15130 results for "cancer studies using rna-seq"

in 28.37 milliseconds.

• BLUEPRINT release August 2016, ChIP-Seq for regulatory T cell, on genome GRCh38

  ChIP-Seq data for 2 regulatory T cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002293

• BLUEPRINT release August 2016, ChIP-Seq for Activated B-Cell-Like Diffuse Large B-Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 3 Activated B-Cell-Like Diffuse Large B-Cell Lymphoma sample(s). 12 run(s), 12 experiment(s), 12 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002307

• BLUEPRINT release August 2016, ChIP-Seq for mature neutrophil, on genome GRCh38

  ChIP-Seq data for 10 mature neutrophil sample(s). 105 run(s), 86 experiment(s), 86 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002449

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002512

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002448

• BLUEPRINT release August 2016, ChIP-Seq for CD38-negative naive B cell, on genome GRCh38

  ChIP-Seq data for 9 CD38-negative naive B cell sample(s). 48 run(s), 44 experiment(s), 44 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002524

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_T=6days_LPS_T=4hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_T=6days_LPS_T=4hrs sample(s). 8 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002495

• Tapestri snDNA-seq data along with matched bulk data for validation

  Files from Tapestri snDNA-seq of archival tissue samples from 16 pancreatic ductal adenocarcinoma (PDAC) patients. Matched bulk sequencing (whole-exome, whole-genome, MSK-IMPACT) data are attached for a subset of the patients.

  Dataset EGAD00001009735

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=1hr, on genome GRCh38

  ChIP-Seq data for 2 monocyte - RPMI_LPS_T=1hr sample(s). 8 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002376

• BLUEPRINT release August 2016, ChIP-Seq for class switched memory B cell, on genome GRCh38

  ChIP-Seq data for 3 class switched memory B cell sample(s). 21 run(s), 21 experiment(s), 21 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002430

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days_LPS_T=4hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days_LPS_T=4hrs sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002296

• BLUEPRINT release August 2016, ChIP-Seq for CD4-positive, alpha-beta thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD4-positive, alpha-beta thymocyte sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002386

• BLUEPRINT release August 2016, ChIP-Seq for adult endothelial progenitor cell, on genome GRCh38

  ChIP-Seq data for 2 adult endothelial progenitor cell sample(s). 16 run(s), 14 experiment(s), 14 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002487

• BLUEPRINT release August 2016, ChIP-Seq for endothelial cell of umbilical vein (proliferating), on genome GRCh38

  ChIP-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 14 run(s), 14 experiment(s), 14 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002424

• BLUEPRINT release August 2016, ChIP-Seq for alternatively activated macrophage, on genome GRCh38

  ChIP-Seq data for 7 alternatively activated macrophage sample(s). 50 run(s), 49 experiment(s), 49 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002317

• Comparison of protocols for deriving pancreatic progenitors from hPSCs (ATAC-seq)

  This dataset contains 27 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared ATAC-seq libraries for the 27 samples, and sequenced them on Illumina HiSeq4000.

  Dataset EGAD00001004824

• ATAC-Seq/Hi-C/4C-Seq dataset for Malignant rhabdoid study

  Study describing the dynamics of chromatin organization within malignant rhabdoid tumors. This study describes how this chromatin organization changes upon SMARCB1 rescue within patient-derived organoid models from malignant rhabdoid tumors. Identification of a novel super-enhancer of MYC and identification of patient-specific enhancer utilization to activate MYC expression in these tumors.

  Dataset EGAD00001011820

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - T=10day_RANK_M-CSF, on genome GRCh38

  ChIP-Seq data for 1 monocyte - T=10day_RANK_M-CSF sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002420

• BLUEPRINT release August 2016, ChIP-Seq for naive B cell, on genome GRCh38

  ChIP-Seq data for 15 naive B cell sample(s). 67 run(s), 59 experiment(s), 59 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002466

• BLUEPRINT release August 2016, ChIP-Seq for endothelial cell of umbilical vein (resting), on genome GRCh38

  ChIP-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 13 run(s), 13 experiment(s), 13 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002488

• North Carolina Clinical Genomic Evaluation by NextGen Exome Sequencing (NCGENES)

  North Carolina Clinical Genomic Evaluation by Next-generation Exome Sequencing This study is part of a larger consortium project investigating the validity and best use of next-generation sequencing (in particular, whole exome sequencing, or WES) in clinical care. Participants are patients who were either seen in the UNC Cancer and Adult Genetics Clinic or referred to the study by their physician. They will be approached by their physician or a genetic counselor for recruitment. Once enrolled, a clinical geneticist or genetic counselor will obtain consent and collect blood samples to be analyzed using WES. Results may include information related to a diagnosis and incidental information. Medically actionable incidental findings will be CLIA-certified and returned to participants in a routine genetic counseling session, along with diagnostic findings. Eligible adult participants will be randomized to have the opportunity to choose to get certain types of non-medically actionable incidental findings, as well. Their decisions will be investigated, as will psychosocial and behavioral responses to sequencing and receiving sequencing information. This is a longitudinal, mixed methods study (i.e., multiple assessments pre- and post-return of results, with both quantitative and qualitative methods used to gather data). Because only the quantitative component of the study uses randomization, only measures and procedures associated with that component are included here. The third study release includes data of additional n=189 subjects.

  Study phs000827

• Rituximab-treated lymphoma patients show correlated deficiency in serological and T cell Spike-specific response after SARS-CoV-2 vaccination: insights from the CORSA Study.

  This study is part of the CORSA trial (NCT04345315), a prospective multicentric research project conducted by the Istituto Romagnolo per lo Studio dei Tumori “Dino Amadori” to investigate the immunologic response to mRNA SARS-CoV-2 vaccines in patients with hematologic malignancies (HM) and healthy individuals as controls (HC). The data in this repository refer to two subcohorts: 7 healthy controls and 10 lymphoma patients, randomly selected. Whole blood samples were collected to characterize T cell receptor (TCR) repertoire specificity against SARS-CoV-2 proteins before and after two BNT162b2 vaccination cycles, at baseline (before vaccination), 50 days after the first dose (V1), and 6 months after the first dose (V3). All participants were vaccinated under the Italian national campaign and provided informed consent following the Declaration of Helsinki. We investigated SARS-CoV-2-specific T cell responses through TCR repertoire profiling and examined correlations between serological and cellular responses in both patient and control groups. Using Next-Generation Sequencing (NGS) to characterize the CDR3 sequences of TCR β-chains from peripheral blood, we assessed clonal expansion (depth) and diversification (breadth) of SARS-CoV-2-specific T cell clonotypes over time, aiming to understand how cancer and its treatment influence vaccine-induced immunity in immunocompromised individuals.

  Study EGAS50000001205

• Transposable Elements Shape Stemness in Normal and Leukemic Hematopoiesis

  Despite most acute myeloid leukemia (AML) patients achieving complete remission after induction chemotherapy, two-thirds will relapse with fatal disease within five years. AML is organized as a cellular hierarchy sustained by leukemia stem cells (LSC) at the apex, with LSC properties directly linked to tumor progression, therapy failure, and disease relapse 1–5. Despite the central role of LSC in poor patient outcomes, little is known about the genetic determinants driving their stemness properties. As LSCs share many functional and molecular properties with normal hematopoietic stem cells (HSC) 6, we investigated accessible chromatin unique across normal hematopoietic and cancer cell states and identified transposable elements (TEs) as genetic determinants of both primitive populations in comparison with their downstream mature progeny. A clinically-relevant TE chromatin accessibility-based LSCTE121 signature was developed that enabled patient classification based on survival outcomes. Through functional assays, primitive cell specific-TE subfamilies were found to serve as docking sites for stem cell-associated regulators of genome topology or lineage-specific transcription factors, including LYL1 in LSCs. Finally, using chromatin editing tools, we establish that chromatin accessibility at LTR12C elements in LSCs are necessary to maintain stemness properties. Our work identifies TEs as genetic drivers of primitive versus mature cell states, where distinct TE subfamilies account for stemness properties in normal versus leukemic hematopoietic stem cells.

  Study EGAS50000001141

• Transposable Elements Shape Stemness in Normal and Leukemic Hematopoiesis

  Despite most acute myeloid leukemia (AML) patients achieving complete remission after induction chemotherapy, two-thirds will relapse with fatal disease within five years. AML is organized as a cellular hierarchy sustained by leukemia stem cells (LSC) at the apex, with LSC properties directly linked to tumor progression, therapy failure, and disease relapse 1–5. Despite the central role of LSC in poor patient outcomes, little is known about the genetic determinants driving their stemness properties. As LSCs share many functional and molecular properties with normal hematopoietic stem cells (HSC) 6, we investigated accessible chromatin unique across normal hematopoietic and cancer cell states and identified transposable elements (TEs) as genetic determinants of both primitive populations in comparison with their downstream mature progeny. A clinically-relevant TE chromatin accessibility-based LSCTE121 signature was developed that enabled patient classification based on survival outcomes. Through functional assays, primitive cell specific-TE subfamilies were found to serve as docking sites for stem cell-associated regulators of genome topology or lineage-specific transcription factors, including LYL1 in LSCs. Finally, using chromatin editing tools, we establish that chromatin accessibility at LTR12C elements in LSCs are necessary to maintain stemness properties. Our work identifies TEs as genetic drivers of primitive versus mature cell states, where distinct TE subfamilies account for stemness properties in normal versus leukemic hematopoietic stem cells.

  Study EGAS50000001147

• Genomic characterization of retinoblastoma (targeted sequencing)

  Retinoblastoma is the most frequent intraocular malignancy in children, originating from a maturing cone precursor in the developing retina. Little is known on the molecular basis underlying the biological and clinical behavior of this cancer. Here, using multi-omics data, we demonstrate the existence of two retinoblastoma subtypes. Subtype 1, of earlier onset, includes most of the heritable forms. It harbors few genetic alterations other than the initiating RB1 inactivation and corresponds to differentiated tumors expressing mature cone markers. By contrast, subtype 2 tumors harbor frequent recurrent genetic alterations including MYCN-amplification. They express markers of less differentiated cone together with neuronal/ganglion cell markers with marked inter- and intra-tumor heterogeneity. The cone dedifferentiation in subtype 2 is associated with stemness features including low immune and interferon response, E2F and MYC/MYCN activation and a higher propensity for metastasis. The recognition of these two subtypes, one maintaining a cone-differentiated state, and the other, more aggressive, associated with cone dedifferentiation and expression of neuronal markers, opens up important biological and clinical perspectives for retinoblastomas. In this study, we performed targeted sequencing of the exonic regions of RB1, BCOR and ARID1A on 37 samples from the series of 102 retinoblastomas. Among them, 23 samples were not subjected to whole-exome sequencing, and 14 samples have the whole-exome sequencing data (deposited in EGAS00001005248).

  Study EGAS00001005550

• Complete sequencing dataset of study EGAS00001002795

  Dataset EGAD00001004572

• DAC IBMsnRNAseq

  This DAC manages the data access to our snRNA-seq and spatial transcriptomic data set on healthy and inflamed human skeletal muscle.

  Dac EGAC50000000220

• DLBCL cfDNA seq

  Sequencing dataset of 290 DLBCL and HGBL cfDNA samples of paired end 150bp sequencing runs.

  Dataset EGAD50000000602

• Centroblast Cohort

  miRNA-seq Cohort of 15 Benign Centroblasts

  Dataset EGAD00001001075

• NABEC Exome-Seq

  Exome sequencing of North American Brain Expression Consortium (NABEC) subject.

  Dataset EGAD00001002886

• SAIF Alignment File

  This is the bam file generated after alignment using BWA program for the SAIF genome

  Dataset EGAD00001000249

• CASES_ONLY

  CASE SAMPLES USING QuantStudio 12K Flex Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA, USA)

  Dataset EGAD00010001482

• CONTROLS_ONLY

  CONTROL SAMPLES USING QuantStudio 12K Flex Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA, USA)

  Dataset EGAD00010001481

• PGx validation GSAv3

  Samples genotyped using Illumina Infinium Global Screening Array v3 for assessing pharmacogenomic genes

  Dataset EGAD00010002645

• TSO500 on DNA

  Targeted sequencing using the TruSight Oncology 500 DNA probes panel, on samples 162 and 521

  Dataset EGAD50000000270

• PRECISION WES

  WES dataset obtained using Illumina HiSeq 2500, Swift Bioscience library kit, paired reads.

  Dataset EGAD00001009639

• Whole exome sequencing and RNA sequencing of cervical cancer

  We designed this study to identify molecular markers involved in the development and prognosis of cervical adenocarcinoma. In this study, we would like to elucidate the molecular biological characteristics of cervical adenocarcinoma in relation to the carcinogenesis of other cervical cancers (squamous cell carcinoma), vaginal and vulvar cancers. In addition, some squamous cell carcinomas of the cervix develop at a young age and have a poor prognosis. Furthermore, small cell carcinoma of the cervix also progresses rapidly and has a poor prognosis, making the establishment of diagnostic and therapeutic methods an urgent task.

  Study JGAS000586

• Whole exome sequencing and RNA sequencing of cervical cancer

  We designed this study to identify molecular markers involved in the development and prognosis of cervical adenocarcinoma. In this study, we would like to elucidate the molecular biological characteristics of cervical adenocarcinoma in relation to the carcinogenesis of other cervical cancers (squamous cell carcinoma), vaginal and vulvar cancers. In addition, some squamous cell carcinomas of the cervix develop at a young age and have a poor prognosis. Furthermore, small cell carcinoma of the cervix also progresses rapidly and has a poor prognosis, making the establishment of diagnostic and therapeutic methods an urgent task.

  Study JGAS000582

• single-cell RNA sequencing and RNA sequencing of normal uterine cervix

  We designed this study to identify molecular markers of HPV18 early promoter. In this study, we developed patient-derived organoids from squamous-columular junction of normal uterine cervix and infected HPV18 into those organoids to elucidate the molecular biological characteristics of HPV18-activated cells.

  Study JGAS000640

• Genetic dysregulation of gene expression and splicing during a ten-year period of human aging in the PIVUS study

  We performed RNA sequencing in whole-blood from the same individuals from the PIVUS study at ages 70 and 80 to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging.

  Study EGAS00001003583

• Somatic_evolution_in_the_psoriatic_skin

  We will use laser capture microdissection to dissect groups of a few hundred cells, from which we will isolate and sequence nucleic acids. We aim to whole-genome, whole-exome and RNA sequence the samples in effort to understand the accumulation of somatic mutations in psoriasis and their effect on transcription.

  Study EGAS00001004882

• Single Cell MK and HSC sequencing

  In the current understanding of adult bone marrow hematopoiesis, megakaryocytes (MKs) originate from cells immuno-phenotypically indistinguishable from hematopoietic stem cells (HSCs), bypassing intermediate progenitors. Here, we use single cell RNA sequencing to characterize HSCs and MKs from human bone marrow, to investigate MK lineage commitment and maturation.

  Study EGAS00001004844

• RSV infection of primary bronchial epithelial cells in asthma

  Primary bronchial epithelial cells derived from healthy donors and asthma patients were differentiated in Air-Liquid-Interface condition and infected with the respiratory syncytial virus. Single-cell RNA sequencing analysis of these cultures was used to study the transcriptomic response of the cells to RSV.

  Study EGAS00001007450

• Single-cell RNA sequencing of T-LGLL patients

  Single-cell RNA sequencing was performed on viably frozen cells from 11 T-LGLL samples from 9 T-LGLL patients and 6 age-matched healthy samples. The raw data is available as fastq files.

  Dataset EGAD00001008409

• Combined Telomerase Vaccination and Pembrolizumab in Advanced Melanoma: WES and RNA sequencing of biopsies from a Phase I Trial

  This dataset contains whole-exome and RNA sequencing of biopsies obtained from patients enrolled in a phase I clinical trial investigating the UV1 vaccine in combination with pembrolizumab in patients with advanced melanoma.

  Dataset EGAD00001011074

• Sequencing data for rare tumors and sarcomas

  This dataset contains DNA and RNA sequencing information for AML, Gliomas, brain tumors (medulloblastoma and ependymoma), DIPG, rhabdoid tumors and soft tissue sarcomas. In total 39 samples are present (14 matched normal, 25 tumor samples). Not all samples have matched normals and not all samples have RNA sequencing data..

  Dataset EGAD00001008974

• RNA sequencing of human intra- and extracranial endothelial cells

  This data set contains the raw .fastq files from one RNA-sequencing experiment. Endothelial cells of the basilar artery and endothelial cells of the carotid artery were post-mortem derived with laser microdissection and sequenced. For this analysis both the basilar- and the carotid artery endothelial cells of eleven individuals were sequenced. For more details please see: DMA Hermkens et al. "Profiling the Unique Protective Properties of Intracranial Arterial Endothelial Cells" Acta Neuropathol Commun. 2019 Oct 14; PMID: 31610812.

  Dataset EGAD00001006203

• Reference_DNA_standards_for_GCLP_pipeline

  The use of reference DNA standards generated from cancer cell lines sequenced in the Cancer Genome Project to establish the sensitivity, specificity, accuracy and reproducibility of the WTSI GCLP sequencing pipeline

  Study EGAS00001001173

• cfDNA methylation profiling in Metastatic Cancer and Cancer of Unknown Primary

  This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating cell-free DNA (cfDNA) for 143 patients with metastatic cancer of known type, 41 patients with Cancer of Unknown Primary (CUP) and 27 non-cancer controls.

  Dataset EGAD00001011178

• ICGC PanCancer Analysis of Whole Genomes

  The Pancancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in more than 2,800 cancer whole genomes from the International Cancer Genome Consortium. Building upon previous work which examined cancer coding regions (Cancer Genome Atlas Research Network, The Cancer Genome Atlas Pan-Cancer analysis project, Nat. Genet. 2013 45:1113), this project is exploring the nature and consequences of somatic and germline variations in both coding and non-coding regions, with specific emphasis on cis-regulatory sites, non-coding RNAs, and large-scale structural alterations.

  Study EGAS00001001692