6365 results for "11+1双色球多少钱一注"

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• Reference epigenome Fat-adipocyte04 h3k27me3 ChIP-Seq data generated from KEP study

  Fat-adipocyte04 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007479

• Reference epigenome Fat-adipocyte04 h3k36me3 ChIP-Seq data generated from KEP study

  Fat-adipocyte04 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007480

• Reference epigenome Fat-adipocyte04 h3k4me3 ChIP-Seq data generated from KEP study

  Fat-adipocyte04 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007482

• Reference epigenome Fat-adipocyte05 h3k9me3 ChIP-Seq data generated from KEP study

  Fat-adipocyte05 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007490

• Raw count matrix for 418 baseline samples

  Count matrix from 418 pre-treatment (Ven-Obi or Clb-Obi) CD19+ B cells

  Dataset EGAD00001009501

• SF10679

  SF10679 snATAC Seq. Oligodendroglioma, Anaplastic (WHO gr. 3). Tumor Location: Frontal Age: 43. Sex: Male.

  Dataset EGAD00001006312

• OV2295-052021 dataset

  OV2295-052021 dataset

  Dataset EGAD00001007756

• Reference epigenome KNIH006 WGBS data generated from KEP study

  A KNIH006 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for beta cells

  Dataset EGAD00001002754

• Reference epigenome KNIH007 WGBS data generated from KEP study

  A KNIH007 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for adipocytes

  Dataset EGAD00001002755

• OT2_Illumina_WXS_MET_CELL

  Whole-exome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample (OT2_cohort)

  Dataset EGAD00001003380

• Hi-C of cohesin-mutated and wildtype adult AMLs

  High-throughput chromosome conformation capture (Hi-C) data generated for cohesin-mutated (STAG2 or RAD21) and cohesin-wildtype AMLs.

  Dataset EGAD00001011198

• ONT Minion reads for a patient with ataxia-pancytopenia syndrome.

  ONT Minion reads to provide 30x coverage for a patient with ataxia-pancytopenia syndrome.

  Dataset EGAD00001005022

• DLP+ Single Cell Genomic Library A98167

  DLP+ Single Cell Genomic Library A98167 for Diffuse large B-cell lymphoma patient sample TFRIPAIR4_DLBCL

  Dataset EGAD00001010249

• Reference epigenome Kidney-Podocyte01 h3k4me3 ChIP-Seq data generated from KEP study

  Kidney-Podocyte01 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007232

• Reference epigenome Kidney-Podocyte01 input ChIP-Seq data generated from KEP study

  Kidney-Podocyte01 input ChIP-Seq paired end data

  Dataset EGAD00001007234

• Reference epigenome ADMSC01_smRNA-Seq data generated from KEP study

  A ADMSC01_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003867

• Reference epigenome Fat-adipocyte03 input ChIP-Seq data generated from KEP study

  Fat-adipocyte03 input ChIP-Seq paired end data

  Dataset EGAD00001007477

• Reference epigenome KNIH001 WGBS data generated from KEP study

  A KNIH001 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002749

• Reference epigenome Pancreas-beta01 h3k27me3 ChIP-Seq data generated from KEP study

  Pancreas-beta01 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007215

• CYP2C19 long-read sequencing

  We have assessed the added value of long-read sequencing for PGx focusing on the clinically important and highly polymorphic CYP2C19 gene within 48 samples.

  Dataset EGAD00001009883

• Reference epigenome Pancreas-Islet02 h3k27ac ChIP-Seq data generated from KEP study

  Pancreas-Islet02 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007193

• Reference epigenome Pancreas-Islet03 h3k9me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet03 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007205

• Reference epigenome Pancreas-Islet04 h3k27ac ChIP-Seq data generated from KEP study

  Pancreas-Islet04 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007207

• Reference epigenome Pancreas-Islet04 h3k27me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet04 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007208

• Reference epigenome Pancreas-Islet04 h3k36me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet04 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007209

• Reference epigenome Pancreas-Islet04 input ChIP-Seq data generated from KEP study

  Pancreas-Islet04 input ChIP-Seq paired end data

  Dataset EGAD00001007213

• Reference epigenome Pancreas-beta01 h3k9me3 ChIP-Seq data generated from KEP study

  Pancreas-beta01 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007219

• Reference epigenome Fat-Preadipocyte01 h3k27me3 ChIP-Seq data generated from KEP study

  Fat-Preadipocyte01 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007222

• Reference epigenome Kidney-Podocyte03 h3k27me3 ChIP-Seq data generated from KEP study

  Kidney-Podocyte03 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007236

• Reference epigenome Kidney-Podocyte03 h3k4me1 ChIP-Seq data generated from KEP study

  Kidney-Podocyte03 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007238

• Reference epigenome Kidney-Podocyte03 h3k4me3 ChIP-Seq data generated from KEP study

  Kidney-Podocyte03 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007239

• Reference epigenome Kidney-Podocyte03 h3k9me3 ChIP-Seq data generated from KEP study

  Kidney-Podocyte03 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007240

• Reference epigenome Kidney-mesangial01 h3k9me3 ChIP-Seq data generated from KEP study

  Kidney-mesangial01 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007254

• Reference epigenome IPS-Fibroblast02 h3k4me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007274

• Reference epigenome IPS-NPC01 h3k36me3 ChIP-Seq data generated from KEP study

  IPS-NPC01 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007279

• Reference epigenome IPS-NPC01 h3k27me3 ChIP-Seq data generated from KEP study

  IPS-NPC01 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007278

• Reference epigenome Pancreas-Islet07 h3k27me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet07 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007458

• Reference epigenome Pancreas-Islet07 h3k36me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet07 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007459

• Reference epigenome Pancreas-Islet08 h3k27me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet08 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007465

• Reference epigenome Pancreas-Islet08 input ChIP-Seq data generated from KEP study

  Pancreas-Islet08 input ChIP-Seq paired end data

  Dataset EGAD00001007470

• Reference epigenome Fat-adipocyte03 h3k36me3 ChIP-Seq data generated from KEP study

  Fat-adipocyte03 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007473

• DLP+ Single Cell Genomic Library A98203

  DLP+ Single Cell Genomic Library A98203 for Diffuse large B-cell lymphoma patient sample TFRIPAIR8_DLBCL

  Dataset EGAD00001010242

• DLP+ Single Cell Genomic Library A98180

  DLP+ Single Cell Genomic Library A98180 for Diffuse large B-cell lymphoma patient sample TFRI_Pair_13_DLBCL

  Dataset EGAD00001010240

• Subfraction targeted high-througput sequencing

  This dataset include the Fastq files from Capture-based targeted high throughput sequencing of bulk, monocytic and progenitor subfractions of PHENOMUT11 sample.

  Dataset EGAD00001009628

• DLP+ Single Cell Genomic Library A98225

  DLP+ Single Cell Genomic Library A98225 for Diffuse large B-cell lymphoma patient sample TFRIPAIR12_DLBCL_rel

  Dataset EGAD00001010246

• BC WGS Dataset 1

  Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells

  Dataset EGAD00001001350

• OT2_Illumina_WGS_MET_CELL

  Whole-genome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample (OT2_cohort)

  Dataset EGAD00001003373

• Thymic epithelial transplantation for complete DiGeorge syndrome Spatial (2025-07-28)

  Spatial transcriptomics study of thymic transplant biopsies . This dataset contains all the data available for this study on 2025-07-28.

  Dataset EGAD00001015659

• H3Africa EPIGEN Phenotype

  Phenotype data from pregnant mothers unexposed and exposed to the Rwandan genocide from 59 whole blood samples.

  Dataset EGAD00001009739

• Geographic variation of mutagenic exposures in kidney cancer genomes – sequence data (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – sequence data (Mutographs)

  Dataset EGAD00001012102

• SF4007

  SF4007 snATAC Seq. Oligodendroglioma (WHO gr. 2) Tumor Location: Left frontotemporal. Age:33. Sex: Female.

  Dataset EGAD00001006317

• Reference epigenome Pancreas-Islet03 h3k4me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet03 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007204

• Reference epigenome Fat-Preadipocyte01 h3k4me1 ChIP-Seq data generated from KEP study

  Fat-Preadipocyte01 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007224

• Reference epigenome Kidney-Podocyte04 h3k36me3 ChIP-Seq data generated from KEP study

  Kidney-Podocyte04 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007244

• Reference epigenome IPS-Fibroblast01 h3k27me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007264

• Reference epigenome IPS-Fibroblast01 h3k36me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007265

• Reference epigenome IPS-Fibroblast01 h3k4me1 ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007266

• Reference epigenome IPS-Fibroblast01 h3k4me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007267

• Reference epigenome IPS-Fibroblast01 h3k9me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007268

• Reference epigenome IPS-Fibroblast01 input ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 input ChIP-Seq paired end data

  Dataset EGAD00001007269

• Reference epigenome IPS-Fibroblast02 h3k27me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007271

• Reference epigenome IPS-Fibroblast02 h3k36me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007272

• Reference epigenome IPS-ENeuron01 h3k27me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007292

• Reference epigenome IPS-ENeuron01 h3k36me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007293

• Reference epigenome IPS-ENeuron01 h3k4me1 ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007294

• Reference epigenome IPS-ENeuron01 h3k4me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007295

• Reference epigenome IPS-ENeuron01 h3k9me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007296

• Reference epigenome IPS-ENeuron01 input ChIP-Seq data generated from KEP study

  IPS-ENeuron01 input ChIP-Seq paired end data

  Dataset EGAD00001007297

• Reference epigenome IPS-ENeuron02 h3k27me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron02 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007299

• Reference epigenome IPS-ENeuron02 h3k36me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron02 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007300

• Reference epigenome IPS-ENeuron02 input ChIP-Seq data generated from KEP study

  IPS-ENeuron02 input ChIP-Seq paired end data

  Dataset EGAD00001007304

• Follow-up of Ovarian Cancer Genetic Association and Interaction Studies (FOCI)

  (Excerpted/paraphrased from original grant application): FOCI seeks to expand our understanding of epithelial ovarian cancer through a coordinated and comprehensive approach. Project 1 will focus on discovery, expansion, and replication. By pooling GWAS, we expect to identify new associations and achieve independent replication, explore whether there are risk variants specific for histologic subtypes, and evaluate structural polymorphisms - copy number variants - as risk factors. Finally, Project 1 will leverage the GWAS data to correlate DNA variants with a new endpoint - survival. Project 2 will focus on biological studies designed to help inform interpretation of findings from Project 1. This will include efforts to identify the functional consequences of variants and improve understanding of biological mechanisms. Project 3 will include epidemiologic studies of gene by gene interaction, gene by environment interaction, and development of risk prediction models. The collective effort builds upon the strengths and history of collaboration inherent in the Ovarian Cancer Association Consortium (OCAC), a multidisciplinary group comprised of epidemiologists, genetic epidemiologists, statistical geneticists, molecular and cell biologists and clinicians that was formed in 2005. The FOCI Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001133 FOCI Cohort. phs001131 Affymetrix Exome Chip phs001132 GWAS Meta Analysis phs001142 Mayo Omni Express phs001150 Mayo 2 5M

  Study phs001133

• Single Chromatin Fiber Profiling in the Human Brain

  We developed a human postmortem brain-applicable ‘Fiber-seq' protocol for genome-scale, PCR-free single molecule sequencing of on average 8-10kb long chromatin fibers, to map nucleosome positioning and nucleosome-depleted regions which include, for example, active promoters and enhancers. We generated two Fiber-seq reference sets, one from sorted non-neuronal NeuN- prefrontal cortex (PFC) nuclei from a 32 year old female donor, with total of 11,143,795 reads/fibers, and median of 30-fold genomic coverage. The other reference set was generated on sorted prefrontal NeuN+ neurons, from two 24 year old brain donors (1 female/1 male), with a combined total read/fiber count of 4,749,556 and median of 20-fold genomic coverage. Each of the peaks in the Fiber-seq libraries seq signal correlated with the ATAC peak levels in the neuronal and non-neuronal ATAC-seq libraries, respectively (promoters, clusters 1, 3; NeuN+, r = 0.574; NeuN-, r=0.683, PHowever, Fiber-seq detected 19,978 highly significant peaks which, while showing some non-significant/near-background ATAC-Seq alignments, lacked a corresponding site-specific enrichment in conventional short-read ATAC- and ChIP-seq datasets. However, 60% of these peaks were in repetitive DNA elements. Therefore, long read single chromatin fiber sequencing, which exceed the base pair length of conventional short-read libraries by two orders of magnitude, could capture many actively regulated repeat elements at the site of specific gene loci, that otherwise would remain unmappable by conventional ATAC-, and histone- ChiP-seq.

  Study phs003771

• Neoadjuvant immunotherapy leads to pathological responses in MMR proficient and MMR deficient early stage colon cancers

  PD-1 plus CTLA-4 blockade is highly effective in advanced-stage, mismatch repair (MMR)-deficient (dMMR) colorectal cancers, yet not in MMR-proficient (pMMR) tumors. We postulated a higher efficacy of neoadjuvant immunotherapy in early-stage colon cancers. In the exploratory NICHE study (ClinicalTrials.gov: NCT03026140), patients with dMMR or pMMR tumors received a single dose of ipilimumab and two doses of nivolumab before surgery, the pMMR group with or without celecoxib. The primary objective was safety and feasibility; 40 patients with 21 dMMR and 20 pMMR tumors were treated, and 3 patients received nivolumab monotherapy in the safety run-in. Treatment was well tolerated and all patients underwent radical resections without delays, meeting the primary endpoint. Of the patients who received ipilimumab + nivolumab (20 dMMR and 15 pMMR tumors), 35 were evaluable for efficacy and translational endpoints. Pathological response was observed in 20/20 (100%; 95% exact confidence interval (CI): 86–100%) dMMR tumors, with 19 major pathological responses (MPRs, ≤10% residual viable tumor) and 12 pathological complete responses. In pMMR tumors, 4/15 (27%; 95% exact CI: 8–55%) showed pathological responses, with 3 MPRs and 1 partial response. CD8+PD-1+ T cell infiltration was predictive of response in pMMR tumors. These data indicate that neoadjuvant immunotherapy may have the potential to become the standard of care for a defined group of colon cancer patients when validated in larger studies with at least 3 years of disease-free survival data.

  Study EGAS00001004160

• prcmd-G-1

  Genetic studies of pregnancy-related cardiometabolic disorders in Central Asian, Northern European, and Colombian populations

  Dataset EGAD00010001212

• ctgap-G-1

  Illumina HumanCoreExome-12v1-1_A chip typing in a Greek adolescent population

  Dataset EGAD00010001005

• GSA reference

  reference whole exome sequence serving as a reference of individuals. Includes the raw GSa files and the called variants in vcf format merge for all individuals (S1-S5).

  Dataset EGAD50000000481

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_003 for Diffuse large B-cell lymphoma patient sample TFRIPAIR10

  Dataset EGAD50000001372

• scRNA-seq Next GEM Single Cell 3ʹ

  Single-cell RNA sequencing (scRNA-seq) was generated using the 10x Genomics Chromium Next GEM Single Cell 3ʹ platform

  Dataset EGAD50000001185

• Solid_WXS_MET-XEN

  Whole-exome sequencing on AB 5500xl Genetic Analyzer of Patient-derived xenograft derived from colorectal cancer metastasis sample

  Dataset EGAD00001002106

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_001 for Follicular lymphoma patient sample TFRIPAIR4_FL

  Dataset EGAD00001010217

• Pre-neoplastic liver colonization by 11p15.5 altered mosaic cells in young children with hepatoblastoma

  Additional datasets linked to EGAS00001006692

  Dataset EGAD00001011097

• Normal sample for patient SA224

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA224

  Dataset EGAD00001009548

• Tumour sample for patient SA720

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA720

  Dataset EGAD00001009585

• Reference epigenome Islet-derived-MSC04 h3k36me3 ChIP-Seq data generated from KEP study

  Islet-derived-MSC04 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007431

• Reference epigenome Islet-derived-MSC02 input ChIP-Seq data generated from KEP study

  Islet-derived-MSC02 input ChIP-Seq paired end data

  Dataset EGAD00001007415

• Reference epigenome Islet-derived-iPSC02 input ChIP-Seq data generated from KEP study

  Islet-derived-iPSC02 input ChIP-Seq paired end data

  Dataset EGAD00001007449

• Reference epigenome Islet-derived-MSC04 h3k4me3 ChIP-Seq data generated from KEP study

  Islet-derived-MSC04 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007433

• Tumour sample for patient SA601

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA601

  Dataset EGAD00001009205

• Tumour sample for patient SA588

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA588

  Dataset EGAD00001009194

• Tumour sample for patient SA590

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA590

  Dataset EGAD00001009196

• Tumour sample for patient SA654

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA654

  Dataset EGAD00001009206

• Normal sample for patient SA604

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA604

  Dataset EGAD00001009217

• Normal sample for patient SA398

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA398

  Dataset EGAD00001009231

• Reference epigenome Islet-derived-MSC04 h3k9me3 ChIP-Seq data generated from KEP study

  Islet-derived-MSC04 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007434

• Normal sample for patient SA221

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA221

  Dataset EGAD00001009362

• Tumour sample for patient SA425

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA425

  Dataset EGAD00001009356

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015302

• Tumour sample for patient SA234

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA234

  Dataset EGAD00001009525

• Tumour sample for patient SA226

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA226

  Dataset EGAD00001009532