7193 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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• Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer

  Our study provides insight into molecular alterations in HN tissues within the affected breast and offers a greater understanding of the spatial implications of these aberrations. This was achieved by performing a comprehensive analysis of RNA sequencing data and proteomic profiles from breast cancers (n=19) and their matched HN tissues (n=38), healthy breast from cosmetic reduction mammoplasty (RM; n=5), and risk reducing mastectomies (RR, n=5), with peritumoral samples excised at proximal (TP, <2 cm) and distal (TD, 5-10 cm) sites from the primary tumor.

  Study EGAS00001004510

• Juntendo Muscle Study (JMS)

  Skeletal muscle fiber type distribution has implications for human health, muscle function and performance. This knowledge has been gathered using labor intensive and costly methodology that limited these studies. This data was used to present a new method based on muscle tissue RNA sequencing data to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for larger number of individuals to be tested in a cost and labor efficient way. Muscle biopsies were taken from the vastus lateralis muscle of 23 human subjects from Japan. Samples were sequenced on the NextSeq® 500/550 (Illumina).

  Study EGAS00001006362

• Muscle SATellite cell study (MSAT)

  Skeletal muscle fiber type distribution has implications for human health, muscle function and performance. This knowledge has been gathered using labor-intensive and costly methodology that limited these studies. This data was used to present a new method based on muscle tissue RNA sequencing data to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for larger number of individuals to be tested in a cost and labor efficient way. Muscle biopsies were taken from the vastus lateralis muscle of 39 Swedish male subjects. Samples were sequenced on the NextSeq® 500/550 (Illumina).

  Study EGAS00001006363

• Multiregional single cell RNA sequencing of human renal cell carcinoma

  The dataset comprises of 5' single cell RNA sequencing with TCR enrichment with 10x Genomics' Chromium technology of multiregional biopsies of human renal cell carcinomas. Biopsies from different tumour regions, the tumour-normal interface, normal kidney, normal adrenal, metastatic regions, peri-nephric fat, and peripheral blood were sequenced from 12 patients with kidney tumours.

  Dataset EGAD00001008030

• MDS-HSC-RNA-SEQ

  Dac EGAC00001000185

• utero-tubal lavage RNA seq DAC

  Dac EGAC00001002241

• GLASS-NL RNA-seq Data access committee

  Dac EGAC00001003470

• RNA-seq of granulosa cells from 8 IVF patients in two age groups

  This dataset contains raw sequencing data of mRNA from granulosa cell samples from 8 human patients undergoing in vitro fertilization. All patients were normal responders referred for male infertility and were grouped into two age groups (younger than 31 or older than 38 years old). Each sample contains all granulosa cells collected from one patient on one collection date. Raw sequencing fastq files are available in this dataset, count tables are available in ArrayExpress (E-MTAB-13496).

  Dataset EGAD50000001210

• ProstOmics - Bulk Transcriptomics

  Bulk transcriptomics data from 176 prostate tissue samples (37 patients, 27 with post-surgery relapse) that were acquired using the SENSE mRNA-Seq Library Prep Kit V2 and Illumina NextSeq 500 instrument. The raw transcriptomics data is single-read RNA-seq. The individual samples have information on patient origin and sample type (cancer, cancer-adjacent field-effect normal or normal sample far from cancer). Patient metadata include information of age at surgery, time (months) until reported relapse, pre-surgery PSA and post-surgery T-stage.

  Dataset EGAD50000000604

• RIP-SeqRaw data

  This dataset contains the raw count matrix generated in the PTBP1 project. Sequencing data were obtained from bulk directional RNA-seq and RIP-seq experiments performed on a NovaSeq 6000 platform (2×100 bp paired-end reads). Read counts were computed using HTSeq-count, without normalization. The dataset comprises two groups of samples: controls and patients. For each group, both input and immunoprecipitated samples are available. Patient samples correspond to skin biopsies from individuals affected by a neurodevelopmental disorder associated with variable skeletal dysplasia and disproportionate short-limbed short stature.

  Dataset EGAD50000001722

• RNAseq of Thymic epithelial tumors and paired normals

  Between November 2010 and May 2014, 20 cases—17 thymomas and 3 thymic carcinomas (including 2 squamous and 1 neuroendocrine carcinoma)—were newly sequenced from surgically removed TETs at Seoul National University Hospital, with written informed consent. Tumors and normal tissues were carefully separated and immediately preserved in liquid nitrogen after resection. DNA and RNA were extracted from the tumors, adjacent normal tissues, and/or blood samples. Libraries for RNA-seq were prepared using the TruSeq Stranded mRNA LT Sample Prep Kit following standard Illumina protocols.

  Dataset EGAD50000001158

• RNA-Seq Profiles from the CheckMate-577 Clinical Trial

  The dataset contains RNAseq profiles of 386 patients from the CheckMate-577 (CA209-577) clinical trial whose ICF allows data deposition into a public repository. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. RNA was analyzed using the Illumina TruSeq RNA Access method for library preparation, followed by sequencing on the Illumina NovaSeq platform with a 50bp paired-end strategy and a target read depth of 50M per sample. Fastq files are included.

  Dataset EGAD50000002394

• Transcriptomic data from a SARS-CoV-2 human challenge study (Kelly Research Group, Arkansas Children’s Research Institute)

  This dataset contains paired-end RNA-Seq data generated from mid-turbinate nasal and throat samples collected as part of a first-in-human SARS-CoV-2 experimental challenge study conducted in the United Kingdom in 2021. Total RNA was extracted using QIAamp Viral RNA kits (Qiagen), and libraries were prepared using TruSeq RNA Exome kits (Illumina). Sequencing was performed on a NovaSeq X Plus instrument configured for 100 bp paired-end reads. The dataset includes raw FASTQ files and associated de-identified metadata.

  Dataset EGAD50000002078

• Cambridge COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of healthy controls, asymptomatic and hosptial-admitted COVID19 patients recruited from Addenbrookes and Royal Papworth hospitals, in collaboration with the NIHR Cambridge Bioresource. 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 are provided (VCF) to aid demultiplexing of single-cell and assignment to specific patient donor samples.

  Dataset EGAD00001007867

• scRNA-seq using 10X Genomics platform

  Matrices of counts from single-cell RNA-seq data for 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert). Dissociated cells from each tumor sample have been sorted to isolate live cells from the 3 compartments: tumor, immune and stromal. Each of the compartments has been analyzed separately by scRNAseq, excluding some desert tumors for which cells from the stromal and immune compartments have been pooled. Sequencing was performed using 10X Genomics Chromium Single Cell platform (v2 Chemistry).

  Dataset EGAD00001006974

• RNA-seq analysis of CCO+/CCO- hepatocytes in normal human liver

  RNAseq data from Passman et al 2023. Clonal CCO-deficient hepatocyte patches and nearby CCO-proficient hepatocytes were identified in morphologically normal human livers and sampled at varying distances along the PT-CV axis. Samples are characterised according to their location within the liver lobule, with "PT" denoting samples abutting the portal triad, "CV" denoting samples abutting the central hepatic vein, and "Mid" sampled acquired midway between these structures. Analysis was performed on an Illumina Nextseq using a high output kit and 100 single-end cycles.

  Dataset EGAD00001010033

• RNA-seq of cells after injection into immunodeficient mice

  This dataset includes 73 samples profiled by high-throughput Illumina sequencing, in bam format, aligned to GRCh37. Normal human CD34+ cord blood (CB), bone marrow (BM), or post-natal thymus (PNT) cells were transduced with various combinations of T-ALL oncogenes, cultured in vitro on OP9-DL1 feeders for up to 25 days, and then transplanted into immunodeficient NSG or NRG mice. The samples were collected after development of frank leukemia in recipient mice.

  Dataset EGAD00001009751

• WES and RNA-seq data of 11 cancer patients with multiple cancer types

  This dataset includes WES and RNAseq from 11 patients with metastatic melanoma, lung, kidney, and stomach cancers, enrolled in phase I clinical trials of TIL ACT (NCT03475134 & NCT04643574). WES was performed on matched cancer and healthy samples, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 2500/4000 and Illumina NextSeq 550 systems. Paired-end reads are provided in fastq format.

  Dataset EGAD00001010169

• Dataset for identification of the dismal subtype of B-ALL with dysregulation of CDX2 and UBTF

  WGS (tumor and germline samples) was performed to identify structural variants in the UBTF/CDX2 subgroup. RNA-seq was performed to detect gene fusion in the UBTF/CDX2 subgroup. HiChIP was performed to investigate 3D chromatin architecture and enhancer landscapes of representative patient samples and cell lines harboring Type I and II FLT3-PAN3 deletions and amplifications.

  Dataset EGAD00001008416

• Sequence Data for DEEP Release August 2016

  DEEP (German Epigenome Project) sequence data of following samples (Sequencing Types: Chip-Seq, WGBS-Seq, RNA-Seq, sncRNA-Seq, NOMe-Se, DNase-Seq): 41_Hf01_LiHe_Ct, 41_Hf02_LiHe_Ct, 41_Hf03_LiHe_Ct, 01_HepG2_LiHG_Ct1, 01_HepG2_LiHG_Ct2, 01_HepaRG_LiHR_D31, 01_HepaRG_LiHR_D32, 01_HepaRG_LiHR_D33, 43_Hm01_BlMo_Ct, 43_Hm03_BlMo_Ct, 43_Hm05_BlMo_Ct, 43_Hm03_BlMa_Ct, 43_Hm05_BlMa_Ct, 43_Hm03_BlMa_TO, 43_Hm05_BlMa_TO, 43_Hm03_BlMa_TE, 43_Hm05_BlMa_TE, 51_Hf01_BlCM_Ct, 51_Hf03_BlCM_Ct, 51_Hf04_BlCM_Ct, 51_Hf02_BlCM_Ct, 51_Hf05_BlCM_Ct, 51_Hf06_BlCM_Ct, 51_Hf06_BlCM_T1, 51_Hf06_BlCM_T2, 51_Hf03_BlEM_Ct, 51_Hf04_BlEM_Ct, 51_Hf02_BlEM_Ct, 51_Hf05_BlEM_Ct, 51_Hf06_BlEM_Ct, 51_Hf06_BlEM_T1, 51_Hf06_BlEM_T2, 51_Hf03_BlTN_Ct, 51_Hf04_BlTN_Ct, 51_Hf02_BlTN_Ct, 51_Hf05_BlTN_Ct, 51_Hf06_BlTN_Ct, 51_Hf06_BlTN_T1, 51_Hf06_BlTN_T2, 51_Hf07_BmTM4_Ct, 51_Hf08_BlTM4_Ct, 51_Hf08_BmTM4_SP1, 51_Hf08_BmTM4_SP2, 51_Hf05_BlTA_Ct, 44_Mm01_WEAd_C2, 44_Mm03_WEAd_C2, 44_Mm02_WEAd_C2, 44_Mm07_WEAd_C2, 44_Mm04_WEAd_C1, 44_Mm05_WEAd_C1

  Dataset EGAD00001002527

• Application of short-RNA-seq in post-mortem human hippocampi from the Calgary Brain Bank (CBB) to assess transcriptome-wide deregulation in processing of SINE Alu RNAs in Alzheimer’s disease

  Here, we investigate through short-RNA_seq in human hippocampi from the Calgary Brain Bank (CBB) whether Alu RNAs are processed in human brains, and whether their processing ratio is deregulated in brains of AD patients compared to healthy aging individuals.

  Study EGAS00001004973

• Profiling Genome-Wide Circulating ncRNAs for the Early Detection of Lung Cancer

  Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all cases. Although imaging techniques such as low-dose computed tomography (LDCT), combined with tissue biopsies, have improved early detection rates, current diagnostic approaches are often limited by high false-positive rates, invasiveness, and radiation exposure, which lead to misdiagnosis and increased patient burden. Therefore, there is an urgent need for minimally invasive, accurate, and safe diagnostic biomarkers, particularly those derived from liquid biopsies such as blood-based exosomal RNA.This dataset specifically focuses on plasma-derived exosomal small non-coding RNAs (sncRNAs).A total of 233 de-identified plasma samples were obtained from Rush University Medical Center, including 116 NSCLC patients and 117 non-cancer controls. Exosomes were isolated from plasma, RNA was extracted, and small RNA sequencing was performed using the Illumina NextSeq 500 platform. Data available through dbGaP include individual-level raw sequencing files (FASTQ) and basic phenotype annotations of the plasma cohort.A diagnostic model was initially developed using small RNA-seq data from 1,446 tissue samples obtained from TCGA and GEO, identifying a robust sncRNA signature that distinguished NSCLC from non-cancer samples with an AUC of 0.90 in hold-out tissue validation. This signature was subsequently validated in the plasma exosome cohort, achieving an AUC of 0.84 in independent validation. The model demonstrated consistent diagnostic performance across subgroups stratified by age, sex, smoking history, cancer stage, and NSCLC subtype. Survival and functional analyses further supported the clinical and biological relevance of the identified sncRNAs. It is hoped that this resource will contribute to a better understanding of the sncRNA expression landscape in NSCLC and promote the development of non-invasive biomarkers for early cancer detection. These data may be applied to the investigation of transcriptomic and other risk factors, provide insight into cancer screening, tumor progression mechanisms, and prognosis prediction, and ultimately support precision medicine for NSCLC.

  Study phs004166

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  Genetic and non-genetic heterogeneity within cancer cell populations represents a major challenge to anti-cancer therapies. We currently lack robust methods to determine how pre-existing and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA-sequencing, we have developed TraCe-seq, a method that captures at clonal resolution the origin, fate, and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual EGFR inhibitors-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Study EGAS00001005405

• RNA-seq of STIC lesions and adjacent normal samples

  In this study, we characterize premalignant lesions of the fallopian tube (serous tubal intraepithelial carcinomas) to explore the earliest events of tumorigenesis following mutation of the TP53 tumor suppressor gene. We conduct laser capture microdissection to isolate premalignant cells from adjacent normal cells, and subject isolated tissues to RNA-seq. Our findings reveal the earliest transcriptional changes established during premalignancy within the fallopian tube.

  Study EGAS50000000200

• RNA-seq following miR-130a overexpression (OE) in human CD34+cord blood cells

  We performed RNA-seq on CD34+ human cord blood (CB) cells transduced with Control or miR-130a OE lentiviruses to identify differentially expressed genes. Sorted CD34+ cells from 3 independent cord blood pools were transduced with lentiviruses containing mOrange (mO) reporter gene. mO+ cells were sorted 3 days post-transduction and RNA was harvested for library preparation and sequencing.

  Study EGAS00001005868