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• Immune signature of malignant melanoma in pregnancy

  Melanoma is a highly immunogenic malignancy and there is a deep-rooted notion among clinicians that a probable systemic immunosuppressed state during pregnancy would negatively influence melanoma related prognosis. To test this hypothesis on a more fundamental level, we collected a unique set of melanoma tumor samples and performed RNAseq to draw comparisons between the immune cell infiltrate of pregnant patients and non-pregnant matched controls. We found that there is indeed no differential expression of any immune cell subset. This underscores the notion that the supposed immunosuppressive state of pregnancy does not hamper the anti-tumor immune response.

  Study EGAS50000000492

• A non-canonical lymphoblast in refractory childhood T-cell leukaemia

  Refractory cancers may arise either through the acquisition of resistance mechanisms by cancer cells or represent distinct diseases. The origin of childhood T-cell acute lymphoblastic leukaemia (T-ALL) that does not respond to initial treatment, i.e. refractory disease, is unknown. Refractory T-ALL carries a poor prognosis and cannot be predicted at diagnosis. Here, we performed single cell mRNA sequencing of T-ALL from children who did or did not respond to initial treatment. We identified a transcriptionally distinctive blast population, exhibiting features of innate-like lymphocytes, as the major source of refractory disease.

  Study EGAS50000000767

• Stage-specific gene and transcript dynamics in human male germ cells

  The testis is one of the most transcriptionallyactive organs, however how germ cell differentiation is controlled at the molecular level remains largely unknown. To study global transcriptional dynamics during human spermatogenesis we sequenced total RNA of human testicular biopsies with 5 specific histological phenotypes: Sertoli cell-only (SCO, n=3), spermatogenic arrests at the spermatogonial (SPG, n=4), spermatocyte (SPC, n=3), and spermatid (SPD, n=3) level, as well as normal spermatogenesis (Normal, n=3). To our knowledge, this work provides the most complete capture of the transcriptome and its dynamics during human spermatogenesis to date.

  Study EGAS00001006135

• bulk RNA sequencing, single cell RNA sequencing and nanopore sequencing of T-ALL patients with TCF7-SI1 fusion

  This dataset contains all sequencing data of the publication "Oncogenic cooperation between the TCF7-SPI1 fusion and NRAS(G12D) requires β-catenin activity to drive T-cell acute lymphoblastic leukemia." This is bulk RNA sequencing of 4 T-ALL patients (X09, XB37, XB41 and XB47) of which X09 has a TCF7-SPI1 fusion, single cell RNA sequencing of these 4 patients toghether with a PDX model of the X09 patient and two patients from another cohort (SJTALL030263 and SJTALL031201) which also have a TCF7-SPI1 fusion, and nanopore sequencing of all patients with the TCF7-SPI1 fusion. Moreover these patient samples with the fusion where treated with PKF 118-310, and bulk RNA sequencing was performed in triplicate to determine the differentially expressed genes.

  Dataset EGAD00001007010

• Genetic landscape of inherited retinal dystrophies

  In the context of research, this dataset contains 423 IRD samples; 411 of them analyzed with Clinical Exome Sequencing solutions, and 12 with Whole Exome Sequencing.

  Dataset EGAD00001007022

• Distinct embryonic phylogenies and driver events of infant Wilms tumor - DNA

  Cancers of adults typically arise through progressive rounds of clonal diversification and intratumoral selective sweeps which generate a long mutational trunk with shorter subclonal branches. Here, we investigated whether tumors of young children exhibit the same phylogenetic configuration. We studied three infants, including two newborns, with the childhood kidney cancer, Wilms tumour, through whole genome sequencing of bulk tissues, of single cell derived organoids, and of microdissections. All three cancers exhibited unusual driver events, with tumours of newborns harbouring FOXR2 rearrangements, delineating a distinct variant of Wilms tumour. Phylogenetic analyses suggest that tumors were seeded in an early, possibly confined window of development. Unusually, following seeding there was extensive polyclonal diversification with little evidence of clonal sweeps, leading to a distinct phylogenetic configuration more reminiscent of normal tissues rather than of adult cancers. These findings indicate that some childhood cancers may diversify via unorthodox phylogenetic pathways.

  Dataset EGAD00001009812

• Next Generation Children project

  Whole genome sequencing of sick children in neonatal and paediatric intensive care units, aligned to reference assembly GRCh37.

  Dataset EGAD00001007780

• Somatic pathogenic variants in the normal mammary gland of sporadic breast cancer patients

  This dataset contains .fastq files generated by targeted DNA sequencing of 542 cancer-associated and cadidate genes (52 individuals), and targeted duplex sequencing of PIK3CA and TP53 genes (4 individuals).

  Dataset EGAD00001008327

• A Genome-Wide Association Study of Peripheral Arterial Disease

  The Electronic Medical Record Phenotypes and Community-engaged Genomic Association Study aims to identify genetic variants mediating susceptibility to peripheral arterial disease (PAD). The study leverages a biorepository of blood samples of 1688 PAD cases and 1649 controls, and the electronic medical record (EMR) to annotate the biorepository. PAD cases were identified from the vascular laboratory database as having an ankle brachial index (ABI) <0.9 at rest or after exercise or having non-compressible vessels. Controls were without prior history of atherosclerotic vascular disease and when tested, no evidence of ischemia on a stress test. Phenotypes and environmental exposures including age, ethnicity, demographic and anthropometric data are derived from the Mayo Electronic Medical Record (EMR). Comorbidities were determined using algorithms for diabetes and hypertension based on ICD-9 codes and medication use. Relevant laboratory data, including lipid levels, fasting blood sugar and serum creatinine at index date or within a 1-year window of the index date were extracted. Medication classes at index date were identified using Mayo's Natural Language Processing-based system with RxNorm codification and NDF-RT terminologies mapping. Smoking status was confirmed by natural language processing of clinical notes. Genotyping of ~600,000 SNPs across the genome is being conducted at the Broad Institute using the Illumina 660W platform. Statistical analyses will be conducted to identify genetic variants associated with susceptibility to PAD.

  Study phs000203

• An Advanced Molecular Medicine Case Report of a Rare Human Tumor Using Genomics, Pathomics, and Radiomics

  The associated data of this study is derived from a single female patient with pulmonary sclerosing pneumocytoma (PSP). The aim of this study is to provide the most comprehensive, multi-modality sequencing study of a single case of PSP to-date. To this end, the following sequencing experiments were performed: i) RNA-Seq of the primary tumor and adjacent normal tissues (6 replicates for each tissue type), which was intended to analyze RNA-Seq fusions, gene expression, expression mutations, ii) low-pass DNA whole genome sequencing (WGS) from primary tumor tissue and germline, which was intended to analyze copy number aberrations, and iii) DNA targeted panel sequencing of lung cancer associated genes, using primary tumor tissue and germline from white blood cells, which was intended to analyze somatic mutations. Principal findings: i) the PSP hallmark mutation AKT1 (p.E17K) was detected within both the DNA and RNA, and ii) the TP53 signaling pathway was found to be statistically significant by three different pathway analysis tools of analyzing gene expression and pathway ramifications. Among proteins within the TP53 signaling pathway, the p53 inhibitor encoded by MDM2 was found to be overexpressed (by differential gene expression analysis). The original sequencing data (i.e., FastQ files) from each of the aforementioned samples will be accessible through dbGaP.

  Study phs003154

• Target gene sequencing for human normal endometrial glands

  The raw fastq files target sequencing of 112 genes for 1,298 endometrial glands and matched blood samples. The paired-end sequencing data sets (R1 and R2) are deposited. ABCC1, ACRC, ANK3, ARHGAP35, ARID1A, ARID5B, ATCAY, ATM, ATR, BARD1, BCOR, BRCA1, BRCA2, BRD4, BRIP1, CAMTA1, CDC23, CDYL, CFAP54, CHD4, CHEK1, CHEK2, CTCF, CTNNB1, CUX1, DGKA, DISP2, DYNC2H1, EMSY, FAAP24, FAM135B, FAM175A, FAM65C, FANCA, FANCB, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCI, FANCL, FANCM, FAT1, FAT3, FBN2, FBXW7, FGFR2, FRG1, GPR50, HEATR1, HIST1H4B, HNRNPCL1, HOOK3, KIAA1109, KIF26A, KMT2B, KMT2C, KRAS, LAMA2, LRP1B, MLH1, MON2, MRE11A, MSH2, MSH6, MTOR, NBN, PALB2, PHEX, PIK3CA, PIK3R1, PLXNB2, PLXND1, PMS2, POLE, POLR3B, PPP2R1A, PTEN, PTPN13, RAD50, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54B, RAD54L, RICTOR, SACS, SIGLEC9, SLC19A1, SLX4, SPEG, STT3A, TAF1, TAF2, TAS2R31, TFAP2C, TNC, TONSL, TP53, TTC6, UBA7, VNN1, WT1, XIRP2, ZBED6, ZC3H13, ZFHX3, ZFHX4, ZMYM4.

  Dataset EGAD00001008465

• DKFZ-HIPO Data Access Committee of Heidelberg Center for Personalized Oncology

  Dac EGAC00001000452

• Whole blood RNA-sequencing of covid-19 patients and healthy controls

  This dataset contains whole blood transcriptome data generated from 93 patients with COVID-19 across a range of severities and 23 healthy controls. All patients were PCR positive for SARS-CoV-2 and disease severity ranged from asymptomatic to severe disease requiring ventilation. Individuals without symptoms, or with mild symptoms, were recruited from routine screening of healthcare workers, while COVID-19 patients were recruited at or soon after admission to Addenbrooke’s or Royal Papworth hospitals. Blood samples were taken at recruitment and then again four weeks later. Further details of the cohort and the generation of the RNA-Sequencing data can be obtained from Bergamaschi, L. et al. Longitudinal analysis reveals that delayed bystander CD8+ T cell activation and early immune pathology distinguish severe COVID-19 from mild disease. Immunity 54, 1257-1275 e8 (2021).

  Dataset EGAD00001007776

• Organoid Derivation Project: WGS (2023-06-22)

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

  Dataset EGAD00001011090

• Southern African Prostate Cancer Study (SAPCS) Ethnic Disparity

  The cohort (n=130) consists of prostate cancer patients from South Africa (n=123) and Brazil (n=7). For each patient, a pair of blood and tumour samples were collected. The sequencing data was mapped to hg38 reference. Blood BAMs are named with “-B” as suffix and tumour BAMs are named with “-T” as suffix.

  Dataset EGAD00001009067

• CBD-RAW-SC-GEX: 10X Single-Cell Gene Expression

  Raw Illumina sequencing data and CellRanger BAM output files. For further information regarding this dataset, please contact Stephen Sansom at contact@combat.ox.ac.uk.

  Dataset EGAD00001008007

• Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

  Single-cell RNA-Sequencing of three primary breast cancers, two primary prostate cancers, and a metastatic melanoma sample from Wu et al. (2021) Genome Medicine study. Each tumour was sequenced across different cryopreservation conditions including Fresh Tissue (FT), cryopreserved single-cell suspensions (CCS), cryopreserved solid tissue fragments (CT) and a cryopreserved after overnight cold storage (CO). Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq platform.

  Dataset EGAD00001007030

• Massively parallel nanowell-based single-cell gene expression profiling

  Technological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable. Here we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5184-nanowell-containing microchip to capture ~1300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells. Overall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.

  Study EGAS00001002320

• The evolutionary history of human colitis-associated colorectal cancer

  Inflammatory bowel disease confers an increased lifetime risk of developing colorectal cancer (CRC), and colitis-associated CRC (CA-CRC) is molecularly distinct from sporadic CRC (S-CRC). Here we have dissected the evolutionary history of CA-CRC using multi-region sequencing. Exome sequencing was performed on fresh-frozen multiple regions of carcinoma, adjacent non-cancerous mucosa and blood from 12 CA-CRC patients (n=55 exomes), and key variants were validated with orthogonal methods. Genome-wide copy number profiling was performed using SNP arrays and low-pass whole genome sequencing on archival non-dysplastic mucosa (n=9), low-grade dysplasia (LGD, n=30), high-grade dysplasia (HGD, n=13), mixed LGD/HGD (n=7) and CA-CRC (n=19). Phylogenetic trees were reconstructed, and evolutionary analysis used to reveal the temporal sequence of events leading to CA-CRC. 10/12 tumors were microsatellite stable with a median mutation burden of 3.0 single nucleotide alterations (SNAs) per Mb, around 20% higher than S-CRC (2.5 SNAs/Mb), and consistent with elevated aging-associated mutational processes. Non-dysplastic mucosa had considerable mutation burden (median 47 SNAs), including mutations shared with the neighboring CA-CRC, indicating a pre-cancer mutational field. CA-CRCs were often near-triploid (42%) or near-tetraploid (21%) and phylogenetic analysis revealed that copy number alterations (CNAs) began to accrue in non-dysplastic bowel, but the LGD/HGD transition often involved a punctuated catastrophic CNA increase.

  Study EGAS00001003028

• Whole Genomes Define Concordance in Matched Primary, Xenograft, and Organoid Models of Pancreas Cancer

  Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis of any common solid epithelial tumour. Multiple failed clinical trials necessitate newer approaches to understand the molecular etiology of this disease. Patient-derived xenografts (PDX) and patient-derived organoids (PDO) may serve as pre-clinical disease models; however, characterization remains largely unaddressed at the whole genome level. We conducted a comprehensive assessment of the genetic landscape of tumours and matched PDX and PDO from patients with PDAC. Our data show that PDX and PDO recapitulate PDAC tumourigenesis with respect to simple somatic mutations and copy number changes, and capture major structural variation events.

  Study EGAS00001002597

• Whole Genome Sequencing and Variant Calling for Autism Families

  We extracted DNA from whole blood or lymphoblast-derived cell lines and assessed the DNA quality with PicoGreenTM and gel electrophoresis. Whole genome sequencing was performed (Illumina HiSeq2000 and Illumina HiSeq X). WGS reads were mapped to the human reference genome assembly hg19 (GRCh37) using Burrows-Wheeler Aligner v.0.7.12 (TCAG) or Isaac v.2.0.13 (Macrogen). For each genome, we performed local realignment and quality recalibration and detected SNVs and small indels using GATK Haplotype Caller v.3.4.6 without genotype refinement. We detected CNVs using ERDS (estimation by read depth with single nucleotide variants) and CNVnator. We detected structural variants using Manta v.0.29.6. When available by the variant caller (i.e. GATK and Manta), trio-based joint variant calling was conducted for each family.

  Dataset EGAD00001008452

• RNAseq of GEPARSIXTO

  294 formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer’s protocol (Promega 9FB167). 279 total RNA sequencing libraries were prepared at TGL using a Bravo Automated Liquid-Handling Platform (Agilent G5562A) and the TruSeq Stranded Total RNA Library Prep Gold Kit (Illumina 20020599) following the manufacturer’s protocol (Illumina 1000000040499). RNAseq library quality and quantity were measured using a TapeStation 4200 (Agilent G2991AA) and Qubit 3.0 fluorometer (Life Technologies Q33216), pooled at equal molar ratios, and denatured following the manufacturer’s protocol (Illumina 1000000106351). 271 total RNA sequencing libraries were sequenced at TGL on NovaSeq 6000 (Illumina 20012850) S4 flow cells (Illumina 20028313) following the manufacturer’s protocol (Illumina 1000000019358) using a 2x50 bp paired-end configuration and pool sizes of 91 libraries to target a read depth of 110 million clusters per library on average.

  Dataset EGAD00001010201

• MutWP5: CRUK Mutographs of Cancer: Cancer Mastectomy (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastecomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010117

• Intra-tumor heterogeneity and clonal evolution of papillary renal cell carcinoma

  Limited knowledge of intratumor heterogeneity (ITH), and clonal evolution of papillary renal cell carcinoma (pRCC) and rare kidney tumor subtypes hinders understanding of tumorigenesis and therapeutic efficacy. We conducted an integrative genomic and epigenomic ITH analysis and studied clonal evolutionary history of pRCC and rare kidney tumor subtypes. We dissected multiple consecutive samples from the center of the tumor towards the tumor's periphery, a normal sample ~5 cm distant from the tumor, and, where feasible, metastatic regions in the adrenal gland. Specifically, we performed 60X multi-region whole-genome sequencing (mWGS), both genome-wide methylation and SNP array profiling, and deep targeted sequencing (average 500X coverage) of 254 cancer driver genes (PMID:24390350). The study population comprises 39 patients with kidney cancers, including 23 with papillary type 1 (pRCC1), 12 with papillary type 2 (pRCC2), one of which also had areas of clear cell, and one each with collecting duct tumor (cdRCC), renal fibrosarcoma rSRC, mixed pRCC1/pRCC2, and an unclassified renal cancer with mixed features of pRCC2 and cdRCC. Based on DNA sample availability, we conducted whole genome sequencing (WGS) on 124 samples from 29 subjects, deep targeted sequencing on 139 samples from 38 subjects, SNP array genotyping on 101 samples from 38 subjects, and genome-wide methylation profiling on 139 samples from 28 subjects. All assays were performed on tumor, metastasis and normal tissue samples, with the exception of the SNP array genotyping, which was conducted only on tumor samples.

  Study phs001573

• WES analysis of a mixed cohort of pituitary tumors

  BACKGROUND: Sporadic pituitary adenomas are the second most common primary brain tumor, but their genetics remains incompletely understood. We performed deep DNA sequencing of 42 pituitary macroadenomas, including hormonally active and atypical adenomas. METHODS: Pituitary adenomas representative of a spectrum of histopathologic subtypes, primary and recurrent tumors, and MIB-1 proliferative indices were profiled. Whole-exome sequencing was performed on tumors and paired blood followed by analysis of somatic copy number alteration and mutation. RESULTS: On the whole, the tumors harbored a low rate of mutations, similar to other benign brain tumors. However, almost one-third (29%) exhibited somatic copy-number alterations across large fractions of the genome (up to 99%). Despite such widespread genomic disruption, these tumors had few focal events, which is atypical among highly-disrupted cancers. The other 71% of tumors formed a distinct molecular class, with somatic copy-number alterations involving less than 6% of the genome. Among the highly-disrupted group, 92% were functional or atypical null-cell adenomas, whereas 87% of the less-disrupted group were clinically non-functional adenomas. The only significantly recurrent events were arm-level losses of chromosomes 1, 2, 11, and 18. No significantly recurrent mutations or insertion/deletion events were identified, suggesting no genes are altered by exomic mutations in >15% of pituitary tumors. CONCLUSIONS: Genomic characterization of a large series of sporadic pituitary adenomas reveals two classes of tumor, based on genomic disruption from arm-level copy-number alterations, which associate with hormonal and histologic subtypes.

  Study EGAS00001001714

• GCAT| WGS BAM V1

  This dataset include BAM files of 808 samples from GCAT cohort. Technology used HiSeq 4000, read length 150 bp, inner mate distance 300 bp. For each sample the paired -ends are generated in separated files. Each FASTQ is splitted in multiple LANEs and grouped by the Multiplex index.

  Dataset EGAD00001008202

• Molecular Genetics of Heroin Dependence in China

  Our principal goal was to determine the chromosomal locations of genetic variations associated with increased vulnerability to heroin dependence. This goal was attained by identifying specific DNA markers that are genetically linked to heroin dependence. We collected blood and diagnostic information (using a structured diagnostic interview) from 1230 people (sib-pairs) having DSM-IV defined heroin dependence as well as from their parents and other affected and unaffected siblings, when possible. Genotype and clinical data was archived using database software. We conducted a multipoint linkage analysis using the guidelines of Lander and Kruglyak to assert statistical significance, and followed up on regions of interest with a dense set of markers to evaluate candidate genes.

  Study phs001213

• Phenotyping and Therapeutic Approaches for Patients with Sellar/Suprasellar Disorders

  The goal of the study is to phenotype and genotype patients with rare hypothalamic and pituitary disorders and identify biomarkers of disease diagnosis, presentation, and progression. We are investigating genetic mechanisms of pituitary tumorigenesis as well as genomic/transcriptomic markers of disease presentation and severity. Patients with suspected or confirmed hypothalamic and/or pituitary disorders and their family members are recruited. Biospecimens including peripheral blood, urine, tumor tissue (as available), and/or stool are collected. Genetic analysis may include a variety of techniques including peripheral blood or tumor tissue targeted Sanger sequencing of one or few genes, peripheral blood or tumor tissue whole exome sequencing, and other as applicable.

  Study phs003245

• Team

  The Team Mallory Freeberg Roderic Guigó Arcadi Navarro Helen Parkinson Jordi Rambla Ana T. Alonso Silvia Bahena Àlex Bedmar Kenneth Buckley Aldar Cabrelles Ángel Carreño Marcos Casado Giulia Cellerino Amy Curwin Teresa D'Altri Abeer Fadda Teresa Garcia Sara Gregorio Max Fischer Bela Juhasz Oriol Lopez-Doriga Mireia Marin Óscar Martínez Andrea Mero Akiris Moctezuma Aurora Moreno Liina Nagirnaja Francesc de Puig Santiago Rensonnet Gabriele Rinck Aravind Sankar Andres Silva Coline Thomas Sabela de la Torre Gemma Vicente The EGA Team at the CRG co-manages the European Genome and phenome Archive together with the EGA Team at the European Bioinformatics Institute. In addition to maintaining and distributing data, we enrich the contents of the EGA contributing with our knowledge about genomics and the relationship between genomes and phenomes. Previous Team Members Alexander Vikhorev Jeff Almeida-King Mario Alberich Sergi Aguilo Pablo Arce Minjie Ding Alfred Gil Leslie Glass Jag Kandasamy Vasudev Kumanduri llkka Lapalainen Audald Lloret i Villas Sira Martinez Anand Mohan Dietmar Orth Justin Paschall Saif Ur Rehman Gary Saunders Thomas Smith Ashutosh Shimpi Marc Sitges Dhvani Solanki Giselle Kerry Nino Spataro Dylan Spalding Matthieu Vizuete-Forster Cristina Yenyxe Gonzalez Garcia Paul Flicek Anna Foix Emilio Garcia Rios Jorge Izquierdo Roberto Ariosa Marta Ferri Peradalta Daniel Barrowdale Babita Singh Umuthan Uyan Aleix Canalda Dona Shaju Mauricio Moldes Carles Garcia Frédéric Haziza Alegria Aclan Lauren Fromont Alvis Brazma Marta Huertas Arnau Soler Gemma Milla Claudia Vasallo Aina Jené Csaba Halmagyi Raül Garcia Thomas Keane Mei Gascón

  Documentation about/team

• Solve RD data - Short-Read Whole-Genome Sequencing, raw data, tuh-kounap_group samples

  Solve-RD SR-WGS data generated for 3 samples provided by the group tuh-kounap

  Dataset EGAD00001015514

• RNA-seq data from 224 advanced prostate tumors generated by the West Coast Dream Team

  224 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node.

  Dataset EGAD00001008487

• WGS of HSPC clones of healthy individual sequenced with Illumina NovaSeq 6000

  Dataset contains WGS sequecing data from clonally expanded hematopoietic stem cells from 7 individual pediatric cancer patients. Samples were taken before (DX - diagnosis) or Follow-up (DX2/REM/FU - Diagnosis 2, remission or follow-up, respectively). In addtion, cord blood clones (Designated CB) treated with X-ray radiation, Cisplatin, Maphosphamide, Vincristine and Doxorubicin and untreated cord blood hematopoietic stem/progenitor cells were have been whole-genome sequenced. (Abbreviations RAD, CISPL, MAPH, VINC, DOX and CTRL, respectively)

  Dataset EGAD00001007078

• Whole genome sequencing delineates regulatory and other genic variants in early onset cardiomyopathy

  Whole genome sequencing of 209 pediatric probands with primary cardiomyopathy and their family members. All samples were sequenced using Illumina short read platform.

  Dataset EGAD00001008477

• RNA-seq data from 164 advanced prostate tumors generated by the West Coast Dream Team including 42 paired samles

  164 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node. 42 pairs prior to enzalutamide treatment and at progression from 21 patients are included.

  Dataset EGAD00001009065

• NuGen Targeted Sequencing of 574 DLBCL Cases of Non-China Cohort from Phoenix Clinical Trial

  NuGen 99-Gene-Panel Targeted Sequencing of 574 DLBCL Cases of Non-China Cohort from Phoenix Clinical Trial. Check the Associated Publication for More Experimental Details.

  Dataset EGAD00001008132

• Application of high-throughput, high-depth, targeted single-nucleus DNA sequencing in pancreatic cancer

  Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimized a highly automated nuclei extraction workflow that achieved fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma (PDAC) patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals novel genomic evolution patterns of PDAC as well.

  Study EGAS00001006024

• sWGS of core biopsies from localized breast cancer patients

  Paired end shallow whole genome sequencing (sWGS) data for the identification of genomewide somatic copy number alterations (SCNA) and the estimation of tumor fractions.

  Dataset EGAD00001008397

• META-PRISM

  A pan-cancer cohort of 1031 patients resistant to systemic therapies or with no approved therapeutic options. It includes whole-exome sequencing of 571 tumor and matched-normal samples, and transcriptome sequencing of 947 tumor samples. Biopsies were taken at entry into precision medicine trials, often after diagnosed resistance. Comprehensive clinical information is available for all patients and include patient age at biospy, tumor primary site and histological subtype, biopsy site, treatments received prior to biopsy, blood assessment results at biopsy, metastatic sites at biopsy, and survival time from the biopsy date.

  Dataset EGAD00001009684

• RNA, ATAC, ChIP datasets from Ankylosing Spondylitis patients and Healthy Controls

  This dataset consists of functional genomic data from 20 Ankylosing Spondylitis patients and 35 Healthy Controls taken from CD4+ T cells, CD8+ T cells and CD14 Monocytes. It contains 364 paired end fastq files consisting of 104 total RNA-seq samples and 116 ATAC samples, for ChIP there are 46 H3K4me3 samples, 46 H3K27ac samples and 3 H3K4me1 samples, along with 49 paired input samples. The samples were sequenced on Illumina HiSeq4000, Illumina NextSeq500 and Illumina NovaSeq 6000 platforms.

  Dataset EGAD00001008758

• Whole-exome sequencing of meningiomas for integrative molecular classification.

  Exome libraries were prepared using 100ng DNA of tumor tissue or matched normal DNA. Exome capture was performed using Agilent SureSelect Human Exome Library Preparation V5 or V6 COSIMC + kits.

  Dataset EGAD00001007051

• Mutation analysis of core biopsies from localized breast cancer patients

  Targeted next-generation sequencing (NGS) of 93 frequently mutated genes in breast cancer using the QIAseq Human Breast Cancer Targeted Panel (QIAGEN), which uses digital sequencing by incorporating unique molecular barcodes (UMI).

  Dataset EGAD00001008396

• MGHBoston_Molpheno_Closed

  This dataset contains Whole Genome Sequencing and, if available, RNA-sequencing and/or ATAC-sequencing data of 17 lymphoblastoid cell lines derived from patients with complex genomic rearrangements. Patients have phenotypes in category of intellectual disability and/or multiple congenital anomalies. Data access is closed.

  Dataset EGAD00001004866

• Longitudinal Study of Fluoride and Other Factors Related to Dental Fluorosis, Dental Caries, and Bone Health

  This project is a combination of the Iowa Fluoride Study and the Iowa Bone Development Study from 1992 - 2019. The Iowa Fluoride Study (IFS) began in 1992 with recruitment of 1,882 mothers of newborns from eight Iowa hospital post-partum wards from March 1992 to February 1995. The focus of the IFS was to collect detailed fluoride, general dietary intake, and other data several times per year from age 6 weeks on and relate them to dental fluorosis and dental caries (cavities). Data collection occurred 3-5 times per year initially, and then twice per year after ~ age 4. Dental exams of the primary (baby) teeth were initiated at ~ age 5.The Iowa Bone Development Study (IBDS) grew out of the IFS in 1998 when we added a "normal bone development" focus, and soon after the age 5 dental exams, we began to collect genetic samples and accelerometry (motion sensor) data. All then-active parents of IFS-participating children were invited to have their child join the IBDS, and the majority agreed to do so. The majority of participating children received both ~ age 5 dental exams and bone densitometry assessments. The bone densitometry at age 5 was determined by dual-energy X-ray absorptiometry (DXA) of the hip, lumbar spine, and whole body.Dental exams for caries and fluorosis were performed again at age 8-9, along with DXA bone scans and accelerometry. DXA scans and accelerometry were performed again at ages 11 and 15 years, along with peripheral quantitative computed tomography (pQCT) scans of the distal tibia and radius, but no dental exams were performed.At ages 13 and 17, dental exams, DXA and pQCT scans, as well as accelerometry, were obtained.At age 19, no dental exams were conducted, but repeat DXA and pQCT scans and accelerometry were obtained, along with multi-slice detector CT (MDCT) of the distal tibia.At age 23, we conducted the final wave of exams, which included dental, DXA, pQCT, MDCT, and accelerometry assessments.In addition, parents were invited to participate once with DXA bone scans and to also provide limited questionnaire data about their own fluoride and dietary exposures and physical activity.Note: Please refer to the document Iowa Fluoride Study/Iowa Bone Development Study (IFS/IBDS) - dbGaP Data Tables: A User's Guide - Version 2.0 for a detailed reference manual on all of the clinical data submitted for this project.Note: No genetic data or specimens were submitted with this study. However, many of the child/parent participants in the study were genotyped. These genotyping data are linked to dbGaP Study Accession: phs000095 under Dr. Mary Marazita: "Dental Caries: Whole Genome Association and Gene X Environment Studies".<img style="width: 1155px;" 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

  Study phs002203

• Preeclampsia InterPregGen Consortium: Large-scale GWAS meta-analysis of maternal preclampsia cases and controls from Europe and Central Asia. Plus extension of earlier European fetal preeclampsia GWAS meta-analysis (see EGAS00001001048) by adding Central Asian fetal preeclampsia cases and controls. Datasets provided under this study are GWAS meta-analysis summary statistics and individual level GWAS genotype data. Related InterPregGen Consortium data are also provided under studies EGAS00001000416 and EGAS00001000417 (whole genome sequence data for 100 unrelated Uzbeks and 100 unrelated Kazakhs) and EGAS00001001048 (European fetal preeclampsia GWAS summary statistics and genotype data

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. The EGAS00001001266 study includes two components the FP7 InterPregGen project: (a) GWAS case-control meta-analysis of maternal PE cases from Europe (UK, Iceland, Norway, Denmark, Finland) and Central Asia (Kazakhstan, Uzbekistan); (b) GWAS case-control meta-analysis of PE fetal (baby) cases from Europe (UK, Iceland, Norway, Denmark) and Central Asia (Kazakhstan, Uzbekistan)

  Study EGAS00001001266

• ANGIOPREDICT - an FP7-funded project enabling personalised medicine for patients with metastatic colorectal cancer.

  Exome (*_{N,T}{1,2}) RNAseq (polyA - *_PolyA, and RiboZero - *_RibZ) Methylation (SeqCapEpi - MAPD*).

  Dataset EGAD00001008463

• Solve-RD_EuroNMD_cohort-1_DF1+2_V1

  Solve-RD data submitted to the ERN-EuroNMD cohort for re-analysis (Data freeze 1+2) v1

  Dataset EGAD00001009768

• A body map of somatic mutagenesis in morphologically normal human tissues

  This dataset contained raw sequencing fastq data of the article "A body map of somatic mutagenesis in morphologically normal human tissues". We sampled morphologically normal tissue biopsies from 5 donors. We performed low-depth WGS on 1,764 samples, high-depth WGS on 48 samples and WES on 1,772 samples.

  Dataset EGAD00001007859

• Integrated genomic analysis identifies driver genes and cisplatin-resistant progenitor phenotype in pediatric liver cancer

  Dataset EGAD00001007858

• National Cancer Institute (NCI) Study of Lung Cancer and Smoking Phenotypes in African-American Cases and Controls

  This is a two-stage case-control study designed to evaluate the association between common genetic variants and the risk of lung cancer. The stage 1 studies included 1737 cases and 3602 controls from the following studies: MD Anderson Lung Cancer Epidemiology Study, The Multiethnic Cohort Study (MEC), NCI-MD Lung Cancer-Case Control Study, Northern California Lung Cancer Study, Project CHURCH (Creating a Higher Understanding of Cancer Research &#948; Community Health), Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), Southern Community Cohort Study (SCCS), and the Karmanos Cancer Institute at Wayne State University (KCI/WSU). The stage 2 studies included an independent set of 866 cases and 796 controls from the following studies: The Black Women&#39;s Health Study (BWHS), The Harvard-MGH Lung Cancer Susceptibility Study (HLCS), MD Anderson Lung Cancer Epidemiology Study, MD Anderson/LBJ Hospital Biorepository, NCI-MD Lung Cancer Case-Control Study, Northern California Lung Cancer Study, Philadelphia Lung Cancer Study on Gene Environment Interactions (Plus-Gene), Southern Community Cohort Study (SCCS), and KCI/WSU.

  Study phs001210

• Whole-genome sequencing of gastric cancer 81 samples in the Japanese population.

  Genomic DNA of 81 cases from Japanese gastric cancer was extracted from tumor and matched normal tissues, and libraries with an insert size of 350–550 bp were prepared. The libraries were sequenced on a HiSeq 2500 instrument (Illumina) with paired-end reads of 101 bp. The read data are stored as FASTQ formatted files.

  Dataset EGAD00001008610