1073 results for "2025年12月600642股价走势分析"

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• Data from Shea et al Can Research 2025

  This dataset contains single cell RNA sequencing (192 fastq files for 59 samples), whole exome sequencing (20 BAM files -hg38- for 20 samples) and bulk RNA sequencing (138 paired-end fastq files and 17 single-end fastq files for 8 samples)

  Dataset EGAD50000001334

• Comparison of transcriptomics profile of stem cell-derived beta cells from HUES8 and RC9

  Stem cell-derived islet cells have a potential to be used to restore endogenous insulin production in people with diabetes. The goal of this experiment is to compare the transcriptomics profile of stem-cell derived beta cells from two different cell lines: HUES8 (non-clinical grade) and RC9 (clinical grade) in terms of beta cell identity and maturity. Stem cell-derived islets were produced using differentiation protocol detailed in Rajaei et al. 2025 (manuscript approved in Science Translational Medicine, pending pubmed ID). Single cell transcriptomics data were generated using 10x Genomics 3' Single Cell Gene Expression kit.

  Study EGAS50000000905

• lpWGS of solid and liquid samples from female patients with metastatic breast cancer

  low-pass Whole Genome Sequencing (lpWGS) to assess the representativeness of seven body liquids from female patients with metastatic breast cancer. 20 patients. 216 liquid samples, 745 solid samples, 20 matched normal samples. 0.5X coverage. Illumina single read sequencing. Fastq files are provided. lpWGS from Richard et al., Nature Communications, 2025.

  Dataset EGAD50000001851

• Learning from the thymic human cell atlas for T cell engineering: Paediatric RNA (2025-10-02)

  T cells are central to adaptive immunity and thus crucial for understanding and treating human disease. While extensively studied in model organisms, translating this knowledge to humans can sometimes be limited by their rapid cross-species evolution and diverse . This dataset contains all the data available for this study on 2026-03-10.

  Dataset EGAD00001015720

• A next-generation dual guide CRISPR system for genetic interaction library screening

  Raw sgRNA sequencing data from a pilot CRISPR screening library to test the dual guide vector system (8,914 guide pairs), and from a large scale genetic interaction screen (~100,136 guide pairs) in HT-29 cells. This data refers to Burgold et al. Nature Communications 2025.

  Dataset EGAD00001015754

• Purified vs unpurified stem cell-islets

  A scRNAseq dataset consisting of stem cell-derived islets treated with gradient separation (HUES8_Pure_Islets) and unpurified control (HUES8_control_islets). scRNAseq was done on cryopreserved stage 7 stem cell (HUES8 cell line)-derived islets. Details about stem cell differentiation and sequencing can be found on the publication by Rajaei et al. (2025, Science Translational Medicine). This dataset correspond to Fig 4 of the publication.

  Dataset EGAD50000001396

• Mapping Cells and Interactions in the Thymus Across Development and Aging (2025-07-28)

  Single cell RNA sequencing on thymic cells from children with syndromic diseases such as Trisomy 21 and inflammatory/autoimmune diseases such as myasthenia gravis. Our group has previously performed atlasing of the healthy human thymus using single cell transcriptomics and obtained an unprecedented understanding of human thymus throughout development. In this study, we intend to survey diseased human thymus and compare this to healthy to obtain a better understanding of thymic dysfunction in human diseases. The diseases we will survey include congenital conditions such as Down's syndrome, CHARGE syndrome, DiGeorge syndrome as well as acquired diseases such as myasthenia gravis and thymic hyperplasia. We intend to perform genetic and genomic study on the samples, including expression analysis. This will not only help us to understand the cells and molecular pathways affected in dysfunctional thymus; but may also lead to generalisable understandings in human genetic diseases and inflammatory/autoimmune diseases. 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/ . This dataset contains all the data available for this study on 2025-07-28.

  Dataset EGAD00001015660

• Head and Neck Organoid Biobank cohort, Issing et. al., 2025, RNA + WES data

  This dataset contains the raw fastq files of RNA and whole exome sequencing of the head and neck organoid biobank. For RNA sequencing, 41 organoid samples collected at different timepoints as well as before and after genetic modification are included. For WES, 25 samples of early organoid cultures or matching tumor tissues are included.

  Dataset EGAD50000001733

• Shallow whole genome sequencing DETECT samples

  Shallow whole genome sequencing of samples from the paper Beddowes et al. A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival. Mol. One 2025. This includes 1048 longitudinal plasma samples from 149 patients and 35 normals. Samples were sequenced with shallow whole genome sequencing for copy number estimation. All the files are single-end fastq files.

  Dataset EGAD50000001333

• Sequence data for "An allele-resolved nanopore-guided tour of the human placental methylome" (Kindlova et al 2025)

  Sequence data generated for the study "An allele-resolved nanopore-guided tour of the human placental methylome" includes Illumina WGS, Illumina RNA-seq, Illumina EM-seq, and Oxford Nanopore Technologies PromethION sequence data.

  Dataset EGAD50000001850

• WTS data from PASS-01 trial

  WTS data for pancreatic cancer samples (PASS-01 Trial; Knox et al., Journal of Clinical Oncology, 2025).  The dataset includes tumour bam files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=115 tumours)

  Dataset EGAD50000002308

• WGS data from PASS-01 trial

  WGS data for pancreatic cancer samples (PASS-01 Trial; Knox et al., Journal of Clinical Oncology, 2025).  The dataset includes tumour and normal cram files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=127 tumour/normal pairs)

  Dataset EGAD50000002309

• stem cell-derived beta cells from cell lines RC9 and HUES8

  stem cell-derived beta cells differentiated using two different cell lines: HUES8 (non-clinical grade) and RC9 (clinical grade). iPSC stem cell lines were differentiated to pancreatic islets using differentiation protocol as detailed by Rajaei et al. (2025, Science Translational Medicine, accepted for publication). scRNAseq was done at stage 7 of differentiation (day 30) using 10X genomics 3' sequencing. Cells were annotated then subsetted for beta cells for downstream analysis

  Dataset EGAD50000001322

• WGS data for Pancreatic Cancer samples (resection cohort)

  WGS data from pancreatic cancer samples. These are part of a resected cohort from a tandem duplicator phenotype paper (Farooq et al, NPJ Precision Oncology, 2025). The dataset includes tumour and normal BAM files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=189 tumour/normal pairs).

  Dataset EGAD50000001834

• NAR-GAB 2025 deposit data

  Paired-end whole-exome sequencing data derived from Illumina hybrid-capture experiments (Agilent SureSelect Human All Exon kits). Six human probands with rare diseases; one sample per subject. Sequencing reads from each individual were processed into analysis-ready gVCF files following standard best-practice pipelines, including alignment, duplicate marking, base quality calibration, and variant calling. All gVCF files are encrypted using Crypt4GH and are available under controlled access through our DAC in accordance with a strict DUO-based policy.

  Dataset EGAD50000002100

• To profile the landscape of sebaceous tumours_WES

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract DNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted DNA will be used for exome sequencing. Please note that the dataset was last revised on October 16, 2025.

  Dataset EGAD00001015367

• 12 Nasopharyngeal carcinoma patients without treatment and 12 Nasopharyngeal carcinoma patients with treatment (WGS)

  12 Nasopharyngeal carcinoma patients without treatment and 12 Nasopharyngeal carcinoma patients with treatment (WGS)

  Dataset EGAD00001009840

• Admixture histories of São Tomé e Príncipe.

  Genotyping datasets used in the article "Nested admixture during and after the Trans-Atlantic Slave Trade in the island of Sao Tome" by Ciccarella M et al. 2025 The genotype data corresponds to 2,104,148 autosomal SNPs genotyped from the IlluminaOmni 2.5 Million BeadChip for 97 volunteer participants sampled on São Tomé e Príncipe, family unrelated at the 2nd degree based on population genetics analyses. In particular, the dataset is composed of 95 individual samples collected on São Tomé and 2 collected on Príncipe. SNP rsID, Chromosome position and genetic position in (bp) are in Build GRCh38.

  Dataset EGAD50000001348

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• Targeted capture ctDNA Library CRCQV42Run036-12

  Targeted capture ctDNA Library CRCQV42Run036-12 from patient PBC0003587, plasma 12 month sample

  Dataset EGAD00001010594

• Targeted capture ctDNA Library CRCQV34Run015-12

  Targeted capture ctDNA Library CRCQV34Run015-12 from patient PBC0002108, plasma 12 month sample

  Dataset EGAD00001010378

• RNA sequencing of 12 NSCLC samples from 4 patients at MDACC

  Multi-region RNA sequencing of 12 NSCLC samples from 4 patients at MDACC

  Study EGAS00001005951

• Whole genome sequencing, SNP array and RNA-seq of uveal melanomas

  We conducted whole genome sequencing and DNA SNP array of 12 uveal melanoma genomes and their matched DNA from blood. We also conducted RNA-seq of the 12 tumour samples.

  Study EGAS00001000472

• Mammary cell samples from donors 28/32/33

  Mammary cell samples from donors 28/32/33. Contains 12 MiSeq sequencefiles and 12 alignment files derived from HiSeq runs.

  Dataset EGAD00001001439

• Whole exome sequencing of 12 NSCLC samples from 4 patients at MDACC

  Multi-region WES from 4 NSCLC patients, totaling 12 tumor samples and 4 matched control samples.

  Study EGAS00001005829

• Colorectal-Cancer-Tumor-Spheres-H012-Microarray_Expression

  Gene expression of 12 colon cancer TSCs (sensitive or resistant) after 12h treatment with 3µM NCT02 or DMSO (control) was analyzed using Illumina microarrays (HumanHT-12 v4 BeadChip).

  Dataset EGAD00010001936

• Target Capture Sequencing of 12 patients

  We perfomed target capture DNA sequencing of 12 patients to assess the detailed biological mechanisms of resistance to immune checkpoint inhibitors.

  Study JGAS000589

• WGS of oesophagogastric cancer

  WGS of 12 oesophagogastric cancer samples WGS or 12 matched germline data.

  Dac EGAC50000000890

• SNP_dataset_1

  Tissue samples using Illumina HumanOmniExpress-FFPE-12 v1.0 BeadChip

  Dataset EGAD00010001179

• single-cell RNA-seq Case-Control study of children progressing to Type1 diabetes

  Single-cell RNA sequencing was carried out on four selected PBMC samples of Finnish children at risk of developing Type 1 diabetes and their gender age and HLA matched control children using 10X genomic platform. All four Case children were positive for multiple islet specific autoantibodies and two of them also progressed to clinical disease during the follow up whereas the control children remain negative for all autoantibodies. Age at seroconversion for Case 2, 3, 5, and 9 children is 12, 18, 24, and 18 months, respectively. Age at sampling, in months, for the pairs was as follows (Case/Control): pair 2:24/24; pair 3: 12/18; pair 5: 12/12; pair 9:24/18.

  Study EGAS00001004070

• WGS of oesophagogastric cancer

  Illumina short read WGS of 12 oesophagogastric cancer samples

  Dataset EGAD50000002239

• Employing_single_cell_sequencing_for_detection_of_mutational_signatures_reflecting_on_going_mutagenesis_

  12 single cells will be sequenced from a previously single-cell derived clone of a JSC-1 cell line. Additional 12 single cells are likely to be sequenced from a previously single-cell derived clone of a SW756 line. Both belong to CGP’s panel of approximately 1000 human cancer cell lines.

  Study EGAS00001002679

• 2018_ETO_WGS

  This study includes 12 paired samples of Korean AML-ETO paitients.12 AML-ETO tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002804

• Combining dasatinib and IFN-α in CML – immunomodulatory effects linked to treatment response and adverse events

  We pooled 100,000 cells from the 12 scRNA+TCRab-seq samples from peripheral blood from three time points (n=4, samples at 0, 3, and 12 months) to understand the landscape of immune subsets in CML during the course of dasatinib+IFN-α treatment

  Study EGAS00001005049

• KRAS Mutations in Multiple Myeloma

  Fastq files for 80 Multiple Myeloma Patients and 12 cell-lines

  Dataset EGAD00001005743

• WGS data of plasma samples from CRC patients

  WGS data of plasma samples from CRC patients (N=12)

  Dataset EGAD00001006419

• Transcriptomic signatures of CD4+ T cells from visceral leishmaniasis (VL) patients

  Bulk RNA-sequencing was performed on CD4+ T cells isolated from the blood of visceral leishmaniasis patients (n = 12) and endemic controls (EC; n = 12). CD4+ T cells were obtained by magnetic-activated cell sorting (MACS). Alterations in the transcripts of T helper (Th) cells during infection were identified.

  Study EGAS00001004152

• Exome sequencing Wilms tumour

  Exome sequencing of lymphocyte DNA from 12 affected individuals from six unrelated, non-syndromic Wilms tumor families.

  Dataset EGAD00001001003

• Targeted capture ctDNA Library CRCQV42Run025-12

  Targeted capture ctDNA Library CRCQV42Run025-12 from patient PBC0003014, saliva sample

  Dataset EGAD00001010478

• Targeted capture ctDNA Library CRCQV42Run051-12

  Targeted capture ctDNA Library CRCQV42Run051-12 from patient PBC0001516, plasma sample

  Dataset EGAD00001010806

• GabonDiv_SNP_genotyping

  Genome-wide SNP genotyping data for 1,235 western Africans by Illumina HumanOmniExpress-12 array, used in the EGAS00001002078 study

  Dataset EGAD00010001209

• Targeted capture ctDNA Library CRCQV34Run007-12

  Targeted capture ctDNA Library CRCQV34Run007-12 from patient PBC0002816, plasma baseline sample

  Dataset EGAD00001010354

• Targeted capture ctDNA Library CRCQV42Run034-12

  Targeted capture ctDNA Library CRCQV42Run034-12 from patient PBC0004173, buffy coat sample

  Dataset EGAD00001010566

• Targeted capture ctDNA Library CRCQV42Run019-12

  Targeted capture ctDNA Library CRCQV42Run019-12 from patient PBC0001295, plasma baseline sample

  Dataset EGAD00001010419

• Targeted capture ctDNA Library CRCQV34Run011-12

  Targeted capture ctDNA Library CRCQV34Run011-12 from patient PBC0002294, plasma baseline sample

  Dataset EGAD00001010366

• Targeted capture ctDNA Library CRCQV42Run033-12

  Targeted capture ctDNA Library CRCQV42Run033-12 from patient PBC0002406, buffy coat sample

  Dataset EGAD00001010551

• Targeted capture ctDNA Library CRCQV42Run047-12

  Targeted capture ctDNA Library CRCQV42Run047-12 from patient PBC0003385, buffy coat sample

  Dataset EGAD00001010724

• Targeted capture ctDNA Library CRCQV42Run028-12

  Targeted capture ctDNA Library CRCQV42Run028-12 from patient PBC0004076, plasma baseline sample

  Dataset EGAD00001010502

• Targeted capture ctDNA Library CRCQV42Run029-12

  Targeted capture ctDNA Library CRCQV42Run029-12 from patient PBC0004173, plasma baseline sample

  Dataset EGAD00001010512

• Targeted capture ctDNA Library CRCQV42Run032-12

  Targeted capture ctDNA Library CRCQV42Run032-12 from patient PBC0001224, buffy coat sample

  Dataset EGAD00001010538