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• Single cell whole genome sequencing of luminal breast epithelial cells from wildtype and BRCA mutation carriers

  Single cell whole genome sequencing was done using DLP+ (https://doi.org/10.1016/j.cell.2019.10.026) on luminal breast epithelial cells from wildtype and BRCA mutation carriers. Each BAM file is a merged BAM from single cells from a single sample, and the cells can be uniquely identified by their @RG group. Only high quality cells were kept, thus there are large differences in BAM sizes. The same sample/patient can be found across multiple BAM files to accumulate more cells, sometimes the same patient will have multiple FACS sorted cell types also split by BAMs.

  Dataset EGAD50000000883

• scRNA-seq dataset, RCC

  scRNA-seq dataset for the study "Surgery in combination with immune checkpoint therapy as an effective treatment for patients with metastatic cancer." The dataset comprises 38 samples from 19 patients, with each pair includes a baseline (BL) sample and a post-biopsy or post-surgery sample. Each sample corresponds to an R1 (read 1) and an R2 (read 2) files (.fastq.gz) for paired reads. Beside procedure (biopsy or surgery), another important phenotype is response (PR and PD in this case, no SD for these patients), included in the description of the samples. The sequencing was performed using Illumina NovaSeq 6000 platform., as seen in the experiment description.

  Dataset EGAD50000000566

• Samples obtained within X-pand project

  This dataset contains five bone marrow samples and three mobilised peripheral blood ones from different healthy individuals. The three bone marrow samples have been sequence with the 10x multiome kit using Illumina sequencers. The three mobilised peripheral blood ones have been split in two aliquots, one for 10x multiome and the other for 10x CITE-seq. Both libraries types have been sequenced with an Illumina sequencer. Raw data has been processed with cell-ranger and map to the human genome (GRCh38) to obtain the bam files.

  Dataset EGAD50000001108

• Data access policy

  Investigators who download restricted data from this dataset should: - Not attempt to identify individual human research participants from whom the data were obtained. - Acknowledge in all oral or written presentations, disclosures, or publications the specific dataset(s) or applicable accession number(s) and the repositories through which the investigator accessed any data. Any user requesting access to this data must apply for authorization, which is granted by the Data Access Committee (DAC). The DAC will review and approve or disapprove all requests from the research community for data access. Decisions to grant access are made based on whether the request conforms to the specifications of the Research Ethics Committee approval and program specific requirements or procedures (if any).

  Dac EGAC50000000504

• Alpha synucleinopathy spectrum - single nucleus RNA seq of prefrontal cortex

  Single nucleus RNA seq dataset from prefrontal cortex of a total of N=46 individuals with alpha synucleinopathies and healthy controls. Tissue samples correspond to patients with Parkinson's disease (PD, N=20) monogenic PD caused by LRRK2 mutations (LRRK2-PD, N=7), multiple system atrophy (MSA, N=6) and neurologically healthy controls (N=13). RNA seq was carried out employing 10X Genomics Chromium. These samples were also sequenced using conventional bulk tissue RNA seq, and available within the same study as a separate dataset.

  Dataset EGAD50000000431

• Longitudinal Transcriptomic Profiling of Endothelial Progenitor Cells in Post-COVID-19 Patients: Insights at 3 and 6-Months Post-SARS-CoV-2 Infection

  Raw transcriptomic data from endothelial cells of post-COVID patients and healthy controls. Samples were collected from post-COVID patients at 3 months (n = 6) and 6 months (n = 6) post-infection, as well as from healthy control individuals (n = 5). All post-COVID patients were hospitalized during the first wave of the pandemic. Among them, half developed pulmonary embolism (TEP; n = 6), while the other half did not (no TEP; n = 6).

  Dataset EGAD50000001452

• Merged VCF file from familial Meniere disease cohort

  This dataset contains a merge VCF file generated from WES data of patients diagnosed with familial Meniere disease (FMD). Variant calling followed GATK best practices using the nf-core/Sarek pipeline (v3), and variants were filtered using genotype-level thresholds consistent with gnomAD filters. Multiallelic variants were split and INDELs were left-aligned during normalization. Variant Quality Score Recalibration (VQSR) was applied separately to SNVs and INDELs using well-established truth sets, with a 90% sensitivity threshold to maximize the detection of rare variants. Final variants were annotated with Ensembl VEP.

  Dataset EGAD50000001682

• Merged VCF file from sporadic Meniere disease cohort

  This dataset contains a merge VCF file generated from WES data of patients diagnosed with sporadic Meniere disease (FMD). Variant calling followed GATK best practices using the nf-core/Sarek pipeline (v3), and variants were filtered using genotype-level thresholds consistent with gnomAD filters. Multiallelic variants were split and INDELs were left-aligned during normalization. Variant Quality Score Recalibration (VQSR) was applied separately to SNVs and INDELs using well-established truth sets, with a 90% sensitivity threshold to maximize the detection of rare variants. Final variants were annotated with Ensembl VEP.

  Dataset EGAD50000001683

• RNA-seq from B-ALL patients treated on the ALLG ALL09 study

  Dataset contains RNA-sequencing data (fastq files) from 46 patients treated on the Australasian Leukaemia and Lymphoma Group (ALLG) ALL09 study (ACTRN12618001734257). All patients were diagnosed with CD19 positive B-cell acute lymphoblastic leukaemia and were negative for Philadelphia chromosome positive disease. Patient samples (bone marrow or peripheral blood) were taken at diagnosis. mRNA was extracted from lymphoblasts and underwent paired-end sequencing using either the illumina NextSeq (75 bp PE) or MGI DNABSEQ-G400 (100bp PE) platforms. Transcriptomic data was used for identification of genomic drivers of acute lymphoblastic leukaemia (ALL).

  Dataset EGAD50000001603

• The prevalence and clinical characteristics of TECTA-associated autosomal dominant hearing loss.

  TECTA is well known as the causative gene for autosomal dominant mid-frequency hearing loss observed in various populations. In this study, we performed next-generation sequencing analysis of a large Japanese hearing loss cohort from unrelated autosomal dominant hearing loss families, to estimate the prevalence and phenotype-genotype correlations in patients with TECTA mutations.

  Study JGAS000201