12213 results for "cancer rna-seq"

in 61.47 milliseconds.

• RNA-Seq studies of Gene Expression in Cells and Networks in FI and ACC in Autism

  RNA-Seq studies of Gene Expression in Cells and Networks in FI (fronto-insular) and AC (anterior cingulate) cortex in Autism. We seek to understand the cellular bases of autism by using a new technology, RNA-Seq, to determine differences in gene expression in autopsy brains of subjects with well described autism versus age and sex matched neurotypical individuals. We have investigated two specific cortical areas involved in self-awareness and social reciprocity which are abnormal in autism and have found increased expression in a network of genes related to inflammation in autism group A, whereas the remaining cases, autism group B, have increased expression in a network of genes related to synapses. The current dbGaP study release includes RNA sequencing and phenotype data of n=27 subjects of African - American, Caucasian, or Hispanic origin.

  Study phs000609

• G-SAM: Transcriptional Evolution of Glioblastomas Treated With Standard of Care

  Collection of mostly matching primary and recurrent glioblastoma RNA-seq sample pairs, also matching with an earlier DNA sequencing study

  Study EGAS00001005436

• RNA-seq dataset for two NUP98-Rearranged Acute Myeloid Leukemia PDX samples

  This dataset includes RNA-seq of two patient-derived xenograft (PDX) samples with NUP98-Rearranged Acute Myeloid Leukemia. Bam files are provided for each sample.

  Dataset EGAD50000001564

• Bulk RNA-seq data of isogenic wild-type RPE1

  Deposited here are time series (6, 24 and 48hrs) bulk RNA-seq data generated from isogenic wild-type (WT) RPE1 untreated or treated with Brequinar (and other dNTP-pool disruptor compounds)

  Dataset EGAD50000001544

• Uveal melanoma whole genome sequencing, SNP arrays and RNA-seq

  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.

  Dataset EGAD00001000372

• Epigentic sequence data of monocytes and macrophages

  Data for paper: Epigenetic dynamics of monocyte to macrophage differentiation with Chip Seq, NOMe, mRNA, total RNA, noncoding RNA, whole genome bisulfite seq,

  Dataset EGAD00001002201

• RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  Dataset EGAD00001006329

• Human tumor bulk RNA-seq

  We profiled 9 high-grade gliomas patient tumor samples by bulk RNA-seq. The raw fastqs are provided.

  Dataset EGAD00001008348

• RNA-Seq data for manuscript titled: A sporadic Alzheimers blood-brain barrier model for developing ultrasound-mediated delivery of Aducanumab and anti-Tau antibodies

  RNA-Seq data for manuscript titled: A sporadic Alzheimers blood-brain barrier model for developing ultrasound-mediated delivery of Aducanumab and anti-Tau antibodies

  Dataset EGAD00001008670

• Dataset for RNA and Exome sequencing of Glioblastoma samples

  This dataset contains RNA Seq, 10x scRNA Seq and Exome sequencing of glioblastoma samples. Sequencing was performed on a Illumina NovaSeq 6000 and Illumina HiSeq 4000. The sequencing was always paired.

  Dataset EGAD00001012235

• RNA-seq data of patients with glioblastoma IDH-wt (CNS WHO grade 4) with matched primary and relapse samples.

  Between January 1st, 2016, and December 31th, 2021, patients with glioblastoma IDH-wt (CNS WHO grade 4) were included. RNA-seq was performed in a subset of patients.

  Dataset EGAD00001015683

• CLL RNA-seq

  This dataset contains Illumina stranded RNA-seq from of 19 chronic lymphocytic leukemia (CLL) patients with or without mutation in SF3B1, as well as 6 B cell samples from healthy individuals. RNA was extracted from CLL cells.

  Dataset EGAD50000000078

• Ewings Sarcoma RNA-seq drug sensitivity

  Illumina RNA-Seq will be performed on four Ewing's sarcoma cell lines and two control cell lines. RNA was extracted from all the lines using a basic Trizol extraction protocol.

  Dataset EGAD00001000337

• Paired RNA seq of wild type VDH15 cells (3 replicates) - a cell line of oral squamous cell carcinoma (OSCC)

  Paired RNA seq of wild type VDH15 cells (3 replicates) - a cell line of oral squamous cell carcinoma (OSCC). RNA was extracted and sequencing libraries were prepared using TruSeq Stranded mRNA Library Prep Kit following manufacturer's protocol. The sequencing was done using Illumina Novaseq 6000.

  Dataset EGAD00001010172

• Genetic and epigenetic analysis of individuals with porokeratosis

  We performed genome sequencing���including whole-exome sequencing (WES), whole-genome sequencing (WGS), long-read WGS, and amplicon-seq���along with SNP array, methylation array, and RNA-seq on samples of epidermis (both lesion and non-lesion), peripheral blood, and/or cultured keratinocytes from individuals with porokeratosis.

  Study JGAS000684

• Molecular profiling of acinar cell carcinoma of the salivary glands

  Samples of acinar cell carcinoma (AciCC) of the salivary glands and paired normal salivary gland tissue were analyzed by whole transcriptome RNA-seq (n=10), whole genome sequencing (n=6), whole genome bisulfite sequencing (n=3) and ChIP-seq (H3K27ac, H3K4me3, H3K27me3, NR4A3, CTCF).

  Study EGAS00001002795

• IBC RNA-seq

  RNA sequencing of IBC patients

  Dataset EGAD00001011649

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  Dac EGAC00001000891

• Differential Transcription Start Site Usage in Brain-related Samples

  RNA-Seq is an effective method to study the transcriptome, but specialized methods are required to identify 5' ends of transcripts. Several published strategies exist for this specific purpose, but their relative merits have not been systematically analyzed. Here, we directly compare the performance of six such methods - testing five with cellular RNA as well as a novel spike-in RNA assay that helps address interpretation challenges that arise from uncertainties in annotation or RNA processing. Using a single human RNA sample, we constructed and sequenced 18 libraries with these methods and one standard, control RNA-Seq library. We find that the CAGE method performed best for mRNA and that most of its unannotated peaks are supported by evidence from other genomic methods. We then applied CAGE to eight brain-related samples and revealed sample-specific transcription start site (TSS) usage as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.

  Study phs001463

• Identification of Novel Immunotherapy Targets in Myeloma

  RNA sequencing (RNA-Seq) was performed on 94 multiple myeloma (MM) patient samples. We used genomic subgroup and high-risk markers to identify therapeutic targets, including TNFRSF17, GPRC5D, ITGA4, and LAX1, with low predicted toxicity and high specificity to MM and genomic subgroups such as those with TP53 alterations.

  Study phs003772

• RNA-seq from Glioblastoma treated with Indisulam

  The dataset includes RNA-sequencing results from four patient-derived glioblastoma cell lines treated with DMSO (vehicle control) or the splicing modulating-drug indisulam (at 6 and 16 hours), resulting in 12 RNA-seq samples. Paired-end sequencing produced 24 FASTQ.gz files. The RNA libraries were prepared using PolyA selection and ERCC spike-ins and sequenced on a NovaSeq platform. This dataset supports the analysis of drug-induced transcriptomic changes and the prediction of subsequent non-canonical tumor-specific antigens (ncTSAs) using the NovumRNA pipeline.

  Dataset EGAD50000000957

• RNA sequencing of tumor samples from patients with BPLL

  RNA-Seq was performed on 12 samples of sorted CD19+ tumor cells. RNA-Seq libraries were prepared using the SureSelect Automated Strand Specific RNA Library Preparation Kit as per manufacturer’s instructions (Agilent technologies) and subjected to paired-end (2 x 100 bp) sequencing on HiSeq2000 (Illumina). The files are in FASTQ format.

  Dataset EGAD00001004412

• Whole genome sequencing, single-cell RNA sequencing, and ATAC sequencing of mesothelioma (patient, patient-derived xenograft and cell line)

  Malignant pleural mesothelioma is an aggressive pleural tumor with a poor prognosis, and elucidating its molecular mechanisms is essential for improving diagnosis and treatment. This study investigates key genes and pathways involved in tumor progression, with particular attention to the involvement of neutrophils in the tumor ecosystem of mesothelioma. We performed whole-genome sequencing and single-cell RNA sequencing (scRNA-seq) of one pleural mesothelioma tumor specimen, scRNA-seq of matched patient-derived xenograft tumors, scRNA-seq of mesothelioma-free pleural tissues from three patients, and assay for transposase-accessible chromatin using sequencing (ATAC-seq) of a patient-derived cell line.

  Study JGAS000859

• Epigenetic profiling of colorectal cancer initiating cells (CC-ICs) to identify bivalently marked genes (H3K4me3 and H3K27me3 ChIP-seq), and investigation of changes in transcriptome following EZH2 inhibition using RNA-seq.

  Epigenetic regulation of transcription plays a crucial role in lineage commitment of embryonic stem cells. Promoters of key lineage-specific differentiation genes are found in a repressed bivalent state, having both activating H3K4me3 and repressive H3K27me3 histone marks, making them poised for transcription upon loss of H3K27me3 in response to environmental cues. Whether the tumour-initiating, self-renewing, cancer-initiating cells (C-ICs) have similar epigenetic regulatory mechanism that prevent lineage commitment is unknown. In order to investigate bivalently marked and repressed promoters, we used a patient-derived CC-IC enriched model to identify the changes in transcriptome following inhibition of EZH2, the H3K27 methyltransferase. We also performed ChIP-seq for H3K27me3 and H3K4me3 at baseline in order to identify repressed and bivalently marked promoters.

  Study EGAS00001003003

• Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia

  Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41).  Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

  Dataset EGAD00001009304

• single cell RNA-seq of small cell lung cancer circulating tumor cells

  This study investigated the transcriptomic profile of circulating tumor cells from three small cell lung cancer patients. CTCs were enriched from the blood of three SCLC patients using the CTC-iChip followed by magnetic depletion of RBCs. The enriched samples were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system.

  Study EGAS50000001401

• A Phase 2 Study of Lamivudine in Patients with p53 Mutant Metastatic Colorectal Cancer

  This was an open-label, single-arm Phase II study of lamivudine in patients who had progressed on systemic therapy for advanced colorectal cancer with TP53 mutations. The phase II study had a two-stage design, with a target accrual of 20 evaluable patients for the first stage and a total of 32 patients for the whole study. The first 9 patients were treated with lamivudine at 150 mg PO bid continuously for 28-day cycles. Subsequent patients (10-32) received a higher dose of 600 mg PO bid continuously for 28-day cycles. Tumor assessments were performed every 8 weeks until documented disease progression by Response Evaluation Criteria in Solid Tumors (RECIST) or drug intolerance. Whole genome sequencing (WGS) and total RNA-seq were performed on pre- and post- treatment biopsies on this trial.

  Study phs002833

• Acute myeloid leukemia single cell RNA-seq (Diagnosis and Relapse)

  To gain insight into the clonal heterogeneity of diagnosis (Dx) and relapse (Re) pairs, we employed single-cell RNA-seq (SORT-seq) to longitudinally profile two t(8;21) (AML1-ETO = RUNX1-RUNX1T1), and four FLT3-ITD AML cases. All the samples are Bone marrow aspirates.

  Dataset EGAD00001008373

• Transcriptional Profiling of Macrophages In Situ in Metastatic Melanoma Reveals Localization-Dependent Phenotypes and Function

  Therapeutic interventions modulating immune function at the tumor site could improve outcomes in cancer. Here we analyzed metastatic melanoma, a tumor type highly responsive to T-cell based therapies, and found that the tumor-infiltrating T cells are localized closely to CD14+ monocytes/macrophages rather than to melanoma cells. Using novel immunofluorescence-guided laser capture micro-dissection, we analyzed transcriptomes of CD3+ T cells, CD14+ monocytes/macrophages and melanoma cells in non-dissociated tissue. CD14+ cells localized in tumors beds displayed specific transcriptional signatures distinct from CD14+ cells that were localized in tumor stroma.The 8 distinct metastatic melanoma samples are from the Cooperative Human Tissue Network (CHTN). 64 RNA-seq files are available from 16 intraCD14+, 16 stromaCD14+, 16 cancer cells, 8 intraCD3+ and 8 stromaCD3+ cells. 2 LCM harvests were completed for the CD14+ and cancer cells on two sections of the samples. One harvest was done for the CD3+ samples.The processed data (TPM/raw counts tables) are available on GEO under GSE180124. 

  Study phs002564

• Development of the prevention and therapy of CRC using patient derived culture tissues.

  Tumor tissues consist of functionally heterogeneous cells including those with high clonogenic potential called cancer stem cells (CSCs) which produce differentiated non-tumorigenic progenies. Transplantation assays have been performed to identify cell surface markers in solid tumors including colorectal cancers, which identified several CSC markers such as CD133 and CD44. In addition to the transplantation, the lineage tracing of genetically labelling cells in animal models of cancer qhas been employed to explore the cellular heterogeneity of tumors by identifying the CSCs and its progenies. This approach is particularly useful to investigate solid tumors, where cellular proliferation and differentiation are controlled by niche factors and cell-cell contact with adjacent cells. Lineage tracing of mouse model of cancer unravel the mode of growth of autochthonous tumor in their native environment. In this study, we used patient derived organoids (PDO) established from surgically resected CRC patients to identify the CSC. Single cell RNA-seq analysis identified potential CRC markers, which may exhibit self-renewal activity and produce progenitors

  Study JGAS000139

• Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

  Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

  Study EGAS00001004335

• Gene_regulation_of_human_CD4__Treg_cells_

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs). It includes whole genome sequence data for ChM-seq (118 H3K4me3, 118 H3K27ac and 6 inputs), ATAC-seq (114 samples) and whole transcriptome (141 samples). All individuals were genotyped (130 samples) using coreExome Illumina SNP chip array. The final quality filtered set included 123 individuals with RNA-seq data, 73 with ATAC-seq, 91 with H3K27ac ChM-seq and 88 with H3K4me3 ChM-seq data. A total of 62 individuals had QCed data for all the assays.

  Study EGAS00001003516

• Massively Parallel Single-Cell RNA-Sequencing of Chronic Rhinosinusitis Nasal and Sinus Tissue

  Single-cell RNA sequencing (scRNA-seq) using the SeqWell V1 platform on sinus mast cells flow cytometrically sorted from the nasal polyps of patients with chronic rhinosinsusitis (CRS) with nasal polyps (CRSwNP) and aspirin-exacerbated respiratory disease (AERD).

  Study phs002333

• Single cell RNA sequencing of lung adenocarcinoma.

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes.

  Study EGAS00001003681

• RNA-seq from in vivo experiments

  RNA sequencing from 12 xenografts implanted using MSTO-211H cell line and treated with vehicle solution, cisplatin + pemetrexed, or palbociclib (N = 4, 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 34 fastq files.

  Dataset EGAD00001007739

• Paired RNA-Seq for Sarcoma tumors

  Paired RNA-Seq of 199 samples of Sarcoma tumors. The sequencing was done mostly on HiSeq 4000 with Illumina TruSeq Stranded mRNA, ist was also done on NovaSeq 6000 using the same kit. Very few samples were sequenced on HiSeq X Ten with Illumina TruSeq RNA or Illumina TruSeq Stranded mRNA.

  Dataset EGAD00001010256

• Processed RNA-seq data for clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

  ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint. This dataset includes the TPM and raw counts tables.

  Dataset EGAD00001006199

• ScRNA-seq of 6 human FL

  Follicular lymphoma (FL) is an indolent cancer of mature B-cells but carries increased risk of transformation to a more aggressive histology over time. We present here comprehensive profiling both tumor and immune compartments in 6 diagnostic FL biopsies by single-cell RNA sequencing. This confirmed results from 155 FL tumors characterized by mass cytometry (CyTOF) which revealed two distinct evolutionary trajectories with disparate risk of transformation and alternate biologies.

  Dataset EGAD00001007691

• Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001010320

• RNA-seq TPMs quantification for baseline tumor samples originating from IMpower150, and relevant clinical metadata

  This dataset includes full tumor transcriptomes from 558 advanced NSCLC tumors. These data originate from pre-treatment samples from a clinical trial for first-line non-small cell lung cancer (IMpower150). The patients in this trial were treated with the PD-L1 inhibitor atezolizumab +bevacizumab + chemotherapy or bevacizumab + chemotherapy or atezolizumab + chemotherapy.

  Dataset EGAD50000001814

• RNA-seq

  RNA sequencing

  Dataset EGAD00001005803

• WGS analysis of a glioma initiating cell line

  We here obtained whole-genome sequencing data to analyze transcription factor binding sequences and somatic mutations found in our RNA-seq analysis of glioma initiating cells.

  Study JGAS000096

• snRNA splicing signature RNA-Seq

  This dataset has RNA-Seq fastq files which were generated as part of the snRNA splicing signature study. Analysis can be performed to regenerate splicing signatures found for RNU4-2, RNU5B-1 and RNU5A-1 by comparing cases versus controls.

  Dataset EGAD50000001299

• RNA-Seq of acute lymphoblastic leukemia in LLAG-0707 study

  This dataset contains RNA-Seq data of acute lymphoblastic leukemia in LLAG-0707 study. Diagnostic samples of 188 patients were sequenced. Reads were aligned to hg19 genome reference using STAR. Aligned bam files are provided in this dataset.

  Dataset EGAD50000001181

• RNA-seq data for genomic determinants of response and resistance to inotuzumab in B-ALL

  RNA-seq data for 101 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000095

• WES and RNA-Seq of HCC biopsies and HCC derived Organoids

  We aimed to identify somatic mutations and transcriptional differences that could explain the resistance to Doxorubicin. This dataset includes RNA-Seq of HCC biopsies and Organoids and WES of Organoids.

  Dataset EGAD50000000060

• RNA-seq dataset for gamma delta (γδ) T-ALL patients

  RNA-seq data for 85 patients with acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL)

  Dataset EGAD50000000027

• BLUEPRINT release January 2015, RNA-Seq for monocyte

  RNA-Seq data for 8 monocyte sample(s). 8 run(s), 8 experiment(s), 8 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001191

• RNA-seq

  RNA-seq of primary and metastatic sites from highly clinically annotated HGSC samples. Samples were obtained pre-treatment based on a laparoscopic triage algorithm from patients who underwent R0 tumor debulking, or received neoadjuvant chemotherapy (NACT) with excellent (ER) or poor response(PR).

  Dataset EGAD00001005238

• Human tumour and matched-normal single-cell RNAseq

  We profiled 16 high-grade gliomas patient tumour samples by single-cell and single-nuclei RNA-seq and 3 normal-matched single-cell RNA-seq using 10X Chromium 3'. The fastq files are provided.

  Dataset EGAD00001006097

• IBS-M RNA-seq raw data

  The data set consists of fastq raw files from RNA-seq of seven mucosal biopsies of the colon from seven patients, among them three patients with irritable bowel syndrome with mixed type symptoms. Paired end sequencing on Illumina NovaSeq 6000 was used.

  Dataset EGAD00001006646

• RNA-seq of HCC patients undergoing sorafenib treatment.

  RNA-seq dataset (BAM files) of 28 HCCs and 19 non-tumor livers derived from 8 patients undergoing sorafenib treatment.

  Dataset EGAD00001008204

• Pediatric high grade glioma RNA-Seq

  We performed RNA-Seq in DIPG and hemispheric HGG.

  Dataset EGAD00001008278

• Pheochromocytoma paraganglioma single nuclei RNA-seq

  Single nuclei RNA sequencing (snRNA-seq) on tissue samples from 11 patients (SDHB and RET). Files are fastq files of 10x-5'scRNAseq libraries.

  Dataset EGAD00001008739

• RNA-Seq data on multiple myeloma CD138positive bone marrow plasma cells

  RNA-Seq data on multiple myeloma CD138positive bone marrow plasma cells, 11 samples, sequenced on HiSeq 4000 and HiSeq X-Ten, using mostly the TruSeq stranded mRNA Kit.

  Dataset EGAD00001008619

• RNA-seq for identification of neotranscripts

  This dataset contains RNA-seq data (Fastq files of paired-end data) of 18 patient tumors used for identification of neotranscripts in 18 different types of fusion-driven sarcomas and other cancers as described in Vibert et al., Mol Cell 2022 (PMID: 35550257)

  Dataset EGAD00001008832

• Genomic characterization of Malignant Pleural Mesothelioma.

  Genomic characterization of Malignant Pleural Mesothelioma using RNA-seq, Exome and Illumina 2.5 M array.

  Study EGAS00001001563

• Development and Validation of Patient-Derived Xenografts from Fibrolamellar Carcinoma Human Tissue

  We developed and validated Patient-Derived Xenografts (PDX) of Fibrolamellar Carcinoma human tissue from surgical resections. Human tissues from primary liver tumor, recurrent liver, and liver metastases were implanted into NOD-SCID-Gamma (NSG) mice (Jackson laboratories) and monitored for tumor growth. Some of the original tissues were frozen for further analysis including RNA sequencing. Tumors that grew were then harvested and passaged into additional mice. Some tumor tissues from the PDX samples were frozen for RNA-Seq analysis. The PDX was validated by histologic, transcriptomic and proteomic analysis. The RNA-Seq analysis was performed on original tissue samples including primary liver tumor, recurrent liver, liver metastases, normal liver, and the derived PDX.

  Study phs002435

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  ChIP-Seq - CEBPE - REH. The ETV6/RUNX1 translocated acute lymphoblastic leukaemia cell line REH was used to perform ChIP-Seq using a CEBPE antibody. Cells were fixed in 1% formaldehyde for 10mins, prior to preparation of chromatin using Active Motif Express ChIP-IT. 2ug of antibody (anti CEBPE Atlas Antibodies HPA002928)was added to 25ug of chromatin O/N at 4C with rotation. Duplicate reactions were pooled and purified. 10ng of ChIPd and input DNA used for Illumina NGS preparation (NEBNext ChIP-Seq Library kit; New England Biolabs), CEBPE and Input DNA ChIP samples were sequenced on a MiSeq using 150bp Kit v3 paired end and a HiSeq 2500 using 2x101 version 4 paired end (Illumina) respectively. Reactions performed in duplicate. shCEBPE RNA-Seq - REH. REH cells were lentivirally transduced with a pTRIPZ shRNA vector for transcriptional profiling of CEBPE. Two controls (empty and non-targeting) and two CEBPE shRNAs (V3THS_150517(A13), V3THS_404312(G3) Dharmacon, GE) were transduced into REH cells. Cells were treated with 1ug/ml doxycyclin for 144hrs and total RNA purified. Libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kit and sequenced on an Illuimna HiSeq 2500 using 2x101 version 4 paired end chemistry. 3 biological replicates of each samples were prepared.

  Study EGAS00001002877

• Spatiotemporal single-cell analysis reveals a time-dependent immunological modulation by multi-fractionated radiotherapy in esophageal cancer

  Description Here, by integrative spatial and single-cell analyses using spatial transcriptome (VISIUM) and single-cell RNA sequencing (scRNA-seq), we examined the spatiotemporal dynamics of immune-response in the tumor microenvironment of esophageal squamous cell carcinoma (ESCC) before, during and after RT. The comprehensive single-cell analyses demonstrated the infiltration of immune cells into tumor with the dynamic change of immune-stimulatory and -suppressive gene expression after RT. ScRNA-seq analysis uncovered the time- and cell-type-dependent alteration of gene expression profile from during to after RT. This datasets in the present study will provide the information of RT-induced gene signature to seek an appropriate target of personalized immunotherapy combined with radiotherapy and of determining the timing of the combination therapy.

  Study JGAS000712

• Colorectal cancer functional annotation - ATAC

  ATAC-seq data from multiple colorectal cancer cell lines

  Study EGAS50000000205

• Contribution of specific cell types to the development of Barrett’s esophagus and carcinoma via germline genetic risk

  This study was designed to elucidate how individual cell types in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) contribute to disease development via germline genetic risk. We performed single cell RNA-sequencing (scRNA-seq) of BE, EAC and paired normal esophagus and gastric fundus tissue samples. After analyzing individual cell types, we integrated the scRNA-seq data and data of a genome-wide association study (GWAS) on BE/EAC to determine cell type-specific genetic risk. Raw data from the RNA-sequencing is provided here.

  Study EGAS50000000530

• RNA alignment

  RNAseq aligned to hg38.p14 using nfcore/RNA-seq

  Dataset EGAD50000000428

• Single-cell RNA-sequencing and cellular indexing of transcriptomes and epitopes of peripheral blood mononuclear cells and peritoneal fluid from patients with achalasia

  The data published here contains cellular indexing of transcriptomes and epitopes (CITE-seq) and single-cell RNA- sequencing (scRNAseq) data on patients with achalasia. Paired PBMC and PF were subjected to 3' scRNAseq and CITE-seq, respectively. All single-cell data was generated using the 10X Genomics (Chromium Single Cell 3’ Reagent) and sequenced in a paired-ended fashion on the NovaSeq6000.

  Study EGAS50000000174

• Human transcriptomic (RNA-Seq) and epigenomic (ATAC-Seq) data of early B-cell lineage (bulk and single-cell) DAC

  Dac EGAC00001003265

• Brain transcriptome of hereditary cerebral haemorrhage with amyloidosis–Dutch type (HCHWA-D)

  HCHWA-D is an early onset hereditary form of Cerebral Amyloid Angiopathy (CAA) caused by a point mutation resulting in an amino acid change (NP_000475.1:p.Glu693Gln) in the Amyloid Precursor Protein (APP). Post-mortem brain tissue (9 patients and 9 age-related controls; frontal and occipital cortex) was used for next generation sequencing of RNA (RNA-Seq with ribosomal RNA depletion).

  Study EGAS00001002730

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• Bulk and RIP-seq transcriptome datasets from skin fibroblasts in PTBP1- and PTBP2-related disorders

  PTBP1- and PTBP2-related disorders are rare human conditions that cause variable neurodevelopmental phenotypes, including intellectual disability and behavioral problems such as autism spectrum disorder, anxiety, aggressiveness, and attention disorders, with or without hyperactivity. PTBP1-related disorder is also associated with skeletal dysplasia. In this study, we generated bulk RNA sequencing and RNA immunoprecipitation sequencing (RIP-seq) data from skin fibroblasts obtained from patients and healthy controls.

  Study EGAS50000001210

• Inferring expressed genes by whole-genome sequencing of plasma DNA

  The analysis of cell-free DNA (cfDNA) in plasma represents a rapidly advancing field in medicine. cfDNA consists predominantly of nucleosome-protected DNA shed into the bloodstream by cells undergoing apoptosis. We performed whole-genome sequencing (WGS) of plasma DNA and identified two discrete regions at transcription start sites (TSS) where the nucleosome occupancy results in different read-depth coverage patterns in expressed and silent genes. By employing machine learning for gene classification we found that the plasma DNA read depth patterns from healthy donors reflected the expression signature of hematopoietic cells. In cancer patients with metastatic disease, we were able to classify expressed cancer driver genes in regions with somatic copy number gains with high accuracy. We could even determine the expressed isoform of genes with several TSSs as confirmed by RNA-Seq of the matching primary tumor. Our analyses provide functional information about the cells releasing their DNA into the circulation.

  Study EGAS00001001754

• RNA-seq study of human long-term and short-term hematopoietic stem cells from umblical cord blood with lentiviral overexpression of S1PR3

  To investigate the molecular and biological pathways altered by S1PR3OE in human hematopoietic stem cells (HSC), we performed RNA-sequencing (RNA-seq) of LT- and ST-HSC 3 days after transduction with control or S1PR3 overexpression (OE) lentiviral vectors. LT-HSC and ST-HSC from 3 pool of CB lin- were FACS-purified, cells were prestimulated for 4 hours and transduced with lentiviral vectors. At day 3, 2000-5300 BFP+ cells were FACS-purified for RNA isolation with a PicoPure kit. We were able to isolate only 1600-1800 BFP+ cells from LT-HSC control samples as opposed to 4000-5400 BFP+ cells from S1PR3OE samples. Thus, we pooled all control BFP+ LT-HSC cells into one sample for RNA-seq analysis. BFP- LT-HSC from control vector transduction were purified from CB1 as an additional LT-HSC control. Nextera libraries generated from 10 ng RNA from 5 LT-HSC samples (2 controls, 3 S1PR3OE) and 6 ST-HSC samples (3 controls, 3 S1PR3OE) were subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Center for Applied Genomics, Sick Kids Hospital.

  Study EGAS00001004798

• Combined genetic and transcriptome analysis of patients with Systemic Lupus Erythematosus (SLE)

  A comprehensive profiling of the genomic architecture of Systemic Lupus Erythematosus (SLE) by combining genetic and transscriptomic analysis by RNA-seq.

  Study EGAS00001003662

• Patient-derived conditionally reprogrammed cells (CRCs) were established and characterized to assess their biological properties and to apply these to test the efficacies of drugs.

  RNA seq data was used for the characterization and profiling of the created patient-derived cells and in vivo tissue.

  Study EGAS00001001702

• RNA-seq dataset of salivary gland tumor samples

  This dataset contains paired-end RNA-seq data of salivary gland tumor samples from 94 patients. Sequencing was performed on Illumina HiSeq 2500, HiSeq 4000, HiSeq X Ten or NovaSeq 6000.

  Dataset EGAD50000001191

• 104 CRLM patients RNA-seq

  This dataset consists of RNA-seq data from 104 CRLM patients. Reads were mapped to the GRCh37 genome version using STAR. The data include patients with no treatment, as well as those treated with FOLFOX, FOLFOX-bevacizumab, atezolizumab, and FOLFOX-bevacizumab-atezolizumab.

  Dataset EGAD50000000954

• RNA-Seq of non-canonical t(7;12) AML

  We performed WGS on AutoMACS-separated BM leukemic blasts (CD34 + CD33+) to characterize the breakpoint and genes involved in the translocation. Additionally, we performed RNA-seq of the bone marrow blast cells to explore the functional consequences of the t(7;12) translocation

  Dataset EGAD50000000268

• Human TRIM24-MET fusion HGG RNA-seq

  Human RNA-seq data for TRIM24-MET fusion tumor primary samples and patient/PDOX-derived cell lines. Cells were treated with 0.1% DMSO or EC90 of MET inhibitors (capmatinib, cabozantinib, crizotinib) for 4 hours. BAM files containing aligned (and unaligned) reads to hg19 are provided.

  Dataset EGAD50000000194

• IBS-D RNA-seq raw data

  The data set consists of fastq raw files from RNA-seq of seven mucosal biopsies of the colon from seven patients, among them three patients with irritable bowel syndrome with diarrhea-predominant symptoms. Paired end sequencing on Illumina NovaSeq 6000 was used.

  Dataset EGAD50000000063

• Total RNA-seq of intestinal gluten tetramer+ and tetramer- CD4+ T-cells from celiac disease patients

  Total RNA-seq of intestinal gluten tetramer+ and tetramer- CD4+ T-cells from celiac disease patients, as well as intestinal CD4+ T-cells from healthy control individuals (paired-end fastq files).

  Dataset EGAD00001004146

• BLUEPRINT: RNA-seq for monocytes and neutrophils

  RNA-seq for monocytes and neutrophils

  Dataset EGAD00001000675

• BLUEPRINT release August 2015, RNA-Seq for monocyte, on genome GRCh38

  RNA-Seq data for 4 monocyte sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001572

• BLUEPRINT release August 2015, RNA-Seq for Multiple myeloma, on genome GRCh38

  RNA-Seq data for 11 Multiple myeloma sample(s). 11 run(s), 11 experiment(s), 11 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001471

• Chromatin 3D interactions mediate genetic effects on gene expression (RNA-seq)

  RNA-seq data for 168 Lymphoblastoid Cell Lines (LCL) and 78 Fibroblasts (FIB) from the Gencord Cohort. This dataset was generated as part of the following study: Delaneau et al (2019). Chromatin 3D interactions mediate genetic effects on gene expression.

  Dataset EGAD00001004872

• Human tumor bulk RNA-seq

  We profiled 186 patient tumor samples by bulk RNA-seq. These includes 38 embryonal brain tumors, 101 high-grade gliomas, 24 low-grade gliomas, 10 medulloblastoma and 13 matched normals. The raw fastqs are provided.

  Dataset EGAD00001005131

• RNA-seq of 27 FFPE prostate samples (tumour only) to identify gene fusions

  RNA-Seq was performed on radical prostatectomy formalin-fixed paraffin-embedded sample pairs (n = 27). Library prep was done by removal of rRNA and sequenced as 75bp paired end on Illumina NextSeq 500. Sequences were aligned to the human genome (hg38) using STAR-Fusion.

  Dataset EGAD00001006108

• Single cell RNA-seq CD8 T cells from elder adults

  Single cell RNA-seq profiling of ~62k purified CD8+ T cell transcriptomes, from six healthy older adult donors using 10X genomics. Cells from each donor were separated based on their IL-7R protein expression (i.e. CD8+ IL7R+ and CD8+ IL7R- T cells).

  Dataset EGAD00001006000

• RNA-seq cohort of normal weight women

  RNA-seq data of non-tumorous breast tissue. There are 32 samples in this cohort.

  Dataset EGAD00001007073

• RNA-seq data from a variety of pediatric brain tumors

  RNA-seq (n=52) data from a variety of pediatric brain tumors including ependymoma (PFA, PFB, Ste, spinal), medulloblastoma (G3, G4, SHH), high grade glioma (H3K27 and H3-WT), pilocytic astrocytoma, and more. Raw data provided as FASTQ. Data generated on Illumina HiSeq2500.

  Dataset EGAD00001007915

• Intellance-2: TruSight Tumor 170 panel based RNA-seq

  Intellance-2: TruSight Tumor 170 panel based RNA-seq

  Dataset EGAD00001007944

• Genomic and Immune Profiling of Breast Cancer Brain Metastases

  Previous work has shown that breast cancer brain metastases (BCBrM) can have unique molecular profiles compared to extracranial tumors (ECTs), resulting in some patients demonstrating subtype switching between primary/extracranial tumors and brain metastases. Description of the biology of BCBrM and associations between biological features and clinical outcomes, particularly between molecular intrinsic subtypes, will facilitate the design of rational therapies for patients with BCBrM. To better characterize the molecular profiles of BCBrM, we conducted whole exome sequencing (WES) and total RNA sequencing (RNA-Seq) on BCBrM tissues, regardless of clinical or molecular subtype, obtained from a cohort of 42 patients from Duke University Medical Center. This cohort adds valuable patient samples to the field and enables strengthened investigation of somatic mutations, copy number alterations, gene expression profiles, and immune populations within and between BCBrM patients and other similar cohorts. The Duke BCBrM cohort includes clinical and molecular annotation of the 42 patient specimens and their associated WES and RNA-Seq data. Clinical and molecular (PAM50) intrinsic subtypes in ECTs and brain metastases were largely concordant within patients. There were observed differences in intrinsic subtype calls between frozen and FFPE specimens of the same tissue, with discordance mostly observed with LumB calls. Copy number alterations in chromosomal regions included clinically relevant genes, and somatic alterations were largely conserved within patients across matched samples, with few genes, including TP53, being recurrently altered in the majority of patient specimens. In matched FFPE brain metastasis and ECT samples, we observed differentially expressed genes and pathways that had increased or decreased expression in brain metastasis, including in oxidative phosphorylation and DNA repair. Survival outcomes for patients differed by intrinsic molecular subtypes, with some association between expression of select gene pathways and survival. Data available through dbGaP will be the sequencing data and sample attributes from BCBrM tissues obtained from 42 patients from Duke University Medical Center.

  Study phs003673

• RNA-Seq

  Dac EGAC00001002038

• Arriba: accurate and efficient detection of gene fusions from RNA-Seq (H021)

  The identification of gene fusions from RNA sequencing data is a routine task in cancer research and precision oncology. However, despite the availability of many computational tools, fusion detection remains challenging. Existing methods suffer from poor prediction accuracy and are computationally demanding. We developed Arriba, a novel fusion detection algorithm with high sensitivity and short runtime. When applied to a large collection of published pancreatic cancer samples (n=803), Arriba identified a variety of driver fusions, many of which affected druggable proteins, including ALK, BRAF, FGFR2, NRG1, NTRK1, NTRK3, RET, and ROS1. The fusions were significantly associated with KRAS wild-type tumors and involved proteins stimulating the MAPK signaling pathway, suggesting that they substitute for activating mutations in KRAS. In addition, we confirmed the transforming potential of two novel fusions, RRBP1-RAF1 and RASGRP1-ATP1A1, in cellular assays. These results demonstrate Arriba’s utility in both basic cancer research and clinical translation.

  Study EGAS00001003554

• Exploring_the_heterogeneity_of_sarcoma_using_single_cell_sequencing_

  Multi region samples are collected from patients, with consent, immediately after resection of the tumour. Samples are digested and sorted using FACS as single cells into lysis buffer. Cells are then stored until further processing for G&T-seq. After sequencing, we will explore intra-tumour heterogeneity using computational approaches to integrate RNA and DNA data onto the tumour phylogeny 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/

  Study EGAS00001002866

• Human Pilocytic Astrocytoma Single Cell RNA Sequencing

  Pilocytic astrocytoma (PA), the most common childhood brain tumor, is a low-grade glioma with a single driver BRAF rearrangement. Here, we perform scRNAseq in six PAs using methods that enabled detection of the rearrangement. When compared to higher-grade gliomas, a strikingly higher proportion of the PA cancer cells exhibit a differentiated, astrocyte-like phenotype. A smaller proportion of cells exhibit a progenitor-like phenotype with evidence of proliferation. These express a mitogen-activated protein kinase (MAPK) program that was absent from higher-grade gliomas. Immune cells, especially microglia, comprise 40% of all cells in the PAs and account for differences in bulk expression profiles between tumor locations and subtypes. These data indicate that MAPK signaling is restricted to relatively undifferentiated cancer cells in PA, with implications for investigational therapies directed at this pathway. Note that 931 out of 1234 samples in the Sequence Read Archive (SRA) passed QC and have transcript count data available from the Broad Institute Single Cell Portal. The transcript count data can be found at https://singlecell.broadinstitute.org/single_cell/study/SCP271/pilocytic-astrocytoma-single-cell-rna-seq#study-download

  Study phs001854

• UCL COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of COVID19 patients recruited from University College London. Data represent RNA-seq, surface protein measurements (CITE-seq) of 192 antibody targets, along with VDJ-seq profiling of single T cell and B cell receptors. Samples are pooled, with 4 donors per pool. Germ-line genotypes derived from previous single-cell RNA-sequencing are provided (VCF) to aid demultiplexing of single-cell and assignment to specific patient donor samples.

  Dataset EGAD00001007865

• DAC_RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Data access committee for RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Dac EGAC50000000352

• Medulloblastoma Illumina RNA-Seq

  Illumina RNA-sequencing of Medulloblastoma primary and relapse tumor.

  Dataset EGAD00001009425

• Case Report: Pre-Clinical Combination Targeting VEGF and PI3K in a Rare, Aggressive Mixed Endometrial Carcinoma

  We report a rare case of a young patient (VENUS 167) initially diagnosed with grade 1 endometrioid endometrial cancer, which, following endocrine treatment, presented with mixed aggressive carcinoma with three distinct histologic patterns: grade 1 endometrioid, large cell neuroendocrine, and undifferentiated carcinoma. The surgical specimen at the time of disease progression was used to establish OPTO.85, a patient-derived organoid (PDO), followed by a corresponding organoid-derived xenograft (ODX). Multi-omic analyses confirmed that OPTO.85 accurately reflected the patient’s tumor characteristics. WES analysis identified oncogenic alterations in PIK3CA, ARID1A, and CTNNB1. Further RNA-seq and ATAC-seq analyses revealed enrichment in VEGF and Wnt signaling pathways, suggesting therapeutic vulnerabilities. A high-throughput drug screen was conducted using ApexBio-Approved and Epigenetic Drug Libraries, along with Kinase Inhibitor and Tool Compound Libraries developed at the Ontario Institute of Cancer Research. The OPTO.85 PDO exhibited sensitivity to PI3K inhibitors and responsiveness to VEGF inhibition. Cediranib demonstrated synergy with BKM120, significantly reducing organoid growth. This combination also showed in vivo efficacy in the ODX model, where dual inhibitors significantly suppressed tumor growth compared to single compounds. This case exemplifies the impact of genomic profiling and patient-derived models in identifying actionable molecular changes in rare cancers with limited therapeutic options and poor prognosis. It highlights that high-throughput sequencing for individual patient tumors and generation of patient-derived models are feasible in endometrial cancer. This preclinical model may assist clinical decision and personalized therapy requiring validation in prospective studies.

  Study EGAS50000001665

• Adult-type Granulosa Cell Tumour of the Ovary RNA Sequencing

  We analyzed 34 AGCTs (19 primary and 15 recurrent) and the KGN cell line by RNA-Seq. Our cohort comprised of 3 AGCTs WT for FOXL2, 28 heterozygous and 3 homo/hemizygous for the pathogenic variant. Fresh-frozen AGCTs were selected from OVCARE’s Gynecological Tissue Bank in Vancouver, Canada for bulk RNA-seq. RNA was extracted from frozen tissue and sections adjacent to the scrolls submitted for RNA-seq were stained with hematoxylin and eosin (H&E) to evaluate tumour cell purity. Cases with >80% tumour cell purity were selected for sequencing with the majority of cases (29 of 34 patients) containing >90% tumour cells. Ribodepleted RNA libraries were constructed and paired-end sequencing (125 base pair reads) was performed.

  Dataset EGAD00001007812

• Single-cell RNA-seq and TCR-seq of synovial tissue and peripheral blood CD4+ and CD8+ T cells from patients with immune-mediated refractory arthritis

  In this study, we investigated CD4+ and CD8+ T lymphocytes from the synovial tissue and peripheral blood of patients with treatment-resistant immune-mediated arthritis using paired single-cell RNA and TCR-sequencing.

  Study EGAS50000000528

• Small RNA-Seq of MicroRNA's in extracellular vesicles of Ushers Syndrome patients

  Small RNA-Seq dataset of MicroRNA's found in tear extracellular vesicles (EVs) and hiPSC-derived retinal pigment epithelium (RPE) cells of Ushers Syndrome patients and control samples. 14 samples were isolated and assessed for quality before preparing libraries using the miReasy and TruSeq Small RNA Library Preparation Kit. Sequencing was performed on the Illumina NextSeq 2000 platform, generating paired end FASTQ files.

  Dataset EGAD50000001709