12069 results for "cancer rna-seq"

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• Human Paraganglioma

  This dataset comprises single-nucleus transcriptomic profiles from 9 human paraganglioma samples. Nuclei were isolated and processed using the SMART-Seq2 protocol to enable full-length, high-resolution RNA sequencing at the single-nucleus level. cDNA libraries were generated and sequenced on the Illumina HiSeq 2500 platform. The resulting raw sequencing data are provided as .fastq files for downstream analysis.

  Dataset EGAD50000001689

• Lymphoma_primary_patient_drug_perturbed_RNASeq_samples

  3'-end low-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule inhibitors (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET-762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). Sequencing was performed on the Illumina HiSeq4000. The dataset contains FASTQ files.

  Dac EGAC50000000578

• DCIS_FF_RNAseq

  This RNAseq dataset contains full transcriptome data on n=77 pure DCIS samples. The RNA is derived from fresh-frozen DCIS samples, obtained from two hospital based cohorts (NKI cohort and Oslo cohort). The libraries were sequenced with 54 bp paired end reads using a Novaseq instrument (Illumina). We share fastq data files of paired end sequencing (two files per sample).

  Dataset EGAD50000002123

• 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.

  Dataset EGAD00001005807

• MPM patients

  - RNA-sequencing data: 5 normal pleurae and 40 malignant pleural mesotheliomas - Targeted DNA-sequencing of the 165 genes included in the “Solid and Haematological tumors” panel (BRIGHTCore, Brussels, Belgium): 6 MPM samples. 2 FASTQ files for each sample (paired).

  Dataset EGAD00001008740

• Transcriptional programming in whole blood reveals changes in pro-inflammatory phenotype explained by changed food and changed life style.

  We here focused on whole blood from paxgene tubes from healthy Tanzanians and the impact of urbanization and diet on innate immune responses. We performed RNA-sequencing of whole blood from paxgene tubes from healthy Tanzanians and investigate that transcriptional changes depend of diet and location.

  Dataset EGAD00001006051

• Paired healthy & tumor organoid Biobank _B16PON

  Organoid cultures derived from colorectal adenomas. RNA and DNA was isolated from these cultures for genome wide profiling.

  Dataset EGAD00001008949

• 4_eCLIP_NOVA1_NOVA2_RBFOX2

  eCLIP of NOVA1, NOVA2 and RBFOX2 from iPSC-derived motor neurons in 2 control lines. Per line and RNA-binding protein input and IP samples and analysis including bigWig files and peak files.

  Dataset EGAD00001008428

• 2 10X multiomics (RNA+DNA) gray matter brain controls donors

  Single cell multiomics from 2 donor controls, expression and chromatin accessibility. Samples belong to gray matter tissue from the brain.

  Dataset EGAD00001008457

• Sequencing data for oesophageal and related samples - Nowicki-Osuch, Zhuang et al (bulk RNA)

  Data supporting: “Deep molecular phenotyping reveals the identity of Barrett’s esophagus and its malignant transition.” Nowicki-Osuch, Zhuang et al. RNAseq (BAM files) 241 tumour samples

  Dataset EGAD00001005388

• Sequencing data for Hepatoblastoma samples

  This dataset contains DNA sequencing data for twelve hepatoblastoma tumor samples, four of which have matched normals. Nine of the samples also have RNA sequencing data from the tumor sample. The dataset comprises six samples from patient tissues and six from cell lines; see metadata for details.

  Dataset EGAD00001006621

• RNAseq in ASD patients and controls

  RNA sequences of a total of 24 samples, including 13 unrelated ASD patients (13 males) and 11 adult individuals of Spanish origin as controls (4 males, 7 females). The RNAseq study was conducted on a HiSeq 4000 (Illumina) and paired-end sequences were obtained (fastq files).

  Dataset EGAD00001008160

• 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

• Natural Killer Cell Plasticity During IL-15-driven Homeostatic Proliferation

  Here we performed single-cell RNA sequencing to address repertoire stability and subset plasticity during IL-15 driven homeostatic proliferation. Sorted NK cell subsets representing discrete stages of NK cell differentiation are compared with the corresponding subsets after proliferation and further sorted into two subsets depending on the rate of proliferation.

  Dataset EGAD00001005420

• TN

  In order to comprehensively investigate the genetic relationship between PTC tumors and benign nodules, we totally collected 127 fresh-frozen biopsies samples from 28 patients with concurrent thyroid benign nodule and PTC (n=20) or simple benign nodule (n=8). We carried out whole-exome sequencing on all the 127 biopsies samples and RNA-sequencing in total of 40 samples.

  Dataset EGAD00001003351

• Newborn Screening Translational Research Network (NBSTRN): Newborn Sequencing in Genomic Medicine and Public Health (NSIGHT2)

  Large-scale studies of whole genome sequencing (WGS) in neonates have largely been neglected. Thus, the clinical and social implications of this absence are largely unknown. The proposed study aims to increase scientific knowledge for acutely ill neonates. This population may stand to benefit largely from WGS given the severity of illness. The proposed clinical study is a prospective, randomized, partially-blinded study that has both quantitative and qualitative assessments of the risks and benefits of the use of STATseq, a 2-day genome test, in acutely ill neonates at Children's Mercy Hospital. Study participants include neonates, their parents, and clinicians caring for them. The overall aims will provide a nuanced understanding of the role of rapid diagnostic WGS for acutely ill neonates, including relative diagnostic sensitivity and change in management both for broad NICU populations and subpopulations, accuracy, reproducibility, and relative value of proband WGS and familial triads. The technological aims include improving diagnostic sensitivity without sacrificing the rapid turnaround time. The clinical aims include looking at increased diagnostic yield, shorter time to diagnosis and clinician perception of management changes that result from implementation of STAT-seq. Finally, the study will investigate the perceived value of STAT-seq in parents and clinicians using structural equation modeling. The studies also are designed for long-term continuation of assessment of the enrollees (beyond the current funding period) and in additional sample types (via a biorepository). Long-term continuation studies will test effects on long-term morbidity, mortality, quality of life and cost of care. We hope that the study results will be sufficient to provide an evidence base for physician adoption and provider reimbursement of WGS in Level 3 and 4 NICUs.

  Study phs002094

• Aberrant Activation of Wound Healing Programs within the Metastatic Niche Facilitates Lung Colonization by Osteosarcoma Cells

  Lung metastasis is responsible for nearly all deaths caused by osteosarcoma, the most common pediatric bone tumor. How malignant bone cells coerce the lung microenvironment to support metastatic growth is unclear. This study delineates how osteosarcoma cells educate the lung microenvironment during metastatic progression.Using single-cell transcriptomics (scRNA-seq), we characterized genome– and tissue-wide molecular changes induced within lung tissues by disseminated osteosarcoma cells in both immunocompetent murine models of metastasis and patient samples. We confirmed transcriptomic findings at the protein level and determined spatial relationships with multi-parameter immunofluorescence. We evaluated the ability of nintedanib to impair metastatic colonization and prevent osteosarcoma-induced education of the lung microenvironment in both immunocompetent murine osteosarcoma and immunodeficient human xenograft models.Osteosarcoma cells induced acute alveolar epithelial injury upon lung dissemination. scRNA-seq demonstrated that the surrounding lung stroma adopts a chronic, non-resolving wound-healing phenotype similar to that seen in other models of lung injury. Accordingly, metastasis-associated lung demonstrated marked fibrosis, likely due to the accumulation of pathogenic, pro-fibrotic, partially-differentiated epithelial intermediates. Inhibition of fibrotic pathways with nintedanib prevented metastatic progression in multiple murine and human xenograft models. Our work demonstrates that osteosarcoma cells co-opt fibrosis to promote metastatic outgrowth. When harmonized with data from adult epithelial cancers, our results support a generalized model wherein aberrant mesenchymal-epithelial interactions are critical for promoting lung metastasis. Adult epithelial carcinomas induce fibrotic pathways in normal lung fibroblasts, whereas osteosarcoma, a pediatric mesenchymal tumor, exhibits fibrotic reprogramming in response to the aberrant wound-healing behaviors of an otherwise normal lung epithelium, which are induced by tumor cell interactions.

  Study phs003569

• Asian Immune Diversity Atlas (AIDA) sQTL

  Current efforts within the Human Cell Atlas (HCA) are largely focused on defining reference human cell types using a relatively small number of samples of predominantly European origin. However, the next phase of the HCA is likely to address the topic of human diversity by comprehensively characterizing variation in cell states across age, sex, population groups, diseases and environments. To spur this next phase, and also expand the geographical scope of the HCA, we propose an HCA-Asia seed network to generate an Asian Immune Diversity Atlas (AIDA). AIDA will generate transcriptome variation datasets from 5 major Asian population groups (Chinese, Japanese, Korean, Indian, Malay), define an atlas of Asian cell types and states, and characterize their variation associated with ethnicity, age and sex. We will also formalize a study design based on common controls that can in principle reduce technical artifacts in a broad range of comparative single cell studies. This study design will be complemented with novel algorithms designed to normalize datasets of interest against the common controls, to increase the robustness of biological inferences. In addition to providing new tools and resources to the HCA, this seed network will serve as a template for future comparative studies in the single cell field.The AIDA dataset consists of scRNA-seq (10x 5′ v2 scRNA-seq) and genotype (Illumina Infinium Global Screening Array v.3) data. In the AIDA splicing quantitative trait loci (sQTL) project, we identified 11,577 independent cis-sQTLs, 607 trans-sQTLs, and 107 dynamic sQTLs. The post-imputation genotype for the Japanese and Korean cohort will be available through dbGaP. The Singaporean (ethnically Chinese, Indian and Malay) genotypes require a data access application to the HELIOS Data Access Committee (helios_science@ntu.edu.sg). European samples are used as control.

  Study phs003848

• Reconstructed VDJ sequences from Smart-seq2 data

  The dataset contains reconstructed VDJ sequences (fasta files) and accompanying metadata for each cell (csv file) from scRNA-seq data generated with the Smart-seq2 protocol. The VDJ sequences were reconstructed with the computational tool BraCeR using raw fastq files as input. The dataset contains sequences from 355 IgA+ peripheral blood B-lineage cells of two untreated celiac disease patients. The sequences comprise both IgA+ transglutaminase 2-specific and other IgA+ B cells.

  Dataset EGAD50000000341

• 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

• Dynamics of checkpoint receptors in γδ T cell subsets are associated with clinical responses during anti-PD-1 immunotherapies

  scRNA-seq data from circulating gamma delta T cells derived from healthy donors and patients with stage IV melanoma that either responded or did not respond to anti-PD-1 monotherapy or anti-PD-1 and anti-CTLA-4 combination therapy. This dataset includes paired samples from these patients before and 3 months after the start of immunotherapy.

  Dataset EGAD50000001812

• Dataset contains all Single cell RNAseq data of human neurons from the study Bouwen et al Nat Comm 2025

  These documents contain the patch seq data presented in the Bouwen et al Nat Comm 2025. Human brain samples were gathered during surgery, neurons were isolated using patch clamp glass pipette. Isolated cells were processed using Smartseq2 pipeline, and sequenced using an Illumina 2500. Files are formatted in fastq format. There are a total of 12 patient samples, each with 2 replication runs.

  Dataset EGAD50000001979

• Log2-CPM (voom)-normalised read-count matrix of the RNAseq Datasets of CLUSTER JIA pre-MTX cohort

  Samples were sequenced with NovaSeq6000 and the sequencing files were processed using the RSSnextflow workflow (https://gitlab.com/b8307038/rssnextflow). The raw read counts from all batches were combined. Analysis-ready batch-corrected read counts were generated using ComBat-seq. Read counts normalisation for DGE analysis was performed with limma-voom function (log2 CPM) as seen in the pipeline.

  Dataset EGAD50000002170

• DAC for "Transcriptome analysis of human iPSC-derived microglia in a novel human 3D cortical tissue model"

  scRNA-seq analysis of human iPSC-derived microglia in a novel, human in vitro 3D cortical tissue model. Samples include three distinct conditions (each as biological duplicates): wild-type microglia extracted from cultures after 1 month (WT_1mo) and 3 months (WT_3mo) of culturing, as well as knock-in microglia extracted from cultures carrying three familial AD mutations in the APP gene (Swedish, Iberian, Arctic; introduced by CRISPR/Cas9-mediated knock-in) after 3 months of culturing (KI_3mo).

  Dac EGAC50000000303

• McGill EMC Community projects Release 7 for cell line "lung epithelial"

  Complete reference epigenome (as defined by IHEC) of a lung epithelial cell line with non-small Cell Lung Adenocarcinoma

  Dataset EGAD00001007679