA samples were subjected to enzymatic conversion by NEBNext enzymatic methyl-seq kit if the hybrid capture panel designed for converted DNA was used downstream. Twist panel hybrid capture was performed with their standard protocol (Twist Bioscience, South San Francisco, CA). The concentration of the post-capture library after the second PCR amplification was measured by Qubit 1xdsDNA HS kit (ThermoFisher, Waltham, MA). Their quality was examined by TBE-UREA PAGE and Bioanalyzer before sequencing. Libraries were then sequenced with 150bp paired-end reads on Illumina machines by Genewiz, Inc. (South Plainfield, NJ, USA). This dataset contains MethylScan data of the plasma samples from 248 noncancer individuals and 27 cancer patients (17 liver and 10 GI-tract cancers).

  Dataset EGAD00001015815

• Altered oligodendrocyte heterogeneity in Multiple sclerosis revealed by single nuclei RNA sequencing

  This study is currently hosted by the European Nucleotide Archive. To access the data contained within the Study please follow the link below: https://www.ebi.ac.uk/ena/browser/view/PRJEB39323 Oligodendrocyte (OL) pathology is increasingly implicated in neurodegenerative diseases, as they are involved in metabolic support of axons and functional cross-talk with other brain cells. Rodent OLs are heterogeneous, with developmental and biological differences, but the extent of heterogeneity in the normal human brain and its contribution to any changes to disease remains unknown. Here we performed single nuclei RNA-sequencing (snRNA-seq) from white matter (WM) areas of post mortem human brain both in control (Ctr) and multiple sclerosis (MS) patients. We identified several sub-clusters of oligodendroglia in the Ctr human WM, some similar to those in mouse, and defined new markers for these cell states. Strikingly, some of these sub-clusters were under-represented in MS tissue, while others were more prevalent than in controls. We found a lack of OL precursor cells (OPCs) and an OL subcluster in an intermediate stage of differentiation in MS lesions and in normal appearing white matter (NAWM), suggesting either depletion by the disease or by a regenerative response. The differences in mature OL sub-clusters indicate different functional states of OLs in MS tissue and, as this is similar in NAWM to lesions, that MS is a more diffuse brain disease than the focal demyelinating lesions suggest. We were also able to identify new putative markers of different MS lesion subtypes. Our findings of an altered heterogeneity of oligodendroglia in MS may have an important contribution to our understanding of disease progression and may alter therapeutic approaches to MS.

  Study EGAS00001003412

• Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer

  Our study provides insight into molecular alterations in HN tissues within the affected breast and offers a greater understanding of the spatial implications of these aberrations. This was achieved by performing a comprehensive analysis of RNA sequencing data and proteomic profiles from breast cancers (n=19) and their matched HN tissues (n=38), healthy breast from cosmetic reduction mammoplasty (RM; n=5), and risk reducing mastectomies (RR, n=5), with peritumoral samples excised at proximal (TP, <2 cm) and distal (TD, 5-10 cm) sites from the primary tumor.

  Study EGAS00001004510

• Osteosarcoma mate-pair and RNA-sequencing

  DNA mate pair and RNA sequencing data of conventional osteosarcomas. Mate pair libraries, with average insert sizes of 2-4 kb, were prepared for sequencing using the Nextera Mate Pair Library Preparation Kit. Paired-end 76 base pair reads were generated using an Illumina NextSeq 500 sequencing instrument. Total RNA was enriched for polyadenylated RNA using magnetic oligo(dT) beads. Enriched RNA was prepared for sequencing using the TruSeq RNA Sample Preparation Kit v2 and paired-end 151 base pair reads were generated from the cDNA libraries using an Illumina NextSeq 500 instrument.

  Study EGAS00001003842

• scD&D-seq of mobilized PBMC from a healthy individual having IDH2 R140Q CHIP

  Single-cell D&D-seq profiles from a mobilized CHIP (clonal hematopoiesis of indeterminate potential) PBMC sample (2 replicates) co-profiled with IDH2 R140Q GoT-ChA.

  Study EGAS50000001590

• ETMR H3K27Ac ChIPSeq

  H3K27Ac ChIP-seq DNA libraries for 5 ETMR samples were prepared using NEBNext ChIP-seq Illumina Sequencing library preparation kit. ChIP-seqlibraries were sequenced using single-end 50 bp reads on the Illumina HiSeq 2000 platform. ChIP-seq peaks analysed was conducted as published previously(Torchia et al. 2016).

  Dataset EGAD00001004809

• miRNA seq data of 13 cases

  miRNA seq data of 13 cases (MMML)

  Dataset EGAD00001001632