768 results for "se pueden comprar monedas en FC 26 Visité Buyfc26coins.com. ¡Increíble! Jugadores de ensueño ya en mi club..2JSs"

in 13.13 milliseconds.

• Pediatric Whole Genome Sequencing Diagnostic Utility

  The standard of care for first-tier clinical investigation of the etiology of congenital malformations and neurodevelopmental disorders is chromosome microarray analysis (CMA) for copy number variations (CNVs), often followed by gene(s)-specific sequencing searching for smaller insertion-deletions (indels) and single nucleotide variant (SNV) mutations. We compared diagnostic rate of WGS to CMA and targeted gene testing of 100 patients referred to The Hospital for Sick Children Genetics clinic in 2014. WGS identified genetic variants meeting clinical diagnostic criteria in 34% of cases, representing a 4-fold increase in diagnostic rate over CMA (8%) (p-value = 1.42e-05) alone and >2-fold increase in CMA plus targeted gene sequencing (13%) (p-value = 0.0009). WGS identified all rare clinically significant CNVs that were detected by CMA. In an additional 26 patients, WGS revealed indel and missense mutations presenting in a dominant (63%) or a recessive (37%) manner. We found four subjects with mutations in at least two genes associated with distinct genetic disorders, including two cases harboring a pathogenic CNV and SNV. When considering medically actionable secondary findings in addition to primary WGS findings, 38% of patients would benefit from genetic counselling.

  Study EGAS00001001623

• PATL2 is a key actor of oocyte maturation whose invalidation causes infertility in women and mice

  The genetic causes of oocyte meiotic deficiency (OMD), a form of primary infertility characterised by the production of immature oocytes, remain largely unexplored. Using whole exome sequencing, we found that 26% of a cohort of 23 subjects with OMD harboured the same homozygous nonsense pathogenic mutation in PATL2, a gene encoding a putative RNA-binding protein. Using Patl2 knockout mice, we confirmed that PATL2 deficiency disturbs oocyte maturation, since oocytes and zygotes exhibit morphological and developmental defects respectively. PATL2's amphibian orthologue is involved in the regulation of oocyte mRNA as a partner of CPEB. However, Patl2's expression profile throughout oocyte development in mice, alongside colocalisation experiments with Cpeb1, Msy2 and Ddx6 (three oocyte RNA-regulators) suggest an original role for Patl2 in Mammals. Accordingly, transcriptomic analysis of oocytes from WT and Patl2-/- animals demonstrated that in the absence of Patl2, expression levels of a select number of highly relevant genes involved in oocyte maturation and early embryonic development are deregulated. In conclusion, PATL2 is a novel actor of mammalian oocyte maturation whose invalidation causes OMD in humans.

  Study EGAS00001002903

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001009048

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 37 samples was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001010139

• 10X CD4 auto-antigens

  Ex vivo CD4 T-cells from 4 donors were stimulated with antigen-coupled beads to aCD3, ABD, EBNA1, ANO2 or CRYAB and the LiveCD3+CD4+CFSEdim cells were sorted by flow cytometry. Cells were labelled with barcoded antibodies to identify the original stimulus. All stimulations from each donor were pooled into four reactions, i.e. one reaction per donor. Libraries were assembled with the 10X Chromium Next GEM Single Cell 5’ Kit for TCR and transcriptome with feature barcodes. Dataset contains raw fastq reads as well as supplementary information needed to link fastq files to modality, i.e. gene-expression, protein or VDJ, and includes supplementary information to de-multiplex the reactions by stimulation condition.

  Dataset EGAD50000002201

• Chinese Alternating Hemiplegia of Childhood (AHC) Disease Study

  AHC is a rare and severe neurological disorder, and characterized by episodic hemiplegia or quadriplegia attacks, accompanied by other paroxysmal symptoms of oculomotor abnormalities, dystonia, seizures and autonomic disturbances; the age of onset usually occurrs before 18 months of life. Sodium-potassium ATPase alpha3 subunit (ATP1A3) has recently been identified as a causal gene for sporadic AHC by three groups. However, there has not been any large genetic study on a Chinese cohort. In the submitted data, whole-exome sequencing of three trios and three sporadic cases in a Chinese cohort produced an average of 18.8 gigabases of raw sequence. Through our analysis pipeline including BWA mapping, GATK recalibration, variant calling and filtering, all six patients contained missense mutations in ATP1A3 which were further confirmed as de novo mutations. Along with validation in additional patients, this study confirmed ATP1A3 as a causal gene in Chinese AHC patients, and reported six novel mutations.

  Study phs000660

• A Genome-wide Association Study (GWAS) of Risk for Osteosarcoma

  This is a genome-wide association study (GWAS) of osteosarcoma, the most common primary bone malignancy. Osteosarcoma typically occurs in adolescents and young adults. It occurs at increased frequency in several inherited cancer predisposition syndromes but the genetic contribution to sporadic osteosarcoma is largely unexplored. The objective of this study was to identify genetic risk factors for osteosarcoma by conducting a genome-wide association study. We developed collaborations with multiple institutions in order to attain the necessary sample size required to discover novel loci in the genome associated with osteosarcoma using the GWAS approach. Genomic DNA (either blood or buccal in source) derived from osteosarcoma cases was obtained from each participating institution or research group. De-identified blood or buccal cell DNA samples from osteosarcoma cases were derived from existing biobanks at the collaborative institutions. Control subjects were derived from existing NCI cohorts and matched by gender and ethnicity.

  Study phs000734

• Vanderbilt Genome-Electronic Records (VGER) Project: QRS Duration

  An important potential enabling resource for Personalized Medicine is the combination of a DNA repository with Electronic Medical Record (EMR) systems sufficiently robust to provide excellence in clinical care and to serve as resources for analysis of disease susceptibility and therapeutic outcomes across patient populations. The Vanderbilt EMR is a state of the art clinical and research tool (that includes >1.7 million records), and is associated with a DNA repository which has been in development for over 3 years; these are the key components of VGER, the Vanderbilt Genome-Electronic Records project, a part of NHGRI's eMERGE network. The VGER model acquires DNA from discarded blood samples collected from routine patient care, and can link these to de-identified data extracted and readily updated from the EMR. The phenotype we analyze here is the QRS duration on the electrocardiogram, since slow conduction (indicated by longer QRS duration) is a marker of arrhythmia susceptibility.

  Study phs000188

• ALLELE Consortium Glioblastoma Project

  Glioblastoma patient samples were sequenced for this project. The purposes of this project are: (1) to establish an umbrella protocol as a mechanism for identifying patients (in the USA and international sites) who agree to the collection, storage, and broad usage of their specimens and ongoing collection, and review of their medical information for the purposes of minimal-risk research and use of such data in clinical trials on which the patient may enroll; (2) to develop operations that facilitate investigator access to the data and/or tissue to conduct research, while minimizing risks to participants and promoting responsible conduct; and (3) to provide the infrastructure for the sharing of de-identified, coded samples, clinical data, and genomic data between participating investigators and institutions. Eligible patients include patients with known or suspected nervous system tumors or other neurologic diseases. Whole exome sequencing from the stated project will be released under this submission.

  Study phs003000

• Direct genetic transformation bypasses tumor-associated DNA methylation alterations

  Tumors represent dynamically evolving populations of mutant cells, and many advances have been made in understanding the biology of their progression. However, key unresolved questions remain about the conditions that support their initial transformation, which cannot be easily captured in patient populations but are instead modeled using transgenic cellular or animal systems. Here, we used extensive patient atlas data to define common features of the tumor DNA methylation landscape as they compare to healthy human cells and used this benchmark to screen 21 engineered human and mouse models for their ability to reproduce these patterns. Notably, we find that genetically induced cellular transformation can trigger global changes in DNA methylation levels that are consistent with extensive proliferation but rarely recapitulate the widespread de novo methylation of Polycomb targets as found in clinical samples. Our results raise pertinent questions about the relationship between genetic and epigenetic aspects of tumorigenesis and provide an important molecular reference for evaluating existing as well as newer tumor models.

  Study EGAS50000000902

• RNA-seq from human embryonic tissues (additional samples 2018)

  How the genome activates or silences transcriptional programmes governs organ formation. Little is known about this in human post-implantation embryos undermining our ability to benchmark the fidelity of in vitro stem cell differentiation or cell programming, or interpret noncoding variation as potential causes of disease. Here, by studying histone modification we identified genome-wide open chromatin states and active repression across thirteen tissues during human organogenesis. We integrated the data with transcription to build the first view of how promoter states from nearly 20,000 genes differentially regulate alternative organ fates, arguing against bivalency during human organogenesis. The data illustrate tissue-specific as well as complex patterns of enhancer activity functional in zebrafish and impute master transcription factors. Overlaying 739 noncoding de novo mutations in patients allowed phenotypic correlation of developmental disorders to unanticipated target genes. Taken together, the data provide a comprehensive genomic framework for understanding normal and abnormal human development.

  Study EGAS00001003738

• A microRNA-signature that correlates with cognition and is a target against cognitive decline

  While some individuals age without pathological memory impairments, others develop age-associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3-microRNA signature that reflect key processes linked to neural homeostasis and informs about cognitive status. We furthermore provide evidence that expression changes of this signature represent multiple mechanisms de-regulated in the aging and diseased brain and are a suitable target for RNA therapeutics.

  Study EGAS00001005627

• Natural history of clonal haematopoiesis (2017-09-04)

  The incidence of acute myeloid leukemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 60. Only 10-15% of cases evolve from a pre-existing myeloproliferative or myelodysplastic disorder; the remaining cases arise de novo without a detectable prodrome and are diagnosed upon development of bone marrow failure. Analysis of diagnostic blood samples has demonstrated that de novo AML is preceded by the accumulation of somatic mutations in pre-leukemic hematopoietic stem and progenitor cells (preL-HSPCs) that subsequently undergo clonal expansion. If individuals in this pre-leukemic phase could be identified, methods for determination of risk and monitoring for progression to overt AML could be developed. However recurrent AML mutations also accumulate during aging in healthy individuals who never develop AML, referred to as age related clonal hematopoiesis (ARCH). To distinguish individuals with preL-HSPCs at high risk of developing AML from those with ARCH, we undertook deep targeted sequencing of genes recurrently mutated in AML in blood samples from 133 individuals in the European Prospective Investigation into Cancer and Nutrition (EPIC) study taken on average 6 years before they developed AML (pre-AML group), together with 683 matched healthy individuals (Control group). Pre-AML cases displayed accelerated age-correlated accumulation of somatic mutations.The identity, number and variant allele frequency (VAF) of mutations differed between the two groups, and were incorporated into a computational model of AML risk prediction that accurately distinguished pre-AML cases from controls on average 7 years prior to AML development. Our findings provide proof of concept that early prediction of AML development is feasible in high-risk populations, paving the way for early disease detection, monitoring, and potentially prevention.

  Dataset EGAD00001003703

• Privacy Notice for the Account User

  Privacy Notice for EGA User Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org, or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: Name Email address Title/Position Organisation Organisational affiliation Username and password (to authenticate access to the system) IP Address (for anonymous usage statistics) We process your personal data: to provide you with the authenticated access to the EGA service (opening and managing submission and distribution account), to publicly publish some aggregate data to facilitate scientific research (e.g. number of accounts, geographic distribution), to better understand the needs of the users and to guide future improvements of the service, to create anonymous usage statistics. If you do not provide us with your personal data we will not be able to open the user account and offer you our services or we will only provide you a subset of functionalities available within the service. 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data), Requested dataset Data access committee – DAC will have access to the name, email, organization, affiliation, title/position of the distribution user account, using it for their own purpose of granting access to their datasets. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Distribution user account data are in the process of granting access disclosed to dataset(s) DAC, which might be a recipient in countries outside of the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI) is necessary for important reasons of public interest embedded in the aims of the EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union. 6. How long do we keep your personal data? All data are stored for as long as you have the account open. Thereafter the storage is prolonged for as long as our service is live, even if you stop using our services. This prolongation is necessary for further scientific research, to ensure legal compliance and security and to facilitate internal and external audits it they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-user-account

• fragmentomic features of individuals with different cfDNA concentrations

  The uploaded data includes sequencing data of 862 individuals from the nasopharyngeal carcinoma (NPC) screening study. Samples from this cohort were sequenced using targeted sequencing methods for the Epstein Barr Virus (EBV) and selected autosomal DNA, but only ‘off-target’ reads were used for fragmentomic analyses. We have also performed genome-wide (non-targeted sequencing) for 1) Individuals with the highest and lowest cell-free DNA concentration (40 individuals); 2) A subsequent collection of the subjects with the highest and lowest DNA concentrations after six years (26 individuals); 3) 30 cases of pregnancy and 4) 20 patients with hepatocellular carcinoma. All sequencing data are of extracted plasma cfDNA from human subjects. The targeted sequencing samples from 862 individuals were sequenced on the NextSeq500 System (Illumina) and aligned to the EBV genome (AJ507799.2) and the human genome (hg19). The alignments were provided in bam format. The original fastq files of the remaining non-target sequencing samples were provided.

  Dataset EGAD50000000970

• Single cell targeted DNA-sequencing (and antibody sequencing) of high hyperdiploid B-ALL

  This dataset contains all sequencing data of the publication "Single-cell DNA and Surface Protein Characterization of High Hyperdiploid Acute Lymphoblastic Leukemia at Diagnosis and During Treatment". We provide both the raw fastq-files as well as the processed data in the form of .h5 files. There are 13 patients: XJ176, XH135, XJ180, XI145, XI148, XI167, XI150, XJ175, XJ178, XI162, XF98, XG111 and XG115. Of 9 patients, also follow-up samples during/after treatment were sequenced: XJ180, XI145, XI148, XI167, XI150, XJ175, XJ178, XI162 and XG111. To identify the cell types and distinguish between normal and leukemic cells, cell surface proteins were also captured for 6 samples: XF98, XG111 (at diagnosis and during treatment), XG115, XI162 (after treatment) and XJ175 (after treatment). All samples were processed on the MissionBio platform with a custom amplicon panel, and DaB-seq for the combined targeted DNA and protein sequencing.

  Dataset EGAD50000000829

• Metabolic reprogramming towards OXPHOS identifies a novel therapeutic target for mantle cell lymphoma

  Metabolic reprogramming is linked to cancer cell growth and proliferation, metastasis, and therapeutic resistance in a multitude of cancers. Targeting dysregulated metabolic pathways to overcome resistance, an urgent clinical need in all relapsed/refractory cancers, remains difficult. Through genomics analysis of clinical specimens, we show that metabolic reprogramming towards oxidative phosphorylation (OXPHOS) and glutaminolysis is associated with therapeutic resistance to the Bruton’s tyrosine kinase inhibitor ibrutinib in mantle cell lymphoma (MCL), an incurable B-cell lymphoma with poor clinical outcomes. Inhibition of OXPHOS with a novel, clinically applicable small molecule, IACS-010759, which targets complex I of the mitochondrial electron transport chain, results in significant growth inhibition in vitro and in vivo in ibrutinib-resistant patient-derived cancer models. This work suggests that targeting metabolic pathways to subvert therapeutic resistance is a clinically viable approach to treat highly refractory malignancies.

  Dataset EGAD00001004577

• single cell RNA-seq of peripheral blood from analysis in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  This dataset contains two experiments. 1) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with SORT-seq (see cell systems, 2016, doi:10.1016/j.cels.2016.09.002). For some of the patients, multiple indipendent plates were produced (each plate is a sample). Barcode-well correspondence can be found here: https://bitbucket.org/princessmaximacenter/sharq/src/master/data/celseq2_bc384-v4.csv . 2) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with10x Genomics Version 2.

  Dataset EGAD00001007752

• Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

  Somatic mutations of RUNX1, which encodes the myeloid and lymphoid transcriptional factor RUNX1, are common in both B- and T- acute lymphoid leukemia (ALL) and are associated with poor prognosis of T-ALL. However, there has been no comprehensive investigation of the pattern or prevalence of RUNX1 germline mutation in both B- and T-ALL. Here we report germline RUNX1 variants in 1.23% of B-ALL and 2.11% of T-ALL, identifying 31 unique variants in 62 B-ALL and 18 unique variants in 26 T-ALL children. The majority of frameshift and nonsense variants affected RUNX1 function in transcriptional regulation, hematopoiesis, and cellular proliferation. We identified JAK3 as the most frequent somatic mutation in T-ALL with RUNX1 variants. These results not only identify RUNX1 as a leukemia predisposition gene but also further underline the importance of germline genetic variants to the development of ALL

  Dataset EGAD00001007793

• IMCISION RNAseq

  RNA sequencing of 32 primary head and neck squamous cell carcinoma (HNSCC) samples prior to treatment with neoadjuvant anti-PD-1 (n=6) or anti-PD-1 + anti-CTLA-4 (n=26) immunotherapy, and 30 paired on-treatment HNSCC samples (i.e. after neoadjuvant immunotherapy). RNA quantity used: 10ng. Library Preparation Kit: SMART Stranded Total RNA Seq Kit (Takara). Sequencing parameters: NovaSeq 6000, 2x 100 bp. File type: fastQ

  Dataset EGAD00001008127

• Replication data for RNA-SEQUENCING: A RELIABLE TOOL TO UNVEIL TRANSCRIPTIONAL LANDSCAPE OF PAEDIATRIC B-OTHER ACUTE LYMPHOBLASTIC LEUKAEMIA

  This dataset contains the raw data of the RNA-seq experiments described in the paper "RNA-Sequencing: a reliable tool to unveil transcriptional landscape of pediatric B-other acute lymphoblastic leukemia" It contains the raw data from 60 pediatric patients diagnosed with B cell progenitor acute lymphoblastic leukemia lacking the main genetic alterations. RNA material was extracted from bone marrow or periphereal blood and RNA libraries were prepared using Illumina® TruSeq™ stranded mRNA kit following manufacturer's instructions and were sequenced in a NextSeq 550 using a v2 HighOutput 150 cycle kit 2x75bp. Funding: Instituto de Salud Carlos III (ISCIII), PI21/00213 

  Dataset EGAD50000000981

• HV31 - Read identifier list for local CCS, CLR, ONT and MGI reads

  This file contains read identifiers for local CCS, CLR, ONT and MGI reads for each of the eight selected genomic regions (HLA, KIR, IGH, IGK, IGL, TRA, TRD, andTRG). We extracted these reads by aligning whole-genome sequencing data to a draft whole-genome de novo assembly, and selecting reads that map to contigs representing each region. These reads were involved in the polishing and validation of the HV31 assembly. Please refer to the relevant manuscript (https://doi.org/10.1101/2021.02.03.429586) for additional details. Read identifiers are stored in JSON format. Along with the full FASTQ files, this file enables convenient re-analysis of the HV31 sequencing data in the eight selected regions.

  Dataset EGAD00001007761

• Unravelling the contribution of HIF pathway and its therapeutic potential in human AML leukemia-initiating cells

  We performed single cell RNA sequencing (scRNA-seq) from bone marrow on 11 pediatric (0-14 years-old) and adolescent and young adult (AYA) (15-39 years-old) de novo AML samples (Dx) (4 inv(16), 3 t(8;21) and 4 rMLL). In addition, for some patients also relapse sample was sequenced (2 inv(16), 2 t(8;21) and 3 rMLL). Cells were sorted into CD34+/CD38- and CD34-/CD38+ and sequenced separately.

  Dataset EGAD00001008514

• Gabriella Miller Kids First Pediatric Research Program in Germline and Somatic Variants in Myeloid Malignancies in Children

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource).All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed.This project aims to sequence an unparalleled number of cases of de novo Acute Myeloid Leukemia (AML) and Down Syndrome AML (DS-AML), to establish a database comprised of genomic and transcriptome information which can be interrogated for both somatic and germline variants. Identification of the somatic variants will provide valuable data on the potential genes and pathways that can be targeted for therapeutic purposes. In addition, interrogation of the host’s constitutional genome may yield valuable information about potential germline variants that, in combination with the somatic data, might provide a more informed approach to patient care. For those patients with predisposition mutations, chemotherapy alone might not be adequate for cure, and stem cell transplantation might be required. Also, those who might be at high risk of adverse secondary events (cardiac complications, secondary malignancies, etc.) can be identified early and their therapy can be tailored to minimize anticipated complications. Thus, we propose that the optimum outcome can only be obtained through comprehensive interrogation of the somatic and germline genomes to fully annotate the genomic makeup of the leukemia and its host. Knowing the genomic and transcriptomic makeup of these patients, along with a full complement of clinical characteristics for this cohort, will be critical for making strong correlations which may aid in therapeutic development for future patients. The de novo AML, DS-AML, and Acute Promyelocytic Leukemia (APL) cases were all collected through clinical protocols conducted by the Children’s Oncology Group (COG). In addition to funding from the Gabriella Miller Kids First Pediatric Research Program, the DS-AML cohort was specifically funded by the Lifespan to Understand Down syndrome (INCLUDE) Project.

  Study phs002187

• Pancreatic, Small-intestinal and Pulmonary Neuroendocrine Tumors

  Purpose: The primary origin of neuroendocrine tumor metastases can be difficult to determine by histopathology alone, but is critical for therapeutic decision making. DNA methylation-based profiling is now routinely used in the diagnostic workup of brain tumors. This has been enabled by the availability of cost-efficient array-based platforms. We have extended these efforts to augment histopathological diagnosis in neuroendocrine tumors. Experimental Design and Results: We compiled data of 69 small-intestinal, pulmonary, and pancreatic neuroendocrine tumors. These data were used to build a ridge regression calibrated random forest classification algorithm (NEN-ID) that predicts the origin of tumor samples with high accuracy (> 95%). The model was validated during 3x3 nested cross validation and tested in a local (n=26) and external (n=172) cohort. In addition, we show that our diagnostic approach is robust across a range of possible confounding experimental parameters such as tumor purity and array quality. A software infrastructure and online user interface was built to make the model available to the scientific community. Conclusions: This DNA methylation-based prediction model can be used in the workup for patients with neuroendocrine tumors of unknown primary. To facilitate validation and clinical implementation, we provide a user-friendly, publicly available web-based version of NEN-ID.

  Study EGAS00001004878