7189 results for "canc*"

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• Genome and transcriptome sequence data from a metastatic clear cell carcinoma of the ovary patient

  Genome and transcriptome sequence data from a metastatic clear cell carcinoma of the ovary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004661

• Evolution of four ER+ breast cancers

  The evolution of four breast cancers was analyzed using longitudinal samples collected over 2-15 years. Whole-genome sequencing and single-cell RNA-Seq were used to analyze evolution. We have deposited VCF files for SNV, indel, and structural variant calls from WGS data, and a text file showing transcripts per million (TPM) expression for the single-cell RNA-Seq data.

  Dataset EGAD00001003303

• Genome and transcriptome sequence data from a metastatic spindle cell sarcoma patient

  Genome and transcriptome sequence data from a metastatic spindle cell sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004670

• Chromosome Segregation Errors Promote a Diverse Spectrum of Simple and Complex Genomic Rearrangements

  Cancer genomes are frequently characterized by numerical and structural karyotypic abnormalities. Here we combined an inducible centromere-specific inactivation approach with selection for a conditionally essential gene, a strategy we term ‘CEN-SELECT’, and show that single-chromosome missegregation during cell division can directly drive a broad spectrum of structural rearrangement types. Cytogenetic profiling revealed that missegregated chromosomes are 120-fold more susceptible to developing seven major categories of structural variants, including translocations, insertions, deletions, and reassembly into chromothriptically rearranged chromosomes. Whole-genome sequencing of clones with genetically propagatable derivative chromosomes identified complex rearrangements and copy-number alterations that can result in gene inactivation or extrachromosomal gene amplification. We conclude that chromosome segregation errors are sufficient to drive extensive structural variation that recapitulates those commonly associated with human cancers.

  Dataset EGAD00001004163

• Genome and transcriptome sequence data from a metastatic breast carcinoma patient

  Genome and transcriptome sequence data from a metastatic breast carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004676

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004681

• The landscape of somatic mutation in normal colorectal epithelial cells

  The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic events and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.

  Dataset EGAD00001004192

• EPO2_Illumina_WXS_XEN

  Whole-exome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from colorectal cancer primary tumor sample (EPO2_cohort)

  Dataset EGAD00001003363

• Genome and transcriptome sequence data from a metastatic gallbladder cancer patient

  Genome and transcriptome sequence data from a metastatic gallbladder cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003604

• Genome and transcriptome sequence data from an anal cancer patient

  Genome and transcriptome sequence data from an anal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003647

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003652

• Osteosarcoma RNAseq

  We propose to definitively characterise the somatic genetics of Osteosarcoma cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome and transcriptome sequencing.

  Dataset EGAD00001000826

• Hipo-032 Metastasome of Colorectal Cancer

  Whole genome sequencing of Control (blood), Tumor and metastasis triplets for 12 samples.

  Dataset EGAD00001003965

• Whole exome sequencing (WES), shallow whole genome sequencing (sWGS), ultra-deep targeted sequencing (TS), RNA whole transcriptome sequencing (RNAseq), targeted TCR sequencing in RNA (RNA-TCRseq) from breast cancer samples.

  Whole exome sequencing (WES), shallow whole genome sequencing (sWGS), ultra-deep targeted sequencing (TS), RNA whole transcriptome sequencing (RNAseq) bam files. Targeted TCR sequencing in RNA (RNA-TCRseq) cram files.

  Dataset EGAD00001003933

• Exome sequencing data from tumor progression cohort

  This dataset, named Stockholm tumor progression cohort, contains exome-sequencing samples of matched primary and metastasis samples from 20 metastatic breast cancer patients. All patients have one or more sequenced normal samples as well. The total number of samples is 125. The dataset has been used, apart from other studies, to explore tumor evolution patterns in metastatic breast cancer at Karolinska Institute Stockholm.

  Dataset EGAD00001003837

• Exome sequencing files for "A single mutant clone populates the pancreatic ductal system to generate coexisting neoplastic lesions"

  Files from whole exome sequencing of eight tumors from eight pancreatic cancer patients along with matched PanIN precursor lesion(s) and a matched normal tissue.

  Dataset EGAD00001004044

• sWGS of HGSOC samples for fixative comparison study

  Shallow whole-genome sequencing of samples from the study "Methanol-based fixation is superior to buffered formalin for next-generation sequencing of DNA from clinical cancer samples". DNA from each sample (100ng) was sheared on Covaris S220 (Covaris): duty cycle - 10%, intensity -5.0, bursts per sec - 200, duration - 300 sec, mode - frequency sweeping, power - 23V, temperature -5:5 C to 6 C, water level - 13. Libraries were prepared with the TruSeq Nano DNA LT Sample Prep Kit (Illumina) using a modi?ed protocol - Sample Puri?cation Beads were replaced by Agencourt AMPure XP beads (Beckman Coultier) and size selection after the End Repair was done to remove only the short fragments. Quality and quantity for contructed libraries were assessed with DNA 7500 kit on Agilent 2100 Bioanalyzer and with Kapa Quanti?cation kit (KAPA Biosystems) on 7900HT Fast Real-Time PCR System (Applied Biosystems) according to the supplier's recommendations, respectively. Libraries from 18 barcoded samples were pooled together in equimolar amounts and each pool was loaded on a single lane of a HiSeq Single End Flowcell (Illumina), followed by cluster generation on a cBot (Illumina) and sequencing on a HiSeq 2500 (Illumina) in a single-read 50bp mode. Reads were aligned using bwa-mem v0.7.12-r1039 to the 1000 genomes version of human genome build GRCh37. Picard (http://picard.sourceforge.net) was used to remove duplicate reads.

  Dataset EGAD00001001938

• WES analysis of patients with USP8 wild-type corticotroph adenomas

  The overall goal of the Identification of recurrent mutations in Cushing’s disease project is to study the impact of whole-exome sequencing (WES) on the clinical care of cancer patients and oncology provider practices. The aims of Project are to implement and establish the feasibility of WES in patients with USP8 wild-type corticotroph adenomas; to develop a framework for the understanding of the molecular mechanism of the pathogenesis of corticotroph adenoma.

  Dataset EGAD00001004136

• Anaplastic Thyroid Cancer somatic variants (MuTect)

  Sequence was aligned to the GRCH38 reference genome. Aligned sequence was analyzed with GATK/MuTect, to generate somatic variant calls across the SureSelect All Exon V5+UTR target region. Somatic variant calls are in VCF format. In total there are 166 tumour samples, 94 of which have a matched normal. Somatic variants for tumours without a matched normal, were called against a panel of normals. Details for the mutect call can be found in the vcf header.

  Dataset EGAD00001004129

• Targeted sequencing of 72 prostate cancer driver in 712 plasma cell free DNA samples

  Dataset contains targeted sequencing data of 712 plasma cell free DNA samples and 428 white blood cell samples collected from 428 men with metastatic prostate cancer. Target capture was performed using a hydridization-based custom Roche SeqCap EZ Choice kit, designed to capture all exons of 72 prostate cancer driver genes. Cell free DNA was extracted from 10 mL blood samples. Libraries were sequenced using Illumina HiSeq 2500 or Illumina MiSeq instruments to a median coverage of 750x. 62% of samples had ctDNA fraction above 2% of total cfDNA. Note that "Dataset type" is erroneously listed as "Amplicon sequencing", because "Captured-based targeted sequencing" or "Hybridization-based targeted sequencing" were not available options in EGA at the time of submission.

  Dataset EGAD00001004208

• Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma

  Glioblastoma patient derived Fast/Slow cycling cancer stem cell RNA sequencing. Consists of 3 patient cell lines and 6 files

  Dataset EGAD00001004380

• WGBS data of solid liver tumor DNA, and WGBS data of cell-free DNA derived from human blood, for CancerDetector study

  The blood samples of four liver cancer patients and four healthy people, and the solid liver tumor samples of two liver cancer patients are collected for this dataset. Blood samples were centrifuged first at 1,600 × g for 10 minutes, and then the plasma was transferred into new micro tubes and centrifuged at 16,000 × g for another 10 minutes. The plasma was collected and stored at -80⁰C. CfDNA was extracted from 5 ml plasma using the Qiagen QIAamp Circulating Nucleic Acids Kit and quantified by Qubit 3.0 Fluoromter (Thermo Fisher Scientific). Bisulfite conversion of cfDNA was performed by using EZ-DNA-Methylation-GOLD kit (Zymo Research). After that, Accel-NGS Methy-Seq DNA library kit (Swift Bioscience) was used to prepare the sequencing libraries. The DNA libraries were then sequenced with 150bp paired-end reads.

  Dataset EGAD00001004317

• GENOMIC INSTABILITY IN MISMATCH REPAIR DEFICIENT COLORECTAL CANCER WES MSI Colorectal Cancer

  This dataset contains Whole Exome Sequencing of 47 MSI colorectal cancers (CRCs) and paired adjacent normal mucosa

  Dataset EGAD00001004550

• ENU-NCI-H508-Cetuximab-SecondRound

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

  Dataset EGAD00001002065

• Somatic pseudogenes acquired during cancer development – Whole Genome sequencing

  Insertion of processed pseudogenes is known to occur in the germline but has not previously been observed in somatic cells. Formation of pseudogenes could represent a new class of mutation in cancers and a new source of potential driver events.

  Dataset EGAD00001000638

• A Study to Evaluate Denosumab in Young Patients With Primary Breast Cancer (D-Beyond)

  This is a prospective, single arm phase IIa trial in which patients with early breast cancer will receive pre-operatively two doses of denosumab 120mg subcutaneously one week apart (maximum 12 days) followed by surgery. Tumor, normal breast tissue and blood samples will be collected at baseline and at surgery. Post-operative treatment will be at the discretion of the investigator.Primary objective: to determine if a short course of RANKL inhibition with denosumab can induce a decrease in tumor proliferation rates as determined by Ki67 immunohistochemistry (IHC) in newly diagnosed, early stage breast cancer in pre-menopausal women.

  Dataset EGAD00001004391

• Genomic characterization of pancreatic tumours and matched xenograft and organoid models - WGS mapped reads

  Whole Genomes Define Concordance in Matched Primary, Xenograft, and Organoid Models of Pancreas Cancer - WGS mapped reads

  Dataset EGAD00001003586

• Metastatic breast cancer targeted gene screen (2014-09-24)

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations. This dataset contains all the data available for this study on 2014-09-24

  Dataset EGAD00001001018

• 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

• Chordoma Sequencing Project RNAseq

  This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work.

  Dataset EGAD00001000653

• PLCRC study

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from Colorectal cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Dataset EGAD00001000947

• Illumina_WXS_MET-XEN

  Whole-exome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from colorectal cancer metastasis sample

  Dataset EGAD00001002098

• mFAST-SeqS of plasma-DNA

  Sequence data from L1-amplicon libraries prepared from plasma-DNA from a set of 24 female controls and 18 male controls without malignant disease and samples from patients breast (n= 28) and prostate cancer patients (n=61).

  Dataset EGAD00001001314

• OCCAMS_Oesophageal Cancer Organoids_1

  ***THIS DATA CAN ONLY BE USED FOR NON-COMMERCIAL CANCER RESEARCH*** Sequencing of organoid cell lines derived from oesophageal tumour sections taken from patients diagnosed with primary oesophageal cancer who underwent tumour resection surgery.

  Dataset EGAD00001001889

• Melanoma-Til Study RNAseq

  In this study, mutations present in a series of human melanomas (stage IV disease) will be determined, using autologous blood cells to obtain a reference genome. From each of the samples that are analyzed, tumour-infiltrating T lymphocytes have also been isolated. This offers a unique opportunity to determine which (fraction of) mutations in human cancer leads to epitopes that are recognized by T cells. The resulting information is likely to be of value to understand how T cell activating drugs exert their action.

  Dataset EGAD00001000325

• A compendium of mutational signatures due to environmental exposures

  Whole-genome-sequencing (WGS) of human tumours has revealed distinct mutation patterns that hint at the causative origins of cancer. We examined mutational-signatures in 324 WGS of human induced pluripotent stem cells (iPSCs) following exposure to known or suspected environmental carcinogens. 79 agents were tested with or without metabolic activation at concentrations that produced measurable cytotoxicity; 41 yielded characteristic substitution mutational signatures. Some exhibit similarity with signatures found in human tumours. Additionally, 6 agents produced double-substitution signatures and 8 produced indel signatures. Investigating mutation asymmetries across genome topography reveals fully functional mismatch and transcription-coupled repair pathways in iPSCs. Primary adducts induced by environmental carcinogens can be resolved by disparate repair/replicative pathways, resulting in an assortment of signature outcomes even for a single mutagen. This compendium of experimentally-induced mutational-signatures permits further exploration of roles of environmental agents in cancer aetiology, and underscores how human stem cell DNA is directly vulnerable to environmental agents.

  Dataset EGAD00001004583

• Illumina_WGS_T-XEN

  Whole-genome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from colorectal cancer primary tumor sample

  Dataset EGAD00001002091

• Sequencing component for the whole genome methylation analysis in PBMCs and cell subsets (pilot study)

  DNA methylation has been shown to play a major role in determining cellular phenotype by regulating gene expression. Moreover, dysregulation of differentially methylated genes has been implicated in disease pathogenesis of various conditions including cancer development as well as autoimmune diseases such as systemic Lupus erythematosus and rheumatoid arthritis. Evidence is rapidly accumulating for a role of DNA methylation in regulating immune responses in health and disease. However, the exact mechanisms remain unknown. The overall aim of the project is to investigate the role of epigenetic mechanisms in regulating immunity and their impact on autoimmune disease pathogenesis.The aim of this pilot study is to perform whole genome methylation analysis in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4, CD8, CD14, CD19, CD16 and whole PBMCs) obtained from 6 healthy volunteers. Whole genome methylation analysis will be performed using two methodological approaches, the Infinium Methylation Bead Array K450 (Illumina) and MeDIP-seq. mRNA expression arrays will also be performed in order to correlate DNA methylation with gene expression as well as genotyping on the Illumina OmniExpress chip

  Dataset EGAD00001000394

• WGS on patients 5-7, study of metastatic prostate cancer

  Data from the study of subclonal metastatic expansion in prostate cancer. Whole genome shotgun sequencing of six samples, tumour and whole blood, from the three additional patients whose somatic variants were examined in depth.

  Dataset EGAD00001001344

• RNA-seq on patients 1-4, study of metastatic prostate cancer

  Data from the study of subclonal metastatic expansion in prostate cancer. RNA-seq of twelve samples, tumour and benign tissue, from the four initial patients.

  Dataset EGAD00001001345

• Fastq data for ChIP-Seq (H3K9me3) assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for ChIP-Seq (H3K9me3) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001408

• The mutational landscape of normal human endometrial epithelium

  All normal somatic cells are thought to acquire mutations. However, characterisation of the patterns and consequences of somatic mutation in normal tissues is limited. Uterine endometrium is a dynamic tissue undergoing cyclical shedding and reconstitution lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands showed that most are clonal cell populations derived from a recent common ancestor, with mutation burdens differing from other normal cell types and many fold lower than endometrial cancers. Mutational signatures found ubiquitously account for most mutations. Many, in some women all, endometrial glands are colonised by cell clones carrying driver mutations in cancer genes, often with multiple drivers. Total and driver mutation burdens increase with age, but are also influenced by other factors, including body mass index and parity, and clones with drivers often originate during early decades of life. The somatic mutational landscapes of normal cells differ between cell types and are revealing the procession of neoplastic change leading to cancer.

  Dataset EGAD00001004547

• MCO colorectal cancer genomics at UNSW

  This dataset contains DNA sequencing data from 95 colorectal cancer and matched-normal samples. The dataset contains targeted deep sequencing of selected regulatory elements in 95 cancer and matched-normal samples, and data for one sample that was additionally whole-genome sequenced (cancer and matched-normal).

  Dataset EGAD00001004582

• Fastq data for ChIP-Seq (H3K36me3) assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for ChIP-Seq (H3K36me3) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001405

• Genome and transcriptome sequence data from a non small cell lung cancer patient

  Genome and transcriptome sequence data from a non small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001001963

• Genome and transcriptome sequence data from an adenocarcinoma of right lung patient

  Genome and transcriptome sequence data from an adenocarcinoma of right lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001001967

• ENU-NCI-H508 cetuximab fixed concentration project

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

  Dataset EGAD00001001948

• March 2016 update of whole genome shotgun sequencing data (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2016 update of whole genome shotgun sequencing data (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001958

• Genome and transcriptome sequence data from a lung cancer patient

  Genome and transcriptome sequence data from a lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001001965

• Genome and transcriptome sequence data from a breast primary patient

  Genome and transcriptome sequence data from a breast primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002017