6377 results for "11+1双色球多少钱一注"

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• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015716

• Sequencing data for oesophageal and related samples - ICGC DCC release 28 (WGS)

  WGS sequencing for 409 cases (832 samples) from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are all available in ICGC release 28

  Dataset EGAD00001004137

• Sequencing data for oesophageal and related samples - ICGC DCC release 27 earmarked (WGS)

  WGS sequencing for 63 cases (126 samples) from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are earmarked for inclusion in ICGC release 27 (deferred to release 28)

  Dataset EGAD00001004028

• Sequencing data for oesophageal and related samples - Alex Frankell et al (WGS)

  Data supporting: "The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic." Frankell et al. WGS (BAM files) 379 matched tumour-normal pairs

  Dataset EGAD00001004417

• Comparison of 3 protocols for deriving pancreatic progenitors from hPSCs (RNA-seq)

  This dataset contains 26 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared Smart-Seq2 RNA-seq libraries for the 27 samples, 1 sample failed library preparation and is not therefore included in this dataset.

  Dataset EGAD00001004823

• Sequencing data for oesophageal and related samples - Noorani et al (WGS)

  Data supporting: "Genomic evidence supports a clonal diaspora model for metastases of esophageal adenocarcinoma." Noorani et al. WGS (BAM files) 134 samples for 18 cases Includes primary, lymph-node, distant metastatic, Barrett's and normal samples.

  Dataset EGAD00001005434

• RNA-seq dataset of Characterization of UV DNA damage in B-cell precursor acute lymphoblastic leukemia

  Extensive characterization of mutational signature SBS7a in B-cell precursor acute lymphoblastic leukemia (BCP-ALL) samples. We aimed to describe the presentation of SBS7a in BCP-ALL, identify other pediatric cancers presenting with SBS7a, look into the link of SBS7a and UV-light in the context of BCP-ALL and cancers with provable UV exposure, and pinpoint when SBS7a was acquired.

  Dataset EGAD00001015598

• Type 1 Diabetes Genetics Consortium (T1DGC): Multi-Ethnic ImmunoChip Study

  Type 1 diabetes (T1D) is characterized by an autoimmune attack that destroys the insulin-producing pancreatic beta cells and is driven by diverse genetic and environmental factors. Between 8-100 chromosome regions are known to contain variants that alter T1D risk, substantially fewer than many other common diseases. Less is known about the contribution of T1D risk alleles in non-European populations, despite recent increases in T1D diagnoses in multiple non-European ancestry groups. To address these gaps in T1D genetics, we doubled the sample size from the previous largest T1D association study, genotyped ancestrally diverse T1D cases, controls, and affected families with the Illumina ImmunoChip array, and imputed additional variants using a large haplotype reference panel. After quality filtering, a total of 61,427 participants and 140,333 genotyped ImmunoChip variants were included in analysis, providing dense coverage in 188 autosomal regions ("ImmunoChip regions") and sparse genotyping in other regions of the genome. Each participant was assigned to one of five ancestry groups using k-means clustering of ImmunoChip genotype principal components: European (EUR, N = 47,319), African Admixed (AFR, N = 4,290), Finnish (FIN, N = 6,991), East Asian (EAS, N = 588) and Other Admixed (AMR, N = 2,239). In total, 16,159 T1D cases, 25,386 controls (unrelated) and 6,143 trio families (i.e., an affected child and both parents) were genotyped and included in association analyses. Imputation with the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) multi-ethnic reference panel was used to improve discovery power and fine-mapping resolution. After imputation, the number of variants in ImmunoChip regions with imputation R-squared > 0.8 and MAF > 0.005 in each ancestry group was 322,084 (AFR), 166,274 (EUR), 163,612 (FIN), 137,730 (EAS) and 188,550 (AMR). Imputed genotypes were compared in the same participants who have whole genome sequencing data, resulting in high concordance. Unrelated cases and controls (N = 41,545) were analyzed initially, assuming an additive inheritance model. T1D trio families (N = 6,143 trios, some trio families were multiplex and analyzed as multiple trios) were analyzed separately, with meta-analysis of case-control and trio results used for discovery of regions associated with T1D (p < 5×10-8). Summary-level data at each SNP (genotype and imputed) for type 1 diabetes (outcome) are provided in dbGaP.

  Study phs002468

• Identifying autosomal recessive mutations causing neurological disorders

  The objective of this study is to resequence of targeted intervals containing autosomal recessive variants causing neurological disorders in consanguineous pedigrees. Using homozygosity mapping, three intervals of very different sizes have previously been unambiguously mapped for three different neurological diseases: 2.4Mb, 8Mb and 14.3Mb in size, for Microlissencephaly, Severe Mental Retardation and Complicated hereditary spastic paraplegia respectively. This study is a pilot to assess how well custom targeted resequencing performs across a broad size range of intervals. The study design is to use a different custom capture probe set for each interval, pulldown from a single patient from each family, and sequence 1 lane using Illumina paired-reads for each sample. Candidate variants will be followed up in the families themselves, and in patients with similar phenotypes from outbred populations.

  Study EGAS00001000023

• Clinical Cancer Sequencing

  Translating whole exome sequencing (WES) for prospective clinical use may impact the care of cancer patients; however, multiple innovations are necessary for clinical implementation. These include: (1) rapid and robust WES from formalin-fixed paraffin embedded (FFPE) tumor tissue, (2) analytical output similar to data from frozen samples, and (3) clinical interpretation of WES data for prospective use. In this study, we describe a prospective clinical WES platform for archival FFPE tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a "long tail" of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15/16 patients. Overall, this methodology may inform the widespread implementation of precision cancer medicine.

  Study phs000694