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• Complex structural variation patterns in pediatric solid tumors

  In this study, we performed systematic characterization of chromoplexy, chromothripsis and extrachromosomal DNA across five types of pediatric solid tumors: neuroblastoma, Ewing sarcoma, Wilms tumor, hepatoblastoma and rhabdomyosarcoma. Almost half of all tumors had at least one complex SV and we identified candidate pathogenic events that affect genes or chromosomal alterations known to be relevant in these cancer types. In conclusion, complex SVs are prevalent and highly pathogenic in pediatric solid tumors.

  Study EGAS00001007565

• cfDNA Methylomes for HCC Detection and Postoperative Monitoring

  To overcome the limitations of current ctDNA-based HCC detection, specifically mutational profiling, we propose quantifying cfDNA methylation levels using cfMeDIP-seq and evaluating its capacity for HCC detection and post-surgery recurrence monitoring. This approach aims to reveal the clonal dynamics of HCC during surgery and upon relapse. Our preliminary data and analyzed results demonstrate that tumor-agnostic cfDNA methylomes can accurately detect HCC and predict recurrence after liver resection or transplantation. This method could have significant implications for the diagnosis, treatment, and monitoring of HCC.

  Study EGAS50000000450

• Development of targeted DNA sequencing panel for brain tumors

  A prompt and reliable molecular diagnosis for brain tumors has become crucial in precision medicine. While Comprehensive Genomic Profiling (CGP) has become feasible, there remains room for enhancement in brain tumor diagnosis due to the partial lack of essential genes and limitations in broad copy number analysis. In addition, the long turnaround time of commercially available CGPs poses an additional obstacle to the timely implementation of results in clinics. To address these challenges, we developed a CGP encompassing 113 genes, genome-wide copy number changes, and MGMT promoter methylation.

  Study EGAS50000000699

• 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

• RNA-seq of longitudinal human blood and nose swab samples from a controlled human infection experiment with SARS-CoV-2 virus

  Controlled human infection experiments enable longitudinal profiling of immune responses to a pathogen. 36 healthy volunteers aged 18-29 years, with no evidence of previous infection or vaccination, were inoculated with SARS-CoV-2 virus and quarantined for 14 days. Blood samples (n=374) for RNA sequencing were collected into PAXgene tubes before virus challenge, 6 hours after challenge, daily thereafter for 14 days and on day 28. Mid-turbinate nose swabs (n=96) for RNA sequencing were collected before virus challenge, and on days 1, 3, 5, 7, 10 and 14 after challenge, preserved in RNAprotect. 18 of 36 participants developed a replicative SARS-CoV-2 infection as evidenced by consecutive PCR-positive swabs for the virus. For every participant, blood RNA from selected days were extracted and depleted for genomic DNA and globin mRNA, before cDNA libraries were constructed using KAPA RNA HyperPrep with RiboErase kits. Libraries were sequenced on the Illumina NovaSeq 6000 platform using NovaSeq 6000 S4 Reagent Kits (200 cycles). Nose swab RNA samples were extracted and depleted for genomic DNA before cDNA libraries were constructed using KAPA mRNA HyperPrep Kits. Libraries were sequenced on the Illumina NextSeq platform the using the NextSeq 500/550 High Output Kit (75 cycles).

  Dataset EGAD50000000942

• 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

• Transcriptome Analysis of Malignant Peripheral Nerve Sheath Tumor-like Melanoma

  Malignant peripheral nerve sheath tumor (MPNST)-like melanoma is a rare malignancy with overlapping characteristics of both neural sarcoma and melanoma. The genomics of MPNST-like melanoma have not been previously described. In this study, we performed whole transcriptome sequencing analysis in 8 samples from 6 patients diagnosed with MPNST-like melanoma. In correlation with deletion ofxa0SERPINB4xa0in all our samples, there was noxa0SERPINB4xa0mRNA expression in our cohort, suggesting a potential tumor-suppressor role of SERPINB4 in MPNST-like melanomas.xa0HRAS, a gene uncommonly mutated in cutaneous melanomas, was mutated in 2 patients, but with no increased mRNA expression.xa0BRAFxa0mRNA expression, resultant from an atypicalxa0BRAFxa0mutation, was increased in association with an inactivatingxa0NF1xa0mutation. Our data demonstrate the role of alternative mechanisms of RAS pathway activation in MPNST-like melanomas and suggest the potential role of other molecular pathways in its carcinogenesis.

  Dataset EGAD00001007000

• Dac for "Altered enhancer-promoter interaction leads to MNX1 expression in pediatric acute myeloid leukemia with t(7;12)(q36;p13)"

  Dac for the data of the manuscript "Altered enhancer-promoter interaction leads to MNX1 expression in pediatric acute myeloid leukemia with t(7;12)(q36;p13)" for Prof. Christoph Plass c.plass@dkfz.de

  Dac EGAC50000000072

• WTCCC case-control study for Autoimmune Thyroid Disease

  WTCCC genome-wide case-control association study for Autoimmune Thyroid Disease (ATD) using the 1958 British Birth Cohort collection as controls.

  Study EGAS00000000020

• Patient-derived conditionally reprogrammed cells (CRCs) were established and characterized to assess their biological properties and to apply these to test the efficacies of drugs.

  RNA seq data was used for the characterization and profiling of the created patient-derived cells and in vivo tissue.

  Study EGAS00001001702

• scRNA-seq from lung cancer organoids and immune cells

  15 scRNA-seq samples were multiplexed, and 5' 10X Chromium scRNA-seq was performed. This dataset provides the FASTQ files for the multiplexed data, as well as the BAM files for the demultiplexed samples.

  Dataset EGAD50000000845

• The Vaginal Microbiome in Reproductive Age Women

  The focus of this cross-sectional study was to characterize the vaginal microbiota of asymptomatic, sexually-active, and reproductive-age women representing four self-reported ethnic groups (White, Black, Asian, and Hispanic). Each woman self-collected two mid-vaginal swabs. The first swab was used to prepare a vaginal smear for Nugent gram stain analysis. The second swab was used for DNA extraction, 16S rRNA gene amplicon sequencing, and detection of Candida albicans. In addition, participants measured vaginal pH and completed a detailed questionnaire on sexual health and behaviors.

  Study phs001909

• Identification_and_functional_validation_of_driver_mutations_in_colorectal_cancer

  Targeted exome sequencing of human colorectal cancers for the identification of novel cancer drivers.

  Study EGAS00001000044

• International Multi-Center ADHD Gene Project (IMAGE) II Case Sample

  This sample represents a collection of cases across a range of sites. All of these samples were ascertained for ADHD with most meeting criteria for combined type ADHD. The collection sites span Europe and America. Further details on the source and inclusion and exclusion information can be found in Neale et al. "Case-Control Genome-Wide Association of Attention-Deficit / Hyperactivity Disorder" J Am Acad Child Adolesc Psychiatry. 2010 September; 49(9): 906-920 PMID20732627. For online access to this manuscript see: PMC2928577.

  Study phs000407

• Diagnosis of pediatric central nervous system tumors using methylation profiling of cfDNA from cerebrospinal fluid

  In this study, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the cell-free DNA in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected 20 cerebrospinal fluid samples of pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. For 11 patients in this study we collected matched tumor DNA. This cohort contains fastQ files of cfRRBS data of these samples.

  Study EGAS50000000377

• Genomewide copy number alteration screening of circulating plasma DNA

  Early cancer diagnosis might improve survival rates. As circulating tumor DNA (ctDNA) carries cancer-specific modifications, it has great potential as a noninvasive biomarker for detection of incipient tumors. We collected cell-free DNA (cfDNA) samples of 1002 elderly without a prior malignancy, carried out whole-genome massive parallel sequencing and scrutinized the mapped sequences for the presence of (sub)chromosomal copy number alterations (CNAs) predictive for a malignancy. When imbalances were detected, 6-monthly clinical follow-up was carried out.

  Study EGAS00001006031

• UK10K NEURO ASD TAMPERE

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The Tampere Autism sample set consists of samples from Finnish subjects with ASD (autism spectrum disorders) with IQs over 70 recruited from a clinical centre for the diagnosis and treatment of children with ASD. For further information on this cohort please contact either Terho Lehtimaki (terho.lehtimaki@uta.fi) or Kaija Puura (kaija.puura@pshp.fi).

  Study EGAS00001000115

• Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA

  Aberrant DNA methylation plays a critical role in tumorigenesis. While DNA methylation has been used for cancer detection and classification, DNA hemi-methylation, a novel epigenetic mark has not been analyzed extensively in cancer epigenomes. Here we report a strand-specific (ss) sequencing method (MeDIP-Seq) for plasma cell free (cf) DNA (sscf-MeDIP-Seq), which can analyze both symmetrically methylated DNA regions (DMRs) as well as hemi-methylated regions (DHMRs). Using the sscf-MeDIP-Seq method, we analyzed plasma cfDNA methylomes of 271 samples from subjects with liver cancer and brain cancer and from individuals without cancer (controls). Among them, 215 samples were chosen as the discovery cohort for the identification of DMRs and DHMRs specific in each subject group and for the training of machine learning models of multi-cancer detection (MCD) using DMRs, DHMRs and DMRs+DHMRs as inputs. These models were then used to predict the 56 samples in the validation cohort. We found that models trained with DMRs+DHMRs as inputs in general outperformed models trained with DMRs or DHMRs alone, with AUROC being 0.971, 0.981, and 0.99 in predicting control, liver and brain cancer samples in the validation cohort, respectively, by the DMR+DHMR-trained models.

  Study phs003462

• Idiopathic Collapsing Glomerulopathy in Brazilian patients

  Collapsing glomerulopathy is a severe kidney disease that often leads to chronic dialysis or kidney transplantation. To expand its understanding, we performed a broad clinical and genetic analysis of a highly admixed patient population with idiopathic collapsing glomerulopathy.

  Study EGAS50000000064

• Whole genome sequencing data of paediatric KMT2A-rearranged acute lymphoblastic leukemia

  Whole genome sequencing data from infant (<1 y) paediatric (< 18 y) KMT2A-rearranged acute lymphoblastic leukemias. Dataset includes fastq and BAM files from diagnostic and remission (control) samples of 3 patients. Dataset consists of two experiments depending on library preparation method; "Experiment 1" is made using normal WGS library preparation (pcr+), and "Experiment 2" is made using pcr-free library preparation method.

  Dataset EGAD50000001568

• Genetics of Microcephalic Osteodysplatics Primordial Dwarfism

  This project aims to find causal variants in 50 patients diagnosed with Microcephalic Osteodysplastic Primordial Dwarfism (MOPD), of presumed recessive inheritance performing whole exome sequencing to ~50x mean depth. This is a collaboration with Prof A. Jackson, MRC Human Genetics Unit, Edinburgh

  Study EGAS00001000064

• Exome and RNA-sequencing data from a relapsed t(1;19) acute lymphoblastic leukemia

  Sequence data is from 4 samples from an adult patient with TCF3-PBX1 t(1;19)-positive acute lymphoblastic leukemia. Exome sequencing was performed on a skin biopsy (normal tissue control) and leukemic bone marrow biopsies taken at diagnosis and at two relapse time points. RNA-sequence data is from leukemic bone marrow from two relapse biopsies.

  Dataset EGAD00001002203

• Dataset for the manuscript of Scywalker: scalable end-to-end data analysis workflow for nanopore single-cell transcriptome sequencing

  Dataset for the manuscript Scywalker: scalable end-to-end data analysis workflow for nanopore single-cell transcriptome sequencing. Contains fastq files for 4 brain samples obtained from short-read NovaSeq 6000 v1.5 Illumina and long-read Oxford Nanopore PromethION sequencing. Single-cell suspensions were generated using 10x Genomics Chromium Next GEM Single Cell 3'Kit v3.1

  Dataset EGAD50000000768

• Epilepsy Genetics Initiative

  The Epilepsy Genetics Initiative (EGI) was created in 2014 with the goal of amassing a database of clinically-generated exome sequence data for patients with epilepsy who have had diagnostic whole exome sequencing. Most of the subjects enrolled in the study did not receive a secure genetic diagnosis from their initial sequencing. Following participant/family consent, EGI transfers raw data from the respective clinical lab to the Institute for Genomic Medicine at Columbia University Medical Center. The strategy of the initiative has been to carry out systematic reanalysis of data to identify new diagnoses that were not possible or missed at the time of initial sequencing and to aid in novel gene discovery in epilepsy.

  Study phs001551

• Baylor Hopkins Center for Mendelian Genomics (BH CMG)

  The Centers for Mendelian Genomics project uses next-generation sequencing and computational approaches to discover the genes and variants that underlie Mendelian conditions. By discovering genes that cause Mendelian conditions, we will expand our understanding of their biology to facilitate diagnosis and new treatments.

  Study phs000711