385 results for "comprar monedas FC 26 Visité Buyfc26coins.com. Todo fue perfecto desde el principio hasta el final..L8Kn"

in 18.88 milliseconds.

• Division of Cancer Epidemiology and Genetics (DCEG) Imputation Reference Dataset

  We have built a new resource for imputation of SNPs for existing and future genome-wide association studies (GWAS), known as the Division of Cancer Epidemiology and Genetics (DCEG) Reference Set. The first build of the data set includes 728 cancer-free individuals of European descent from three large prospectively sampled studies, 98 African-American individuals from the Prostate, Lung, Colon, and Ovary Cancer Screening Trial (PLCO), 74 Chinese individuals from a Chinese clinical trial in Shanxi, China (SHNX), and 349 unrelated individuals from the HapMap Project (see Molecular Data Section for details on arrays used). The final harmonized dataset includes 2.8 million autosomal polymorphic SNPs on 1,249 subjects after rigorous quality control metrics were applied.

  Study phs000396

• WES dataset of a TIL-ACT metastatic melanoma cohort

  Whole-exome sequencing (WES) data from 13 patients with metastatic melanoma in a TIL-ACT cohort, generated to characterize tumor genomics and neoantigen landscapes relevant to adoptive T cell therapy.

  Dataset EGAD50000001731

• alopecia areata

  exome sequencing files from 25 alopecia areata samples from spain.

  Dataset EGAD00001006370

• Single-cell RNA sequence analysis of iPS cell-derived cardiomyocytes treated with S-RBD-sfGFP or GFP

  To determine the transcriptional response in human cardiomyocytes treated with SARS-CoV-2 spike receptor-binding domain (S-RBD-sfGFP), human cardiomyocytes differentiated from induced pluripotent stem cells (iPSC-CMs) were replated on day 21 after differentiation and treated with S-RBD-sfGFP or control-GFP for 48 hours on day 26-28. iPSC-CMs were dissociated and the single cell suspension was analyzed by single cell RNA-sequence.

  Study JGAS000620

• RNA-Sequencing and Somatic Mutation Status of Adrenocortical Tumors: Novel Pathogenetic Insights

  To investigate the relationship between transcriptome profile and genetic background in a large series of adrenocortical tumors and to identify new potential pathogenetic mechanisms, we performed transcriptome profiling by high-throughput sequencing. We collected snap-frozen tissue from patients with adrenocortical tumors (n = 59) with known genetic background: 26 adenomas with Cushing syndrome, 17 adenomas with mild autonomous cortisol secretion, 9 endocrine-inactive adenomas, 7 adrenocortical carcinomas. Additionally, we sequenced 4 control samples.

  Study EGAS00001004533

• High-depth whole genome sequencing of paired ductal carcinoma in-situ (DCIS) and germline control samples from 26 individuals.

  Deposited here are whole-genome sequencing data for 26 paired breast cancer DCIS and matched-normal samples taken from the same individual. Average sequence coverage is 118x for DCIS samples and 41x for matched-normals. Matched-normal samples are from blood. Sequencing was performed on an Illumina HiseqX. Due to specific restrictions imposed by the ethical approval at sample collection, the use of the germline data is restricted to filtering of somatic mutation calls only and cannot be used outside this purpose.They are a part of a broader project that uses high-depth WGS to investigate the somatic mutation genomic landscape of DCIS in order to uncover biological insights into breast cancer progression as well as possible methods to stratify DCIS patients for individualised therapy or disease monitoring.

  Dataset EGAD50000002237

• Breast Cancer Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of 26 primary breast cancers from Wu et al. (2021) study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001007495

• Human brain development single cell sequencing additional samples

  69 tissue samples from various parts of the developing human embryo brain were dissociated and single cells were collected and processed without bias for mRNA-seq using 10X chromium 3' protocol. Libraries were sequenced on Illumina NovaSeq and reads aligned against the human GRCh38 genome. This is an addition to EGAD00001006049 Human development single cell sequencing, consisting of samples added after the original submission to EGA, but included in final paper.

  Dataset EGAD50000001295

• SCLC study MGH - WES dataset

  For whole-exome sequencing 1 µg of DNA from fresh-frozen tumors was fragmented by sonication technology (for DNA from fresh-frozen tumors: Bioruptor, diagenode, Liѐge, Belgium; for DNA from FFPE material: Covaris). The fragments were end-repaired and adaptor-ligated, including incorporation of sample index barcodes. After size selection, libraries were subjected to an enrichment process with Sure select XT (Agilent). The final libraries were sequenced with a paired-end 2×75 bp protocol for an average coverage of 100-120x

  Dataset EGAD00001003970

• RNA-seq from time-course experiment treating cells for 72h

  RNA sequencing from MSTO-211H cell line cultures treated for 72h with vehicle solution, palbociclib 250nM, or abemaciclib 250nM (N = 3, each). RNA-seq prepared using TruSeq Stranded mRNA libraries and sequenced with Illumina HiSeq 4000. Data is in raw fastq format, paired end. Some samples have been split in two lanes, with a final count of 24 fastq files.

  Dataset EGAD00001007737

• WGS datasets of pediatric glioblastoma

  WGS with linked reads of pediatric glioblastoma. For each patient, blood and tumor tissue were sequenced. For two patients, we also provide sequencing data for the blood of their parents.

  Dataset EGAD00001005212

• DIPG WES and RNA-Seq

  We characterised H3K27M-mutant diffuse intrinsic pontine glioma (DIPG, n=21) and RNA-Seq (n=26 DIPG, 12 normal brain)

  Dataset EGAD00001006450

• RNA-seq and scRNA/TCR-seq data for publication: "Pharmacological inhibition of nonsense-mediated mRNA decay enhances anti-tumour immunity"

  PDFs RNA-seq and scRNA/TCR-seq data for Pharmacologic inhibition of nonsense-mediated mRNA decay enhances anti-tumour immunity

  Dataset EGAD50000001720

• WES of melanoma tumours prior to combined immune checkpoint blockade treatment.

  Paired melanoma tumor and normal (PBMC) WES data from a cohort of 26 patients subsequently treated with combined immune checkpoint blockade.

  Dataset EGAD00001005941

• Duplex sequencing of 26 genes

  Buccal samples and paired esophageal epithelium were obtained using the three sizes of swabs and endoscopic biopsy, respectively. Forty samples from 10 subjects were analyzed via duplex sequencing. This dataset contains bam files that were mapped to the GRCh37 reference genome.

  Dataset EGAD50000000998

• WGS

  Whole Genome Sequencing

  Dataset EGAD00001001120

• Somatic mutations in twin breast cancers (2019-04-03)

  The aim of this study is to investigate the somatic mutations in twins with BRCA1/2 negative breast cancer with no strong family history. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004890

• L1 Retrotransposon sequencing in Cocaine Use Disorder - Study 1

  Cocaine Use Disorder (CUD) is a global public health problem, with no effective pharmacotherapies. While CUD is marked by high heritability, discovery of variants associated with risk for CUD has proven difficult. We used Restriction Enzyme Based Enriched L1 sequencing (REBELseq) to amplify L1 retrotransposons in gDNA isolated from medial prefrontal cortex NeuN+ neuronal nuclei from 25 CUD cases and 26 controls. Amplified libraries were sequenced on the Illumina HiSeq 4000 platform, and sequencing data was analyzed with the REBELseq bioinformatics pipeline.

  Study phs001966

• Small‑scale mutations are infrequent as mechanisms of resistance in post‑PARP inhibitor tumour samples in high grade serous ovarian cancer

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 26 patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Study EGAS50000000146

• RNA-Seq of Myeloid Cells in Dendritic Cell Therapy Response

  RNA libraries were prepared from 100 ng of total RNA using the Illumina Stranded Total RNA Prep with Ribo-Zero Plus kit, then sequenced (2×150 bp) on the Illumina NextSeq550. Transcript-level quantification was done with kallisto, followed by gene-level summarization (tximport) and differential expression analysis (DESeq2). Quality control included PCA, hierarchical clustering, and deconvolution with CIBERSORTx to exclude non-myeloid genes. Final analyses identified transcriptomic differences among healthy donors and three patient subgroups based on response to dendritic cell therapy.

  Dataset EGAD50000001681

• RNAseq of human fetal pancreas development

  The dataset comprises RNA-seq information of 4 subpopulations sorted from human fetal pancreas of 3 different donors. Low input libraries were generated using the Smart-seq2 protocol after Ampure XP cleanup of the total RNA extracted from the sorted cells. Libraries were multiplexed and sequenced paired-end over 2 lanes of HiSeq4000 each. Raw data was aligned to the human genome refernence GRCh37 using STAR v2.5.1b with GENCODE v19 as transcriptome reference, and unaligned reads were folded into the final uploaded bams.

  Dataset EGAD00001004210

• Chromatin accessibility in human monocyte differentiation

  This dataset consists of ATAC-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting TET2, IRF4 and EGR2. In total, it includes 26 samples.

  Dataset EGAD00001006601

• Detection of cancers three years prior to diagnosis using plasma cell-free DNA

  A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

  Study EGAS00001008068

• Identification of intronic sequences promoting natural skipping of ABCA4 exon 15 using long-read transcriptomics and midigene assays

  Stargardt disease is an inherited retinal disease that leads to progressive loss of vision, and is caused by biallelic variants in the ABCA4 gene. A significant proportion of ABCA4 variants of variable penetrance affect pre-mRNA splicing. Previously, we observed the exclusion of certain ABCA4 exons into the final transcript in the absence of any disease-causing variants. In this study, we explored this phenomenon that we coined natural exon skipping (NES) for the entire ABCA4 transcript, using targeted RT-PCR analysis as well as long-read transcriptome sequencing of control retina samples. For the most abundant NES event, which is skipping of ABCA4 exon 15, overlapping ABCA4 deletion constructs were employed to identify responsible cis-regulatory sequence motifs. Subsequently, antisense oligonucleotides (AONs) were designed and tested to reverse NES and restore fully-spliced ABCA4 mRNA. We identified intronic regions on each side of exon 15 that, when deleted, increased the inclusion of exon 15 in the final transcripts. Interestingly, these motifs appear to work in a synergistic manner. Further fine-mapping of these regions revealed several cis-regulatory motifs that may be responsible for inducing NES, on each side of the exon. AONs targeting these motifs unfortunately did not decrease the skipping of exon 15. In conclusion, we discovered an intriguing phenomenon that, in the absence of disease-causing variants, results in the skipping of one or more exons in the ABCA4 transcript. These NES events appear to be regulated by cis-regulatory motifs within the flanking introns. This work captured the extend of NES throughout ABCA4 transcript and the role of cis-regulatory motifs in pre-mRNA splicing.. The use of AONs targeting cis-regulatory motifs is an innovative strategy for splicing modulation, suitable for complementing future variant-specific splicing modulation therapies in ABCA4 retinopathies.

  Study EGAS50000000071

• Single cell RNAseq of stenotic, inflamed and non-inflamed transmural lesions from patients with Crohn's disease

  This dataset contains a gene-cell matrix derived from single-cell RNA sequencing (scRNA-seq) data of ileal tissue from Crohn's disease (CD) patients and colorectal cancer (CRC) patients. It includes: Crohn's Disease Patients: A trio of transmural lesions (stenotic, inflamed, and non-inflamed) from each patient. Colorectal Cancer Patients: Unaffected ileal tissue used as external non-inflamed control. Cell Level Metadata: The dataset includes relevant cell-level metadata such as cell type annotations used in the study. Experimental Details: Platform: 10x Genomics Chromium Single Cell 3' GEX Sequencing: Illumina NovaSeq Processing: Data processed with Cell Ranger software. Resulting count matrices were merged for downstream analysis, including integration and dimensionality reduction. Dataset Composition: Crohn's Disease Patients: 10 patients with 3 samples each (non-inflamed, inflamed, stenotic), totaling 30 samples. Colorectal Cancer Patients: 5 patients with 1 sample each of unaffected tissue, totaling 5 samples. Data Provided: Merged Raw Count Matrix: The final merged raw count matrix used for downstream analysis. Cell Metadata File: Contains details of sample, tissue, and patient for each cell in the count matrix. Barcodes File: Indicate each cell barcode which also encodes the sample, tissue, and patient details for each cell. CD.S_Inf: Stenotic Corhn's disease inflamed samples CD.S_Sten: Stenotic CD patient stenosis sample CD.S_Prox: Stenotic CD Patient - proximal non-inflamed sample CC.C_Prox: CRC Patient proximal unaffected sample eg: A barcode 'CC.C_1_Prox_AAGTCGTAGACCCTTA' indicates CRC Patient unaffected proximal sampe from CRC Patient no.1 and the nucleic acid sequence indicate a unique cell from this sample. Total Samples: Crohn's Disease (CD) Patients: 30 samples Colorectal Cancer (CRC) Patients: 5 samples Patient_no Sample Sample_type 1 CC.C_1 CC.C_1_Prox CC.C_Prox 2 CD.S_1 CD.S_1_Prox CD.S_Prox 3 CD.S_1 CD.S_1_Infl CD.S_Infl 4 CD.S_1 CD.S_1_Sten CD.S_Sten 5 CC.C_2 CC.C_2_Prox CC.C_Prox 6 CD.S_2 CD.S_2_Prox CD.S_Prox 7 CD.S_2 CD.S_2_Infl CD.S_Infl 8 CD.S_2 CD.S_2_Sten CD.S_Sten 9 CC.C_3 CC.C_3_Prox CC.C_Prox 10 CC.C_4 CC.C_4_Prox CC.C_Prox 11 CD.S_3 CD.S_3_Prox CD.S_Prox 12 CD.S_3 CD.S_3_Infl CD.S_Infl 13 CD.S_3 CD.S_3_Sten CD.S_Sten 14 CD.S_4 CD.S_4_Prox CD.S_Prox 15 CD.S_4 CD.S_4_Infl CD.S_Infl 16 CD.S_4 CD.S_4_Sten CD.S_Sten 17 CC.C_5 CC.C_5_Prox CC.C_Prox 18 CD.S_5 CD.S_5_Prox CD.S_Prox 19 CD.S_5 CD.S_5_Infl CD.S_Infl 20 CD.S_5 CD.S_5_Sten CD.S_Sten 21 CD.S_6 CD.S_6_Prox CD.S_Prox 22 CD.S_6 CD.S_6_Infl CD.S_Infl 23 CD.S_6 CD.S_6_Sten CD.S_Sten 24 CD.S_7 CD.S_7_Prox CD.S_Prox 25 CD.S_7 CD.S_7_Infl CD.S_Infl 26 CD.S_7 CD.S_7_Sten CD.S_Sten 27 CD.S_8 CD.S_8_Prox CD.S_Prox 28 CD.S_8 CD.S_8_Infl CD.S_Infl 29 CD.S_8 CD.S_8_Sten CD.S_Sten 30 CD.S_9 CD.S_9_Prox CD.S_Prox 31 CD.S_9 CD.S_9_Infl CD.S_Infl 32 CD.S_9 CD.S_9_Sten CD.S_Sten 33 CD.S_10 CD.S_10_Prox CD.S_Prox 34 CD.S_10 CD.S_10_Infl CD.S_Infl 35 CD.S_10 CD.S_10_Sten CD.S_Sten

  Dataset EGAD50000000559