2163 results for "2025年12月10日300883股价走势分析"

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• Early Onset and Progression of Primary Ciliary Dyskinesia Lung Disease Prior to 10 Years of Age

  Primary Ciliary Dyskinesia (PCD) is a genetic defect in airway host-defense, and typically results in chronic infection of the airways. Patients with PCD have chronic lung, sinus and ear infections. This longitudinal study is designed to define the rate of progression of PCD lung function in participants prior to 10 years of age using special lung function tests, which help to track lung impairment and prognosis in other disorders of the airways such as cystic fibrosis. This longitudinal protocol will also systematically track other specific outcomes, including pathogens infecting the airways (assessed by respiratory cultures), and age at onset and progression of airway damage and bronchiectasis [assessed by high-resolution computerized tomography (HRCT) of the chest].

  Study phs001310

• The aim of this project is to identify, on 15 French Caucasian and 10 African-Caribbean men, through an integrative approach of DNA sequencing and transciptomic analyses, relevant genomic events that characterize or allow targeting the various phenotypes of aggressiveness of early stages of prostate cancer.

  Every year about 70,000 new cases of prostate cancer are diagnosed in France and 8,700 men died from this disease. But the incidence and the rate of mortality per 100,000 men in the French West Indies are respectively 1.5x and 2x upper than the rates observed in the metropolitan France. The aim of this project is to identify, on 15 French Caucasian and 10 African-Caribbean men, through an integrative approach of DNA sequencing and transciptomic analyses, relevant genomic events that characterize or allow targeting the various phenotypes of aggressiveness of early stages of prostate cancer.

  Study EGAS00001002176

• minION fastq files of 10 different tumor samples from the Master program (H021)

  Nanopore RNA Sequencing was done for 10 tumor samples. Direct cDNA sequencing was performed using the SQK-DCS109 kit (Oxford Nanopore Technologies). For analysis of a single sample on a MinION flow cell (version R9.4.1), 5 μg RNA was used as input. For multiplexing on a MinION flow cell, 2.5 μg RNA per sample was used as input, and the native barcoding expansion kit EXP-NBD104 was employed in conjunction with SQK-DCS109. After reverse transcription with Maxima H Minus Reverse Transcriptase (Thermo Scientific), second-strand synthesis was performed using the 2x LongAmp Taq Master Mix (New England Biolabs). The resulting double-stranded cDNA was subjected to end-repair and dA-tailing using the NEBNext Ultra End Repair/dA-Tailing Module (New England Biolabs). For multiplexed libraries, this step was followed by barcode ligation and library pooling. Next, libraries were quantified with a Qubit Fluorometer 3.0 (Life Technologies). Finally, sequencing adapters were added to the library preparations and ligated with Blunt/TA Ligase Master Mix (New England Biolabs), followed by further quality control using a Qubit. Samples ACC1 and ACC2 were analyzed on individual MinION flow cells, while the remaining eight samples were sequenced as multiplexed libraries on two MinION flow cells by pooling four samples for each run. Five ACC samples were also analyzed individually on Flongle flow cells

  Dataset EGAD00001008970

• Pilot study Pilocytic Astrocytoma ICGC PedBrain, whole genome sequencing of 5 tumors and matched blood

  Pilot study Pilocytic Astrocytoma ICGC PedBrain, whole genome sequencing of 5 tumors and matched blood

  Dataset EGAD00001000271

• Massachusetts General Hospital Cancer Center DAC for single cell RNA-seq data from small cell lung cancer primary tumors and CTCs

  single cell RNA-seq data from 10 small cell lung cancer primary tumors and circulating tumor cells of three small cell lung cancer patients

  Dac EGAC50000000808

• WGS data for ependymomas (5 tumor-control pairs)

  Whole genome sequencing data for ependymomas (5 tumor-control pairs). See Mack, Witt et al. Nature 506(7489):445-50, 2014 (PMID: 24553142).

  Dataset EGAD00001000950

• Whole genome and whole exome sequencing of mucosal melanomas

  NGS of 10 mucosal melanomas:Whole genome sequencing of 5 mucosal melanomas and matched normal DNAWhole exome sequencing of 5 mucosal melanomas and matched normal DNA

  Dataset EGAD00001000945

• WES and RNAseq data from Clonal driver neoantigen loss under EGFR TKI and immune selection pressures

  WES and RNAseq data from Clonal driver neoantigen loss under EGFR TKI and immune selection pressures

  Dataset EGAD00001015474

• The Environmental Determinants of Diabetes in the Young Study (TEDDY)

  The Environmental Determinants of Diabetes in the Young (TEDDY) Study investigates genetic and genetic-environmental interactions, including gestational infection or other gestational events, childhood infections and other environmental factors after birth, in relation to the development of pre-diabetic islet autoimmunity and type 1 diabetes (T1D). Beginning in 2002, a consortium of six centers assembled to participate in the development and implementation of studies to identify environmental factors that trigger the development of islet autoimmunity and T1D in genetically susceptible individuals. The TEDDY study screened around 400,000 newborns and recruited 7,749 neonates from the general population with a pre-determined T1D risk of 3% and 919 neonates with first degree relatives who have T1D and who have a pre-determined T1D risk of 10%. Thus, TEDDY proposes to follow over 8,000 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) until the age of 15. Participants are followed every three months for islet autoantibody measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive subjects continue to be followed at 3 month intervals and autoantibody negative subjects are followed at six month intervals. In addition to the analysis of autoantibodies, additional data and sample collection is performed at each visit. The parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. DNA extracted from the 9-month TEDDY blood sample was used for SNP genotyping. Samples were available for 7,082 participants. SNPs were genotyped by the Center for Public Health Genomics at the University of Virginia, using the Illumina ImmunoChip SNP microarray of around 196,000 SNPs selected from 186 regions associated with 12 autoimmune diseases (including T1D) (Hadley et al., 2015). "Data quality control (QC) steps included eliminating subjects with a low call rate (> 5% SNPs missing) and discrepancies between reported gender and prior genotyping at the HLA laboratory. Secondly, SNPs were removed from analysis due to low call rate, Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements)" (Törn et al., 2015). QC resulted in a total of 7,023 subjects with data on 176,586 SNPs. Additional information on the TEDDY study are available in the following articles: The Environmental Determinants of Diabetes in the Young (TEDDY) Study. TEDDY Study Group. Annals of the New York Academy of Science, 2008 and TEDDY - The Environmental Determinants of Diabetes in the Young - An Observational Clinical Trial. Annals of the New York Academy of Science, 2006 Details of the TEDDY protocol can be found in The Environmental Determinants of Diabetes in the Young (TEDDY): Genetic Criteria and International Diabetes Risk Screening of 421,000 infants. Pediatric Diabetes, 2011

  Study phs001037

• Whole Genome Sequencing of Waldenstrom's Macroglobulinemia

  Whole genome sequencing was conducted on 10 tumor/germline paired samples along with 20 additional unpaired tumor samples from patients with Waldesntrom's macroglobulinemia. Tumor lymphoplasmacytic lymphoma cells were obtained from CD19+ selected bone marrow mononuclear cells. Germline tissue was obtained from CD19 depleted peripheral blood mononuclear cells. High molecular weight DNA was then submitted for whole genome sequencing with Complete Genomics and aligned to HG19/NCBI human reference build 37.

  Study phs000740

• Blood Gene Signatures Associated with Stiffness After TKA

  In this study, we used PAXgene Blood RNA tubes collected from patients undergoing total knee arthroplasty (TKA) for osteoarthritis. Samples were collected with IRB approval and patient consent. We identified 8 patients with knee stiffness after TKA (cases) and 10 patients without post-TKA stiffness (controls). We isolated RNA from cases and controls for RNA-seq analyses, comparing samples collected the day of surgery and samples collected at 24 hours after surgery.

  Study phs002927

• Comparison Across Multiple Types of Sleep Deprivation

  This study is designed to assess neurobehavioral performance, as well as molecular and physiological changes associated with variations in timing and quantity of sleep. Gene expression changes associated with neurobehavioral (cognitive) performance were assessed in a time-series among individuals randomly assigned to four separate sleep conditions during a 10-day inpatient study: a well-rested control, sleep restriction with nighttime sleep, sleep restriction with daytime sleep to roughly simulate shiftwork schedules, and total (acute) sleep deprivation.

  Study phs003924

• The Heterogeneity Study of HeLa S3 Cells Based on Full-Length Single-Cell RNA-Seq

  In this study, we produced full-length RNA-seq data of 45 single HeLa S3 cells, 8 replicates of 10 pg total RNA and one 5 ng total RNA from HeLa S3 cell population. Using this data, we investigated the heterogeneity of HeLa S3 cells in gene expression, alternative splicing, fusion and HPV-host fusion and expression. This study provides comprehensive transcriptomic characters of HeLa S3 cells at the single cell level.

  Study phs001029

• MOSAIC Window DLBCL Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 10 DLBCL patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001702

• MOSAIC Window Mesothelioma Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 10 Mesothelioma patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001706

• Leiden_melanomafamilies

  Around 10% of patients who present in melanoma clinics have a first degree relative with a previous diagnosis of melanoma. While around 3% have three or more relatives who have been diagnosed with the disease. In this project we will whole genome sequence patients from large Dutch familial melanoma pedigrees to identify mutations in genes that drive melanomagenesis. The identification of these genes will facilitate the management of familial melanoma patients and their families.

  Study EGAS00001000627

• sWGS of Pap test smears from healthy donors and HGSOC patients and matched tumor tissue

  Shallow whole genome sequencing was performed on Pap test smears considering at least 10 M reads per sample. The cohort consists of 77 samples from healthy women, i.e. no tumor diagnosis, and 65 samples from women with a diagnosis of high-grade serous ovarian cancer (HGSOC) taken months or years before diagnosis. 44 primary tumor samples matched to the respective HGSOC patients were sequenced in the same manner as the Pap test smears.

  Study EGAS00001007084

• Congenital Heart Disease in UK Families

  This project aims to identify highly penetrant coding variants increasing the risk of Congenital Heart Disease (CHD) performing whole exome sequencing on DNA samples from 23 affected individuals, selected from 10 families with presumed Autosomal Recessive Inheritance. This is a collaboration with Prof. Eamonn Maher and Dr. Chirag Patel from the Department of Medical and Molecular Genetics, University of Birmingham plans to sequence 23 indexed Agilent whole exome pulldown libraries on 75Bp PE HiSeq (Illumina).

  Study EGAS00001000066

• CML_blast_phase_rearrangement_screen

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from 10 Chronic Myeloid Leukemia in blast phase samples and subjected to a total of two lanes of 50 bp, paired end sequencing on the llumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions

  Study EGAS00001000191

• Whole genome sequencing of patients affected by acute intermittent porphyria

  Acute intermittent porphyria (AIP) is an hereditary rare metabolic disorder of incomplete penetrance, affecting the biosynthesis of heme. IAP is an autosomal dominant disorder, resulting in a substantial reduction of the activity of the hydroxymethylbilane synthase coding gene (HMBS). Most HMBS mutation carriers are asymptomatic and only between 10% and 20% of patients present acute attacks of the associated symptoms. Here, we sequenced whole genomes of 16 AIP patients.

  Study EGAS00001004999

• RNA-sequencing of mechanical stress induced osteoarthritis-like damage in aged human cartilage explants treated with the anti-deiodinase iopanoic acid

  The current study aimed to confirm chondroprotective effects of the D2 inhibitor iopanoic acid (IOP) in an ex vivo aged human osteochondral explant model in which injurious mechanical stress is applied to inflict OA-like damage. This dataset contains RNA-seq (Illumina HiSeq X ten) of osteochondral explant cartilage from aged human patients that underwent a joint replacement surgery due to OA (N=10 donors; n=21 explants).

  Study EGAS00001006242

• Mapping genetic effects on cell type-specific chromatin accessibility using single nucleus ATAC-seq

  Gene regulation is highly cell type-specific and understanding the function of non-coding genetic variants associated with complex traits requires molecular phenotyping at cell type resolution. In this study we performed single nucleus ATAC-seq (snATAC-seq) and genotyping in peripheral blood mononuclear cells from 13 individuals. We mapped chromatin accessibility QTLs (caQTLs) in each immune cell type and sub-type in a subset of 10 samples of European genetic ancestry.

  Study EGAS00001006184

• WGBS data (CancerLocator study) of cell-free DNA derived from human blood

  The blood samples of eight lung cancer patients and one benign lung tumor patient are collected for this dataset. Blood samples were centrifuged first at 1,600 × g for 10 minutes, and then the plasma was transferred into new micro tubes and centrifuged at 16,000 × g for another 10 minutes. The plasma was collected and stored at -80⁰C. CfDNA was extracted from 5 ml plasma using the Qiagen QIAamp Circulating Nucleic Acids Kit and quantified by Qubit 3.0 Fluoromter (Thermo Fisher Scientific). Bisulfite conversion of cfDNA was performed by using EZ-DNA-Methylation-GOLD kit (Zymo Research). After that, Accel-NGS Methy-Seq DNA library kit (Swift Bioscience) was used to prepare the sequencing libraries. The DNA libraries were then sequenced with 150bp paired-end reads.

  Dataset EGAD00001003168

• Sequencing data for oesophageal and related samples - Normals release 3 (RNA)

  Dataset EGAD00001003902

• Sequencing data for oesophageal and related samples - Normals release 4 (RNA)

  Dataset EGAD00001004022

• RNA-seq (raw fastq files)

  RNA-seq data from lumbar spinal cord blocks from 10 ALS samples and Controls. Raw fastq files are provided in this dataset.

  Dataset EGAD50000000833

• High-resolution analysis for urinary DNA jagged ends

  consists 17 cases, 7 control cases and 10 cancer cases.

  Dataset EGAD00001008594

• Deep Sequencing of somatic cancer mutations

  We enriched a panel of cancer associated genes using the Custom Sure Select Target Enrichment Kit. Identified mutations were validated with deep sequencing in order to assess mutated allele frequencies more accurately.

  Dataset EGAD00001001313

• Multi-omics Profiling of Asian Breast Cancers

  186 tumor/normal matched samples from whole exome sequecing and 178 samples (168 tumors, 10 normals) from whole transcriptome sequencing

  Dataset EGAD00001003776

• Long-read amplicon sequencing data per risk gene

  Each gene contains individual nanopore long-read amplicon sequencing FASTQ files for: individual (IND) 01-05 and brain regions: Brodmann Area (BA): 10, 24, 9, 46, caudate (CAUD), cerebellum (CBM) and temporal cortex (TCX).

  Dataset EGAD00001015350

• Sequencing data for "Replication timing alterations are associated with mutation acquisition during tumour evolution in breast and lung cancer"

  Repli-seq data for "Replication timing alterations are associated with mutation acquisition during tumour evolution in breast and lung cancer"

  Dataset EGAD00001015363

• PDX_HTA2.0_Guergen2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) and RCC metastases related to Guergen et al, Front Oncol 12:2022 889789. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.34.0). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 25).

  Dataset EGAD00010002392

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 12)

  The dataset contains whole genome sequencing data of 17 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 46 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000441

• HIV-phyloTSI: PANGEA (PCR amplicon)

  This dataset includes sample numbers TSI_0426 to TSI_0527 for the PANGEA (PCR amplicon) cohort of the study. Samples were generated by pooling four overlapping PCR amplicons (see Gall et al 2012, DOI: 10.1128/JCM.01516-12). The sequencing was conducted using the Illumina NovaSeq system. Each sample has a BAM file, and its associated reference file.

  Dataset EGAD50000001308

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Dataset EGAD50000000263

• Visium Spatial transcriptomics

  This study consists of the spatial transcriptomics data generated by : Visium CytAssist Spatial Gene Expression for FFPE (10x) for steatotic liver disease-associated hepatocellular carcinoma (SLD-HCC) (n=7) and non-SLD-HCC (n=5) The goal of this data is to compare SLD-HCC vs non-SLD-HCC as well as response to immunotherapy

  Dataset EGAD50000001506

• Dataset for GIST-WHOLE_GENOME

  Rare cancer sequencing data of 18 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008876

• Single-cell RNA-seq and spatial transcriptomics data of patients with sarcoidosis

  Single-cell RNA-seq and spatial transcriptomics data for 12 patients with sarcoidosis. From each patient, we analyzed skin biopsies of both lesional and non-lesional skin and we performed spatial transcriptomics for lesional skin samples. The data are provided as aligned BAM files.

  Dataset EGAD00001010020

• RNA-sequencing data from vitamin C experiment

  Fasq-files from 3 unaffected TET2 mutation carriers, 2 mutation carriers diagnosed with lymphoma and 3 family members without TET2 mutation. Time series data collected from 0, 6 and 12 months after daily dose of 1g vitamin C.

  Dataset EGAD00001010009

• PacBio HiFi sequencing of telobait-captured DNA from 68 patients

  PacBio HiFi sequencing was performed on 68 barcoded patients' genomic DNA after a telobait-capture protocol to enrich for telomeric regions. The sequencing reads of each patient were de-multiplexed and presented as patient-specific PacBio CCS BAM files. There are 56 new samples and 12 repeated samples from run 1.

  Dataset EGAD00001009397

• Cancerous Adaptive Dosing Melanoma WGS Dataset

  Illumina NovaSeq 6000 30x WGS of 26 samples, each with up to 5 matched timepoints. Timepoints A,B,C,D,and E correspond to Pretreatment, Week 3, Week 6, Week 9, and Week 12 after treatment, respectively. Additional sample metadata (sample recurrence, treatment course, age, sex, comorbidities, etc.) are present in sample description.

  Dataset EGAD00001010926

• COVID-19 Multiomics Atlas

  We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51).

  Dataset EGAD00001015602

• Genomics of Opioid Pharmacogenomics and Acute/Chronic Postsurgical Pain after Major Surgery in Children

  Pain management after surgery is not optimal, partly due to great interindividual variability in pain perception and coping. This can lead to persistent pain beyond the healing period and disability. Up to two-thirds of the inter-individual variability results from genetic variations in pain perception as well as response to the pain medicine. The investigators aim to identify genomic (genetic/epigenetic), psychological and drug profiles contributing to this variability. Opioids are the mainstay for treatment of postoperative pain in children. Experience dictates that opioids have narrow therapeutic indices and large inter-patient variability in response. This leads to serious side effects like respiratory depression in up to 50% of children undergoing invasive surgery, which can be fatal. It is evident that there are particular children who are more susceptible to suffering side effects and having inadequate pain relief from opioids.It is hypothesized that much of the genetic variability can be explained by gene function which is modulated by a) Single Nucleotide Polymorphisms (SNPs) in genes that encode proteins involved in pain perception, opioid transport/metabolism (pharmacokinetics), and opioid receptor signaling (pharmacodynamics); b) epigenetics which modify gene expression without structural changes to the DNA, and c) genes that influence psychological factors.The purpose of this research study is to identify factors and genes that may be associated with acute and chronic post-surgical pain, and to develop pharmacometric models for response to opioids, like morphine and hydromorphone. While children undergoing different surgeries will be recruited for acute outcomes, children undergoing spine fusion will be followed for 10-12 months for evaluation of psychological and genomic factors affecting chronic post-surgical pain, with a goal of identifying genetic and epigenetic risk models for prediction of acute and chronic post-surgical pain. Although opioids are used every day, some children have bad reactions from their use, like breathing problems, sedation, etc. The investigators want to study factors that may be associated with pain sensitivity, opioid requirements after surgery, their metabolism, efficacy and their side-effects. The investigators expect that the information obtained in this research study will help to develop effective, safer, and tailored treatment options in the future.

  Study phs002105

• CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling

  The study aims to characterize the gut metagenome of Norwegian screening participants and assess the ability of the gut metagenome to identify those at need for colonoscopy. Background: Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current screening methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary screening methods. To aid in the development of a non-invasive screening test with improved sensitivity and specificity, we have initiated a prospective biomarker study (CRCbiome), nested within a large randomized CRC screening trial in Norway. We aim to develop a microbiome-based classification algorithm to identify advanced colorectal lesions in screening participants testing positive for an immunochemical fecal occult blood test (FIT). We will also examine interactions with host factors, diet, lifestyle and prescription drugs. The prospective nature of the study also enables the analysis of changes in the gut microbiome following the removal of precancerous lesions. Methods: The CRCbiome study recruits participants enrolled in the Bowel Cancer Screening in Norway (BCSN) study, a randomized trial initiated in 2012 comparing once-only sigmoidoscopy to repeated biennial FIT, where women and men aged 50–74 years at study entry are invited to participate. Since 2017, participants randomized to FIT screening with a positive test result have been invited to join the CRCbiome study. Self-reported diet, lifestyle and demographic data are collected prior to colonoscopy after the positive FIT-test (baseline). Screening data, including colonoscopy findings are obtained from the BCSN database. Fecal samples for gut microbiome analyses are collected both before and 2 and 12 months after colonoscopy. Samples are analyzed using metagenome sequencing, with taxonomy profiles, and gene and pathway content as primary measures. CRCbiome data will also be linked to national registries to obtain information on prescription histories and cancer relevant outcomes occurring during the 10 year follow-up period. Discussion: The CRCbiome study will increase our understanding of how the gut microbiome, in combination with lifestyle and environmental factors, influences the early stages of colorectal carcinogenesis. This knowledge will be crucial to develop microbiome-based screening tools for CRC. By evaluating biomarker performance in a screening setting, using samples from the target population, the generalizability of the findings to future screening cohorts is likely to be high.

  Study EGAS50000000170

• UK10K_OBESITY_SCOOP

  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 SCOOP samples are part of the Obesity group and will undergo exome sequencing. Severe Childhood Onset Obesity Project (SCOOP) is a sub-cohort of the Genetics Of Obesity Study (GOOS) cohort established by Sadaf Farooqi and Steve O’Rahilly at the University of Cambridge over the last 12 years. The GOOS cohort contains >4,000 patients of diverse geographic origin, many of whom have monogenic and syndromic forms of obesity, and includes patients that are offspring of consanguineous union. SCOOP is a subset of >1500 UK Caucasian patients with severe, early onset obesity (all patients have a BMI Standard Deviation Score (SDS) > 3 and obesity onset before the age of 10 years), in whom all known monogenic causes of obesity have been excluded. GWAS data on the SCOOP cohort will be available (WTCCC2 independent study) at the time of the start of this study. Data from this cohort has demonstrated that the prevalence of the common obesity risk alleles in FTO, MC4R and NEGR1 are amongst the highest within SCOOP, demonstrating its value also in the study of genetic variants with an impact on more common obesity. For further information with regard to this cohort please contact Sadaf Farooqi (isf20@medschl.cam.ac.uk).

  Study EGAS00001000124

• RNA_Seq_in_Patients_with_Primordial_Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000283

• Viral Respiratory Pathogens Genetics

  The overall purpose of this study is to investigate the host genetic factors in response to influenza virus infection, with the focus on influenza vaccination in the first substudy "Adult Influenza Vaccine Genetics" and with the focus on influenza natural infection and other acute respiratory infections (ARIs) in the second substudy "Acute Viral Respiratory Infection Genetics". In the first substudy, healthy adults were enrolled in 2008 (male cohort) and 2010 (female cohort) and immunized with seasonal influenza vaccine. In the second substudy, healthy adults were invited to enroll to be followed for acute respiratory illness through two consecutive influenza seasons 2009-2010 and 2010-2011. Peripheral blood genomic DNA samples were collected from all the subjects, and time-series RNA and serum samples were obtained pre- and post- immunization/infection. Genotyping was carried out on peripheral blood genomic DNA samples using Illumina HumanOmniExpress-12 v1 arrays. Peripheral blood RNA samples obtained at each visit were analyzed using Illumina Human HT-12 (for all the samples) and HiSeq 2000 (for 130 samples in the "Acute Viral Respiratory Infection Genetics" study). Serum specimens were tested using hemagglutination-inhibition (HAI) antibody assay for Influenza H1N1, H3N2, and Influenza B strains. A detailed description of each substudy is provided under their own pages below and via the grouping tool in the right-hand box: phs000635 Adult Influenza Vaccine Genetics phs001031 Acute Viral Respiratory Infection Genetics

  Study phs001030

• Organoid BulkRNAseq

  Here, we aim to understand early determinants of brain organoid quality and generated a set of brain organoids from 12 different hPSC lines using an adaptation of the unguided Lancaster protocol (Lancaster & Knoblich, 2014). All cell lines were obtained from healthy donors. 12 donor hPSC lines were differentiated into brain organoids and a set of 72 individual organoids (6 per line) were randomly selected morphologically diverse organoids and subjected to bulk RNA sequencing for gene expression analysis. RNA was extracted using the RNeasy kit (Qiagen, Germany) according to the manufacturer’s instructions. A total of 1000 ng per sample was sent for RNA sequencing to Azenta Life Sciences (Genewiz Leipzig, Germany) for sequencing. Library preparation was performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina following manufacturer’s instructions (NEB, Ipswich, MA, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End (PE) configuration v1.5 at a depth of >20 million reads in each sample. Raw sequence data (.bcl files) generated from Illumina NovaSeq6000 was converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20. The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014).

  Study EGAS50000000659

• Drug-perturbation-based stratification of blood cancer

  As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.

  Study EGAS00001001746

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 10)

  Whole genome sequencing data of 56 high-grade serous carcinoma (HGSC) patients (208 samples) sequenced with Novoseq 6000

  Dataset EGAD50000000275