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• Transcriptome atlas of brain organoid developent

  Single-cell Cut&Tag of three histone modifications and chromatin accessibility over a timecourse of brain organoid development from pluripotency. We profiled 5 time points of brain organoid development and 2 time points of retinal organoid development. We used scRNA-seq to profile transcriptome. Library preparation was carried out with the 10x genomics platform.

  Dataset EGAD50000000223

• CMML NGS data collection from Gustave Roussy

  In this dataset are the data from :- 17 patients studied by WGS- 49 patients studied by WES- 9 (/49) patients studied by RNASeq at 2 time points- the same 9 patients studied by ERRBS at 2 time points

  Dataset EGAD00001001853

• To reveal the spectrum of gene mutations in grade II/III gliomas, whole exome sequencing of 52 samples including 4 multi-regional and 10 multi-time points sampling cases and 293 SNP-array were performed.

  To reveal the spectrum of gene mutations in grade II/III gliomas, whole exome sequencing of 52 samples including 4 multi-regional and 10 multi-time points sampling cases and 293 SNP-array were performed. Our analysis revealed high degrees of temporal/spatial heterogeneity generated during tumor expansion and relapse.

  Study EGAS00001001045

• We performed whole-exome sequencing and whole epigenome sequencing (RRBS) of samples collected from different time points during radiotherapy from thirty-four ESCC patients. We compared the genetic and epigenetic features of the different time biopsy samples to reveal the changes in ESCC received radiotherapy.

  We performed whole-exome sequencing and whole epigenome sequencing (RRBS) of samples collected from different time points during radiotherapy from thirty-four ESCC patients. We compared the genetic and epigenetic features of the different time biopsy samples to reveal the changes in ESCC received radiotherapy.

  Study EGAS00001002718

• We performed whole-exome sequencing and whole epigenome sequencing (RRBS) of samples collected from different time points during radiotherapy from thirty-four ESCC patients. We compared the genetic and epigenetic features of the different time biopsy samples to reveal the changes in ESCC received radiotherapy.

  We performed whole-exome sequencing and whole epigenome sequencing (RRBS) of samples collected from different time points during radiotherapy from thirty-four ESCC patients. We compared the genetic and epigenetic features of the different time biopsy samples to reveal the changes in ESCC received radiotherapy.

  Study EGAS00001002719

• Understanding_hematopoietic_stem_cell_mobilization_and_engraftment_

  This study looks at patients undergoing gene therapy for genetic blood and immune disorders, in particular sickle cell disease. From each patient, single blood HSPC colonies are grown from patient blood mononuclear cells, bone marrow mononuclear cells, or CD34+ at multiple time points: pre gene transduction, post-transduction, and post-infusion (at several time points). Whole-genome sequencing will be performed on DNA from these colonies and somatically-acquired mutations will be called. Using these mutations, a phylogeny of these cells can be inferred and further inferences can be made about the gene therapy transduction and engraftment steps.

  Study EGAS00001004620

• The ICGC-TCGA DREAM Somatic Mutation Calling - Tumour Heterogeneity Challenge

  Tumors are composed of many different cell types, ranging from the normal tissue micro-environment, infiltrating immune cells and tumour cells. This group of tumour cells is itself intrinsically highly heterogeneous, driven by the rapid mutation rate of cancer cells to become a mixture of different sub-populations. These different types of cells, called subclones, have different sets of mutations in their DNA. Because some subclones evolve from others, many subclones share mutations. While it is increasingly easy to determine what mutations are present in the tumor, it remains very difficult to determine which subclones have which mutations. The task of assigning mutations to subclones is called subclonal reconstruction.The ICGC-TCGA DREAM Somatic Mutation Calling - Tumour Heterogeneity Challenge (SMC-Het) is an international effort to improve standard methods for subclonal reconstruction: to quantify and genotype each individual cell population present within a tumor. The goal of this challenge is to identify the best subclonal reconstruction algorithms and to identify the conditions that affect their performance.

  Study EGAS00001002092

• Phenotype information

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model in-cluding 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX non-obese diabetic (NOD)-scid IL2Rgnull (NSG) mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either rituximab, cyclophosphamide, doxorubicin, vincris-tine, and prednisone (R-CHOP), CD20-targeted human IFNα2-based AcTaferon combined with CHOP (huCD20-Fc-AFN-CHOP), or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the using the SMARTer Stranded Total RNA-Seq Kit v3.

  Dataset EGAD50000000806

• To reveal the spectrum of gene mutations in grade II/III gliomas, whole exome sequencing of 52 samples including 4 multi-regional and 10 multi-time points sampling cases and 291 SNP-array were performed.

  To reveal the spectrum of gene mutations in grade II/III gliomas, whole exome sequencing of 52 samples including 4 multi-regional and 10 multi-time points sampling cases and 291 SNP-array were performed. Our analysis revealed high degrees of temporal/spatial heterogeneity generated during tumor expansion and relapse.

  Study EGAS00001001044

• Longitudinal RNA-seq (whole blood) in a twin cohort

  The dataset consists of 232 RNA-seq samples (whole blood) obtained from healthy female from the TwinsUK adult registry cohort. The samples were obtained at two time points separated on average by 22 months.

  Study EGAS00001001763

• RNASeq data from one small cell prostate cancer patient (4 samples from 3 time points)

  RNASeq data from one small cell prostate cancer patient - 4 cancer samples (FFPE) from Patient 1 collected at 3 different time points. mRNA was selected using the Magnetic mRNA Isolation Module (NEB) and sequenced on the Illumina NextSeq 500 as 75bp paired end reads (total read length 150bp).

  Dataset EGAD00001011154

• Atezolizumab monotherapy following dCRT indicated a promising cCR rate in patients with unresectable locally advanced esophageal squamous cell carcinoma (EPOC1802)

  The objective is to analyze tumor and normal cell exome sequencing of esophageal cancer patients participating in the Tenergy trial before treatment and RNA sequencing specimens of tumor biopsy specimens at three points before treatment, after radiation chemotherapy, and after atezolizumab administration, in order to search for biomarkers to predict treatment response. Exome sequencing of pretreatment tumor tissue (27 specimens) and normal tissue (27 specimens) from esophageal cancer patients participating in the Tenergy trial, and RNA sequencing of tumor biopsy specimens at three time points before treatment (28 specimens), after radiation chemotherapy (25 specimens) and after atezolizumab administration (25 specimens).

  Study JGAS000708

• "Elucidation of Immune Status and Its Clinical Significance in Patients with Solid Tumors, Including Gastrointestinal Cancers": A Phase II Clinical Trial of Lenvatinib Plus Pembrolizumab in Patients with Advanced Gastric Cancer

  The objective is to analyze tumor and normal cell exome sequencing of gastric cancer patients participating in the EPOC1706 trial before treatment and RNA sequencing specimens of tumor biopsy specimens at two points before treatment and after the combination therapy of Lenvatinib plus pembrolizumab, in order to search for biomarkers to predict treatment response. Exome sequencing from 10 gastric cancer patients participating in the EPOC1706 trial, and RNA sequencing of tumor biopsy specimens at two time points before treatment (9 patients) and after the combination therapy (8 patients) were obtained.

  Study JGAS000894

• This data consists of iPSC derived model systems stimulated with different media.

  This data consists of iPSC derived model systems stimulated with different media (where possible from the top/bottom separately) to provide insight into which more accurately reflects the human gut environment.

  Dataset EGAD50000001918

• Fastq files from target enrichment

  Fastq files generated during target sequencing of 10MB genomic region surrounding top hits in GWAS in a subset of 86 individuals in case families. Paired end sequencing performed on Illumina NextSeq.

  Dataset EGAD00001007801

• Single-cell RNA sequencing reveals cell-type specific eQTLs in peripheral blood mononuclear cells

  This proof-of-concept study shows that single-cell RNA sequencing in ~25,000 peripheral blood mononuclear cells (PBMCs) of 45 donors allows for the identification of cell type-specific cis expression quantitative trait loci effects (cis-eQTLs). Moreover, the significant top-eQTL effects show consistent allelic direction (94%) with previously published whole blood deepSAGE data. These cell type-specific eQTLs may give us additional insight into the downstream consequences of genetic risk factors for immune-mediated diseases.

  Study EGAS00001002560

• Youth-GEMs, the project using data to define the mental health trajectories of young people

  Mental health trajectories are shaped by genetic, cognitive, social, and environmental factors that are particularly influential during human development. How exactly the interplay between these factors is impacting mental health, however, is yet unknown. The project “Gene Environment interactions in Mental health trajectories of Youth (Youth-GEMs)”, funded by the European Commission under the Horizon Europe programme, aims to help reducing mental suffering among European youth. How do Youth-GEMs contribute to bettering mental health in young people? Youth-GEMs aims to identify specific neurological, (epi)genetic and environmental drivers on mental health trajectories of young people. To do so, the project is working on a public knowledge base on functional genomics of the developing human brain, between birth and 24 years old. Reliable predictive models for trajectories of onset and course of mental illness in young people of the general population in Europe will be developed. Additionally, a secure and FAIR data infrastructure in mental health is being produced. Engaging and empowering young people Youth-GEMs is also working on the engagement of young people in the scientific field of Psychiatry. For that, the project is developing initiatives such as Science Café, intended to create a learning community where ideas and stories are shared. The 10th Science Café will take place today, with the participation of Lauren Fromont from the EGA. How do the EGA contribute to Youth-GEMs? The contributions require careful data management and harmonisation: we are dealing with an extraordinary amount of data types, sources, and time points (since the studies are longitudinal). To analyse them together and to determine which factors and interactions are truly key to account for mental health trajectories, the variables need to be transformed in a common “language”, i.e., harmonised under a common data model. Further, to guarantee FAIRness of data storage and sharing for future projects that will further advance our knowledge in the mental health field, we are ensuring that data are processed securely but can also be discovered easily. Find out more information about the project in the Youth-GEMs website.

  Blog youth-gems-mental-health

• Genome analysis of oesophageal cancer and Barrett's oesophagus

  The median survival of oesophageal cancer this year is only 13 to 19 months after diagnosis and more than 90% will die from their disease. Therefore better treatment options are needed. The likelihood of cure for early screen-detected cancers is much higher. Barrett's oesophagus is a pre-cancerous lesion associated with a 30-40 fold increased risk of developing cancer. In an attempt to detect cancer early many patients with Barrett's are enrolled into surveillance programs involving regular endoscopies. A major problem with this approach is that the prevalence of BO in the population is estimated to be around 2%, but most patients with BO will never develop cancer. We are undertaking genomic and/or transcriptomic analysis of oesophageal tumours, Barrett's oesophagus and matched normal samples. The aim is to identify oesophageal-related genomic and transcriptomic alterations, which may reveal mutational process occurring, suggest biomarkers of tumour progression and treatment and identify novel treatment strategies.

  Study EGAS00001002864

• SmMIP-tools:a computational toolset for processing and analysis of single-molecule molecular inversion probes derived data

  Single-molecule molecular inversion probes (smMIPs) provides a modular and cost-effective platform for high-multiplex targeted next-generation sequencing (NGS). Nevertheless, translating the raw smMIP-derived sequencing data into accurate and meaningful information currently requires proficient computational skills and a large amount of computational work, prohibiting wide-scale adoption of smMIP-based technologies. To enable easy, efficient, and accurate interrogation of smMIP-derived data, we developed SmMIP-tools, a computational toolset that combines the critical analytic steps for smMIP data interpretation into a single computational pipeline. Here, we describe in detail two major components of the software. The first is a read processing tool that performs quality control steps, generates read-smMIP linkages and retrieves molecular tags. The second is an error-aware variant caller capable of detecting single nucleotide variants (SNVs) and short insertions and deletions (indels). Using a cell-line DNA dilution series and a cohort of blood cancer patients, we benchmarked SmMIP-tools and evaluated its performance against clinical sequencing reports. We anticipate that SmMIP-tools will increase accessibility to smMIP-technology, enabling cost-effective genetic research to push personalized medicine forward.

  Study EGAS00001005359

• Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia

  Key Points• Multiple mechanisms of acquired CD19 mutations and splicing contribute to CD19 loss and relapse to blinatumomab.• Identification of CD19 ex2part levels represents a new biomarker predictive of resistance or likely failure of blinatumomab

  Study EGAS00001004027

• Identification of Putative Neoantigens in Stage III Melanoma

  This study of three metastatic melanoma patients utilized exome sequencing and RNA sequencing to help identify putative neoantigen peptides that could be further validated by standard immunological assays before design of a personalized vaccine. For each set of neoantigens identified and verified by standard assays, we designed GMP peptides that correspond to the top neoantigens, then used these to condition dendritic cell isolates from each patient. The conditioned dendritic cells were used as the vaccine in three rounds of vaccination, followed by monitoring for T cell memory response to each of the neoantigens.

  Study phs001005

• GWAS for Membranous Nephropathy

  Primary membranous nephropathy (MN) is a rare autoimmune cause of kidney failure. This dataset is from a genome-wide association study (GWAS) designed to identify novel genetic risk loci for MN. The provided cohort (named as European-1 Cohort) is composed of 611 cases of primary MN and 1,246 healthy controls of European ancestry. This cohort was used in the GWAS meta-analysis, as described in the manuscript entitled "Genetic architecture of membranous nephropathy and its potential diagnostic implications" (Nature Communications 2020, in press).The genome-wide summary statistics, including trans-ethnic meta-analysis across 8 GWAS cohorts of European and East Asian ancestry and ethnicity specific meta-analyses, are freely available for download on the Kiryluk lab website: http://www.columbiamedicine.org/divisions/kiryluk/resources.php.

  Study phs001984

• Comprehensive genetic analysis of uveal melanoma heterogeneity during metastatic progression

  Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Despite improvement of diagnosis and treatment of the primary tumor, there is no effective treatment of metastatic disease and approximately half of patients will die within one year or less following metastases detection. Tumor heterogeneity has been proposed as a key factor of drug resistance. However, it has been scarcely studied in UM. The present project aims searching for specific drivers of the metastatic progression, describing the genomic and transcriptomic landscape of metastatic UM, exploring tumor heterogeneity and investigating its role in drug resistance. Thus whole exome sequencing and transcriptomics have been performed on constitutional, primary tumor and metastatic samples from 28 UM patients.

  Dataset EGAD00001004554

• INCLIVA-CC-WES DAC

  Localised colon cancer WES study contaning WBCs, tissue and plasma samples at different time points

  Dac EGAC50000000156

• Combining dasatinib and IFN-α in CML – immunomodulatory effects linked to treatment response and adverse events

  We pooled 100,000 cells from the 12 scRNA+TCRab-seq samples from peripheral blood from three time points (n=4, samples at 0, 3, and 12 months) to understand the landscape of immune subsets in CML during the course of dasatinib+IFN-α treatment

  Study EGAS00001005049