23144 results for "ega"

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• GTestimate: Improving relative gene expression estimation in scRNA-seq using the Good-Turing estimator

  This study introduces a novel scRNA-seq normalization method, which takes unobserved genes into account. To validate GTestimate we designed a cell targeted amplification strategy, enabling us to sequence a small set of cells twice, once at a "typical" sequencing depth and once at a "ultra-deep" sequencing depth.

  Study EGAS50000000915

• Investigation of 3D chromatin structure in clear cell renal cell carcinoma

  In order to investigation the 3D chromatin structure in clear cell renal cell carcinoma (ccRCC), we performed ultra high-resolution chromatin capture using MNase (Micro-C) in 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and the chromatin interactions in hic format. Data were processed using the Juicer pipeline.

  Dataset EGAD50000001884

• Investigation of chromatin accessibility in clear cell renal cell carcinoma using ATAC-seq

  To identify regions of open and accessible chromatin in clear cell renal cell carcinoma (ccRCC), we performed ATAC-seq on the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and processed narrowPeak fomats. Data were processed using the nf-core atacseq pipeline.

  Dataset EGAD50000001885

• Epigenetic analysis of clear cell renal cell carcinoma using ChIP-seq

  To investigate the epigenetic landscape of clear cell renal cell carcinoma (ccRCC), we performed ChIP-seq data for the CTCF, H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3, and HIF1A marks in the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as the HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and narrowPeak formats. Data were processed using the nf-core chipseq pipeline.

  Dataset EGAD50000001886

• WGS data of conditional knockout mouse model mammary tumours

  Deposited here are 56 whole-genome sequencing BAM files from 15 Trp53f/w, 12 Trp53f/f, 14 Brca1f/f Trp53f/w, and 15 Brca1f/f Trp53f/f mouse mammary tumor samples sequenced on Illumina NovaSeq PE150. An additional 6 whole genome sequencing BAM files from corresponding normal tissues of mice are also included as controls (BPC_D666, B1PC_D840, BPTC_D992, PC_D503, PC_D720_Kid, PTC_H531). All samples were used in the study “Insights into BRCA1 and TP53 associated breast cancer development from integrated whole genome analysis of mouse model mammary tumors, Huo et al., 2026.”

  Dataset EGAD50000002036

• A distinct monocyte cellular state links systemic immune dysregulation to pulmonary impairment in long COVID

  This is an independent cohort of Long COVID patients recruited from a rehabilitation centre. These patients had Long COVID from 8 months to more than 2 years since their acute COVID-19 disease. PBMC from these patients were collected and single cell transcriptomics dataset was generated.

  Study EGAS50000001216

• WES

  Genomic DNA was extracted from PBMCs and whole blood using the Chemagic Prime DNA Blood 4k kit. DNA quality and integrity were assessed by Qubit and Tapestation, and only samples with sufficient quantity, DIN > 6, and confirmed sex were used. Whole-exome libraries were prepared with the SureSelect XT Human All Exon V8 kit (Agilent), covering all human protein-coding regions. DNA was fragmented, adapter-ligated, captured, and amplified following the manufacturer’s protocol. Libraries were quantified, pooled (95 samples), and sequenced on an Illumina NovaSeq 6000 using S4 flow cells, generating up to 12 billion paired-end reads per run.

  Dataset EGAD50000002037

• Transcriptome data of WS patients and controls

  Fibroblasts of 4 WS patients and 4 sex matched controls were transformed into iPSCs, which were then differentiated to Neuroepithelial Stem Cells (NESCs), and further differentiated into neurons. RNA sequencing was performed at the NESC stage and after 4 and 8 weeks of neural development for 3 replicates per individual using the Illumina TruSeq stranded library polyA method on the NovaSeq6000 platform at NGI Stockholm. The data was preprocessed using the nf-core/rnaseq (https://nf-co.re/rnaseq) that includes quality control, data cleaning, and read alignment to GRCh38 (STAR, v2.6.1d)

  Dataset EGAD50000001728

• Molecular classification of small intestinal adenocarcinomas

  In this study we analyzed genomic and transcriptomic data from 135 small intestinal adenocarcinoma (SIA) patients. Through this analysis, we identified three distinct subtypes based on gene expression patterns, revealing the diverse molecular characteristics among SIA patients. Our findings provide comprehensive insights into the unique features of each subtype.

  Study EGAS50000001238

• The Celiac Gene Expression Data Access Committee

  This study presents RNA sequenced from several intestinal phenotypes such as from patients with damaged intestinal mucosa as well as from those without a damaged intestine but still an autoantibody response to tissue transglutaminase (“potential celiac disease”) or those with treated celiac disease. By combining phenotypes in a much larger number of tissue samples from both peripheral blood and mucosal biopsies, we found highly differentially expressed genes, but also identify genes involved in controlling and triggering celiac disease associated changes. This study identifies molecular mechanisms involved in celiac disease and new possible targets for treatment and for identification of individuals at risk.

  Dac EGAC50000000630