4982 results for "*oma"

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• Medulloblastoma PDX Primary tumor

  Dataset EGAD00001009484

• Medulloblastoma Cirlce-Seq

  Circle-Seq experiment.

  Dataset EGAD00001009483

• Oesophageal adenocarcinoma scRNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains single-cell RNA-seq generated from the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19) and additional donors with Barrett's oesophagus using the 5' Single Cell Gene Expression assay from 10x Genomics. Samples were generated from oesophageal tumours, Barrett's oesophagus, and normal oesophagus and gastric tissues, with the aim of generating a reference atlas for cell types found in normal and disease-associated tissue states in the upper GI tract. This reference atlas was used as the basis for a deconvolution workflow to estimate the cell composition of bulk transcriptomes from these tissues, and to assess cell type-specific expression patterns of potential predictive biomarkers for immunochemotherapy regimens in this setting.

  Dataset EGAD00001009401

• sc-RNA-Seq soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001009002

• RNA-Seq of primary pediatric kidney tumor controls for the soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008709

• RNA-Seq soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008467

• WGS soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008466

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Transcriptomic sequencing on pre-immunotherapy melanoma patients.

  Dataset EGAD00001007710

• Multi-site tumor sampling highlights molecular intra-tumor heterogeneity in malignant pleural mesothelioma

  Dataset EGAD00001007762

• Single cell RNA-Seq of Clear Cell Sarcoma of the Kidney

  Dataset EGAD00001007498

• Immunotesting cohort with RNA-seq data of melanoma samples

  This dataset contains RNA-seq raw data in fastq format from 9 melanoma samples. The samples are formalin-fixed paraffin-embedded (FFPE) treated. For target enrichment SureSelect XT Human All Exon V6 was used. The libraries were sequenced in paired-end mode (2 x 50 nt) on a NovaSeq6000 S2 flow cell.

  Dataset EGAD00001006783

• Whole-genome sequencing of a thyroid carcinoma harboring a ETV6-NTRK3 fusion and a NTRK3 G623R mutation (HIPO-021)

  Dataset EGAD00001006243

• ChIP-Seq files for RMS.

  ChIP-Seq files accompanying the paper titled "Identification of Therapeutic Targets in Rhabdomyosarcoma Through Integrated Genomic, Epigenomic, and Proteomic Analyses".

  Dataset EGAD00001006398

• PromethION (and Illumina) WGS and MinION transcriptome for a patient with diffuse large B-cell lymphoma.

  Dataset EGAD00001006204

• Whole-genome and transcriptome sequencing of a patient with extrapancreatic acinar cell carcinoma

  Dataset EGAD00001006023

• Whole-genome and transcriptome sequencing data of an undifferentiated gastric spindle cell sarcoma

  Dataset EGAD00001006014

• scRNA-seq of glioblastoma cells alone or after co-culture with cerebral organoid cells

  Dataset EGAD00001005315

• Paired-end RNA-seq analysis of the 3D evolution of glioma cell populations. Part 1.

  Dataset includes 160 double-stranded RNAseq libraries collected from 16 patients with adult diffuse glioma. The majority of these samples were spatially-mapped during sample collection, enabling the genomic information derived from them to be mapped in 3D space.

  Dataset EGAD00001005222

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 1.

  Dataset contains Exome sequencing data (aligned and base quality score recalibrated BAM files) for 236 tumor samples + matched normal from blood, collected from 21 patients with adult diffuse glioma. The majority of these samples were spatially-mapped during sample collection, enabling the genomic information derived from them to be mapped in 3D space.

  Dataset EGAD00001005221

• Transcriptome of Ewing sarcoma tumors - RNA-seq (ICGC)

  Transcriptome of Ewing sarcoma tumors (ICGC project). Fastq files of 57 RNA-seq are available (2x101bp).

  Dataset EGAD00001004493

• Identification of molecular subgroups in multiple myeloma by whole exome sequencing.

  Dataset EGAD00001004408

• Whole Genome Sequencing of HCC

  The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003994

• Whole exome sequencing data from two patients with isolated myelosarcoma followed by acute myeloid leukemia

  Dataset EGAD00001003831

• RNA-SEQ data from 13 CAF (Cancer Associated Fibroblast) samples sorted from fresh high-grade ovarian carcinoma

  Dataset EGAD00001003460

• Raw sequencing data - Intra-tumor heterogeneity and clonal evolution patterns towards platinum-resistant high-grade serous ovarian cancer

  This dataset includes 69 sampels of whole-exome sequencing data of high-grade serous ovarian carcinoma (HGSOC). We included patients with advanced (International Federation of Gynecology and bstetrics [FIGO] stage IIIeIV) HGSOC for which biopsies were obtained during debulking surgery, the first at initial diagnosis and the second at disease relapse. Where possible, matched normal DNA from each participating patient was obtained from a whole-blood sample. Written informed consent was obtained from all patients and approved by the local ethics committee.

  Dataset EGAD00001001381

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - side_cases_barretts

  Dataset EGAD00001001379

• Whole-Genome Bisulfite Sequencing of a paired initial and recurrent glioma

  Dataset EGAD00001001616

• Carcinoma of the oral tongue (OTSCC) genomic landscape characterisation

  18 Exomes for discovery set and 60 Targeted panel for prevalence set

  Dataset EGAD00001001465

• Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma

  Dataset EGAD00001003324

• Targeted resequencing of coding regions of ribosomal protein genes in multiple myeloma samples

  Dataset EGAD00001003302

• Pseudomyxoma peritonei exome sequencing vcf-files

  Dataset EGAD00001003297

• Ewing sarcoma genome sequencing

  Dataset EGAD00001001051

• BAM files from Cholangiocarcinoma exome sequencing

  Dataset EGAD00001001220

• Lengthening and shortening of plasma DNA in hepatocellular carcinoma patients

  Dataset EGAD00001001275

• Integrated molecular analysis of clear cell renal cell carcinoma

  Dataset EGAD00001000597

• Pilocytic Astrocytoma ICGC PedBrain RNA sequencing

  Pilocytic Astrocytoma ICGC PedBrain RNA sequencing

  Dataset EGAD00001000617

• Angiosarcoma follow up study

  A bespoke targeted pulldown experiment will be performed on patients with Angiosarcoma. the resulting products will be sequenced to determine the prevalence of previously found mutations in these patients.

  Dataset EGAD00001000620

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - pilot normal and pre/post-chemo

  Dataset EGAD00001000704

• DIPG_ICR_WES

  Whole exome sequencing of 6 tumour and normal pairs of diffuse intrinsic pontine glioma (DIPG)

  Dataset EGAD00001000706

• Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma

  Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma by massively-parallel sequencing of tumour samples. Comparison of genomic characteristics of pretreatment 'sensitive' to recurrence 'resistant' tumours to identify the genetics of drug resistance.

  Dataset EGAD00001000707

• The UCSF Low Grade Glioma Genome Project #1

  Dataset EGAD00001000714

• Angiosarcoma whole exome

  Extension of angiosarcoma whole genome sequencing study

  Dataset EGAD00001000722

• Matched tumour/normal .bam files generated by QCMG at University of Queensland from HiSeq whole genome sequencing of oesophageal adenocarcinoma cases

  Dataset EGAD00001000845

• HCC.GNE RNA-Seq

  RNA-Sequencing data (raw read sequences) for 23 samples, from 12 patients, for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma"

  Dataset EGAD00001000886

• Mantle Cell Lymphoma Dataset

  Dataset EGAD00001000667

• Whole exome sequencing of peripheral T-cell lymphoma (PTCL)

  Dataset EGAD00001000659

• Novel driver variants in the histone 3.3 genes, H3F3A and H3F3B, define bone and cartilage cancer sub-types

  A selection of human cancers harbours somatic driver mutations in genes encoding histones, most notably childhood brain tumours with K27M substitutions of the histone 3.3 gene, H3F3A. We performed whole genome sequencing of the benign cartilage tumour, chondroblastoma, and targeted sequencing of histone 3.3 genes, H3F3A and H3F3B, in seven further skeletal tumour types. We identified an exceptionally high prevalence of novel histone 3.3 driver mutations at glycine 34 and at lysine 36. Histone 3.3 gene mutations were found in 91% in giant cell tumours of bone (48/53), mainly H3F3A G34W variants, and in 92% of chondroblastoma (73/79), predominantly K36M mutations in H3F3B. H3F3B is paralogous to the cancer gene H3F3A. However, H3F3B driver variants have not previously been reported in human cancer. Our observation demonstrate remarkable tumour-specificity of mutations, with respect to which histone 3.3 gene and residue is mutated, indicating that the advantage these mutations confer is tumour dependent. Moreover, tumour-specific mutation of H3F3A and H3F3B suggests, that although both genes encode identical proteins, they are likely non-redundant and employed differentially during skeletal development.

  Dataset EGAD00001000646

• Exome sequencing of patients with Ewings sarcoma

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing,s sarcoma tumours.

  Dataset EGAD00001000333

• Somatic mutations, clonal architecture and genomic evolution in multiple myeloma

  Multiple myeloma is an incurable plasma cell malignancy whose molecular pathogenesis is incompletely understood. We used whole exome sequencing, copy number profiling and cytogenetic to analyses 84 samples from 67 patients with myeloma. In addition to known myeloma genes, we identify new candidate genes, including truncations of SP140, ROBO1 and FAT3 and clustered missense mutations in EGR1. We find oncogenic mutations in cancer genes not previously implicated in myeloma, including SF3B1, PI3KCA and PTEN. We define diverse processes contributing to the mutational repertoire, including kataegis and somatic hypermutation. Most cases have at least one cluster of subclonal variants, including subclonal driver mutations, implying on-going tumor evolution. Serial samples revealed diverse patterns of clonal evolution, including linear evolution, differential clonal response and branching evolution. Our findings reveal the myeloma genome to be heterogeneous across patients and, within individual patients, to exhibit diversity in clonal admixture and dynamics in response to therapy.

  Dataset EGAD00001000339

• Frequent mutation of the major cartilage collagen gene, COL2A1, in chondrosarcoma

  Chondrosarcoma (CHS) is a heterogeneous collection of malignant bone tumours and is the second most common primary malignancy of bone after osteosarcoma. Recent work has identified frequent, recurrent mutations in IDH1/2 in nearly half of central CHS. However, there has been little systematic genomic analysis of this tumour type and thus the contribution of other genes is unclear. Here we report comprehensive genomic analyses of 49 cases of CHS. We identified hypermutability of the major cartilage collagen COL2A1 with insertions, deletions and rearrangements identified in 37% of cases. The patterns of mutation were consistent with selection for variants likely to impair normal collagen biosynthesis. In addition we identified mutations in IDH1/2 (59%), TP53 (20%), the RB1 pathway (27%) and hedgehog signaling (22%).

  Dataset EGAD00001000358

• The genomic architecture of mesothelioma

  The genome-wide landscape of somatically acquired mutations in mesothelioma has not been deeply characterised to date, but advances in DNA sequencing technology now allow this to be addressed comprehensively. Harnessing massively parallel DNA sequencing platforms, we will identify somatically acquired point mutations in all coding regions of the genome from patients with mesothelioma. In addition, using paired-end sequencing, we will map copy number changes and genomic rearrangements from the same patients.

  Dataset EGAD00001000360

• Targeted gene fusion sequencing (Fus-seq) in mesothelioma

  This is a small pilot data set to test the feasibility of cDNA exomes across 1200 cancer cell line panel. cDNA exomes or Fus-seq is further explained in this studies Abstract.

  Dataset EGAD00001000361

• A common single nucleotide variant in T is strongly associated with chordoma

  Chordoma is a rare malignant bone tumor that expresses the transcription factor T. We conducted an association study of 40 patients with chordoma and 358 ancestry-matched, unaffected individuals with replication in an independent cohort. Whole-exome and Sanger sequencing of T exons reveals a strong risk association ( allelic odds ratio (OR) = 4.9, P = 3.3x10-11, CI= 2.9-8.1) with the common (minor allelic frequency >5%) non-synonymous SNP rs2305089 in chordoma, which is exceptional in cancer genetics.

  Dataset EGAD00001000226

• Melanoma-TIL Study Exomes

  Melanoma-TIL Study Exomes

  Dataset EGAD00001000243

• Integrative Oncogenomics of multiple myeloma

  Integrative Oncogenomics of multiple myeloma

  Dataset EGAD00001000246

• Integrative Oncogenomics of multiple myeloma

  Integrative Oncogenomics of multiple myeloma

  Dataset EGAD00001000247

• DATA FILES FOR SJRB

  Retinoblastoma whole genome sequencing

  Dataset EGAD00001000261

• Chondrosarcoma Targeted Sequencing Study

  This Study uses a focused bespoke bait pull down library method to target findings of Chondrosarcoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Dataset EGAD00001000265

• Osteosarcoma Targeted Sequencing Study

  This Study uses a focused bespoke bait pull down library method to target findings of Osteosarcoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Dataset EGAD00001000266

• Chordoma Targeted Sequencing Study

  This Study uses a focused bespoke bait pull down library method to target findings of Chordoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Dataset EGAD00001000267

• Pilot study Pilocytic Astrocytoma ICGC PedBrain, whole genome sequencing of 5 tumors and matched blood

  Pilot study Pilocytic Astrocytoma ICGC PedBrain, whole genome sequencing of 5 tumors and matched blood

  Dataset EGAD00001000271

• Meningioma Targeted Sequencing Study

  This Study uses a focused bespoke bait pull down library method to target findings of Meningioma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Dataset EGAD00001000273

• Identifying Novel Fusion Genes in Myeloma

  Identifying Novel Fusion Genes in Myeloma

  Dataset EGAD00001000112

• Osteosarcoma Exome Sequencing

  Osteosarcoma Exome Sequencing

  Dataset EGAD00001000118

• Chordoma Exome Sequencing

  Chordoma Exome Sequencing

  Dataset EGAD00001000119

• DATA_SET_ICGC_PedBrainTumor_Medulloblastoma

  DATA_SET_ICGC_PedBrainTumor_Medulloblastoma

  Dataset EGAD00001000122

• Chondrosarcoma Exome

  Chondrosarcoma Exome

  Dataset EGAD00001000125

• Burden of Disease in Sarcoma

  Burden of Disease in Sarcoma

  Dataset EGAD00001000127

• Genetic landscape of hepatocellular carcinoma

  Genetic landscape of hepatocellular carcinoma

  Dataset EGAD00001000131

• Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Sequence reads for pediatric GBM samples for manuscript: Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Dataset EGAD00001000134

• DATA FILES FOR NBL

  Neuroblastoma whole genome sequencing

  Dataset EGAD00001000135

• Tumor sample of a serious ovarian carcinoma

  Tumor sample of a serious ovarian carcinoma

  Dataset EGAD00001000139

• Blood sample of serious ovarian carcinoma patient

  Blood sample of serious ovarian carcinoma patient

  Dataset EGAD00001000140

• Osteosarcoma Whole Genome

  Osteosarcoma Whole Genome

  Dataset EGAD00001000147

• Subgroup-specific structural variation across 1,000 medulloblastoma genomes

  Subgroup-specific structural variation across 1,000 medulloblastoma genomes

  Dataset EGAD00001000158

• Whole Genome Sequencing accompanying Genetic landscape of pediatric Rhabdomyosarcoma

  Whole Genome Sequencing accompanying Genetic landscape of pediatric Rhabdomyosarcoma.

  Dataset EGAD00001000164

• Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma

  Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma

  Dataset EGAD00001000001

• Osteosarcoma Sequencing

  Osteosarcoma Sequencing

  Dataset EGAD00001000007

• Familial Melanoma Sequencing

  Familial Melanoma Sequencing

  Dataset EGAD00001000016

• ICGC Germany PedBrain Medulloblastoma Pilot_2_LM

  ICGC Germany PedBrain Medulloblastoma Pilot_2_LM

  Dataset EGAD00001000027

• Pancreatic adenocarcinoma QCMG 20110901

  Pancreatic adenocarcinoma QCMG 20110901

  Dataset EGAD00001000049

• UK10K_RARE_COLOBOMA REL-2012-11-27

  UK10K_RARE_COLOBOMA REL-2012-11-27

  Dataset EGAD00001000307

• Whole genome sequencing of matched germline-tumour samples in follicular lymphoma

  Whole genome sequencing analysis was performed on 6 patients within matched germline, follicular lymphoma and transformed follicular lymphoma.

  Dataset EGAD00001000292

• Molecular characterization of invasive lobular carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

  Dataset EGAD00001000288

• Whole genome analyses of the childhood cancer neuroblastoma

  Neuroblastomas are tumors of peripheral sympathetic neurons and are the most common solid tumor in children. To determine the genetic basis for neuroblastoma we performed whole-genome sequencing (6 cases), exome sequencing (16 cases), genome-wide rearrangement analyses (32 cases), and targeted analyses of specific genomic loci (40 cases) using massively parallel sequencing. On average each tumor had 19 somatic alterations in coding genes (range, 3-70). Among genes not previously known to be involved in neuroblastoma, chromosomal deletions and sequence alterations of chromatin remodeling genes, ARID1A and ARID1B, were identified in 8 of 71 tumors (11%) and were associated with early treatment failure and decreased survival. Using tumor-specific structural alterations, we developed an approach to identify rearranged DNA fragments in sera, providing personalized biomarkers for minimal residual disease detection and monitoring. These results highlight dysregulation of chromatin remodeling in pediatric tumorigenesis and provide new approaches for the management of neuroblastoma patients.

  Dataset EGAD00001000282

• SCAT_Osteosarcoma_Validation

  This experiment is to validate putative somatic substitutions and indels identified in an exome screen of ~50 osteosarcoma tumour/normal pairs. It is the first stage in our ICGC commitment to study osteosarcoma. The validation process is an important component of our analysis to clarify the data prior to looking for evidence of new cancer genes, or subverted pathways important in the development of cancer. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000280

• Data set for Whole-genome-Sequencing of adult medulloblastoma

  Data set for Whole-genome-Sequencing of adult medulloblastoma

  Dataset EGAD00001000275

• UK10K_RARE_COLOBOMA REL-2012-07-05

  UK10K_RARE_COLOBOMA REL-2012-07-05

  Dataset EGAD00001000206

• Neuroblastoma samples (Analyses_vcf files)

  Neuroblastoma samples (Analyses_vcf files)

  Dataset EGAD00001000202

• Neuroblastoma samples

  Neuroblastoma samples

  Dataset EGAD00001000196

• UK10K_RARE_COLOBOMA REL-2012-01-13

  UK10K_RARE_COLOBOMA REL-2012-01-13

  Dataset EGAD00001000179

• Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma

  Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma

  Dataset EGAD00001000175

• UK10K_RARE_COLOBOMA REL-2012-02-22

  UK10K_RARE_COLOBOMA REL-2012-02-22

  Dataset EGAD00001000185

• SCAT osteosarcoma sequencing

  SCAT osteosarcoma sequencing

  Dataset EGAD00001000107

• Meningioma Exome

  Meningioma Exome

  Dataset EGAD00001000099

• Pancreatic adenocarcinoma QCMG 20120201

  Pancreatic adenocarcinoma QCMG 20120201

  Dataset EGAD00001000096

• Glioma cell lines rearrangement screen

  Glioma cell lines rearrangement screen

  Dataset EGAD00001000090

• Splenic Marginal Zone Lymphoma with villous lymphocytes exome sequencing

  Splenic Marginal Zone Lymphoma with villous lymphocytes exome sequencing

  Dataset EGAD00001000081

• Integrative Oncogenomics of Multiple Myeloma

  Integrative Oncogenomics of Multiple Myeloma

  Dataset EGAD00001000074

• Kaposi sarcoma exome

  Kaposi sarcoma exome

  Dataset EGAD00001000071