3884 results for "RNA AND sequencing OR transcriptome"

in 13.17 milliseconds.

• BCSA_Exome+SmartSeq3

  Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

  Dataset EGAD00001009781

• Data for the study "Plasma ctDNA is a tumor tissue surrogate and enables clinical-genomic stratification of metastatic bladder cancer"

  Sequencing data from patients with bladder cancer. BAM files from targeted DNA sequencing of bladder cancer driver genes in 344 circulating tumor DNA and tumor tissue samples. BAM files from whole exome sequencing of 49 circulating tumor DNA and tumor tissue samples. Paired FASTQ files from RNA sequencing of 86 tumor tissue samples.

  Dataset EGAD00001006362

• Spatial transcriptomics reveals immune and tissue remodeling, highlighting diverse host responses across mycobacterial granuloma types

  Granulomas are the hallmark of Mycobacterium infections, forming structured immune environments that drive disease persistence. However, their spatial and functional organization remains unclear. Using spatial RNA sequencing on 33 patient explants, we try to reveal the detailed gene expression and cell composition landscape of granulomas.

  Dataset EGAD50000001462

• Citeseq of human bone marrow

  CITE-seq dataset of human bone marrow from four healthy donors. Single-cell RNA sequencing was performed using the 10x Genomics 3’ v3 platform. Approximately 7,000–10,000 cells were loaded in each 10x channel, after which the single-cell libraries were prepared according to manufacturer’s instructions, except for the added CITE-seq steps. Demultiplexed FASTQ files are provided.

  Dataset EGAD50000001211

• Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy"

  Dataset of the study "Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy". This dataset contains the cellranger's gene-expression matrices for the 5 prime single-cell RNA sequencing experiments

  Dataset EGAD50000000748

• Sequencing data for oesophageal and related samples - Mourikis et al (RNA)

  Data supporting: "Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma." Mourikis et al. RNAseq (BAM files) 137 samples

  Dataset EGAD00001004776

• 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

• 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

• 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

• 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

• Sequencing data for oesophageal and related samples - Ng, Contino et al (RNA)

  Data supporting: "Interplay of processes shapes structural variations undergoing selection in oesophageal adenocarcinoma" Ng, Contino et al. RNAseq (BAM files) 214 oesophageal adenocarcinoma samples

  Dataset EGAD00001007809

• 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

• Whole exome and RNA sequencing data from urothelial bladder cancer patients treated with anti-PD-(L)1

  We have generated and analyzed genomic data from a cohort of metastatic urothelial carcinoma patients treated with ICI such as anti-PD-(L)1 monoclonal antibodies. The dataset contains whole exome sequencing data of 27 whole blood samples and 27 FFPE tumor samples. Further, it includes RNA sequencing data from 21 tumor samples. Following the RECIST criteria, 10 patients were classified as non-responders to the treatment, and 17 were responders. The dataset also contains a merged vcf file containing somatic mutations called by Strelka2 and Mutect2 following the gatk best practice pipeline.

  Dataset EGAD00001010324

• Integrated Single-Cell and Microbiome Profiling of Stable Bronchiectasis Across Disease Severity

  Bronchiectasis is a chronic respiratory disease characterized by persistent airway inflammation and recurrent infections. In this study, sputum samples from patients with mild, moderate, and severe bronchiectasis, collected during clinically stable disease, were analyzed using flow cytometry, single-cell RNA sequencing, and 16S rRNA gene sequencing. The resulting datasets enable characterization of neutrophil populations, transcriptional states, and airway microbial communities across disease severity stages.

  Study EGAS50000001808

• INTEGRATIVE MOLECULAR ANALYSIS OF SKIN TUMORS FROM CYLD CUTANEOUS SYNDROME PATIENTS

  CYLD cutaneous syndrome (CCS) is a rare autosomal dominant disorder characterized by germline CYLD mutations and by multiple benign skin tumors dependent on NF-kB pathway. We assembled a large cohort of CCS rare skin tumors that was profiled with whole exome or genome sequencing, RNA sequencing and methylation arrays to better understand genetic mechanisms of CCS tumorogenesis.

  Dataset EGAD50000000362

• Bulk RNASeq of metastatic colorectal cancer organoids treated with crenigacestat alone or in combination with cetuximab

  Bulk RNA sequencing was performed on mCRC organoids cultured under untreated conditions or treated with crenigacestat alone or in combination with cetuximab. This dataset was generated to investigate the transcriptional changes associated with combination therapy and to compare these profiles with the adaptive responses observed following cetuximab monotherapy in the corresponding ATOH1 wild-type and knockout organoid models.

  Study EGAS50000001422

• Single-cell multi-omics reveals clonal evolution and T-cell dynamics underlying differential responses to ibrutinib in Waldenström macroglobulinemia.

  To elucidate the molecular basis underlying differential response and resistance to ibrutinib in Waldenström’s macroglobulinemia (WM), we conducted a prospective phase II trial (NCT02604511) of ibrutinib monotherapy in treatment-naïve patients. Seventy-four sequential bone marrow (BM) aspirates from 17 patients, collected from baseline through 48 treatment cycles, were profiled using single-cell RNA and V(D)J sequencing.

  Study EGAS50000001596

• Recurrent DNMT3B gene rearrangements are associated with unfavorable outcome in dicentric (9;20)-positive pediatric BCP-ALL

  We provide clinical data sets of Array CGH, targeted RNA-seq, total RNA-seq, whole genome bisulfite (WGBS) and whole genome DNA sequencing (WGS) obtained from bone marrow (BM) or peripheral blood (PB) mononuclear cells of 57 pediatric patients with dicentric chromosome dic(9;20) positive Acute lymphocytic leukemia (ALL), from which in 6 cases DNMT3B gene rearrangement was identified. This data is complemented by total RNA-seq and WGBS of samples from 4 additional ALL patients with a t(12;21) translocation and ETV6-RUNX1 gene fusion. DNA was isolated from BM or PB B-lymphocytes using Qiagen QIAamp DNA Blood Midi Kit to perform i) Array CGH of 58 dic(9;20) positive samples by hybridizing 500ng DNA using a Agilent 400K SurePrint G3 Custom CGH Human Genome Microarray (e-Array design 84704) ii) WGBS of 6 DNMT3B rearrangement positive samples and 4 ETV6-RUNX1 positive samples using Tecan TrueMethyl oxBS-Seq module for library preparation and Illumina NovaSeq 6000 platform to run 2x151 cycles iii) WGS of DNMT3B rearrangement positive samples using Illumina Lotus DNA Library Prep Kit followed by sequencing running 2x160 cycles on an Illumina NovaSeq 6000 platform. RNA was isolated from PB B-lymphocytes using the PerkinElmer Chemagic 360 instrument, followed by i) targeted RNA-seq of 56 dic(9;20) positive samples prepared using Illumina TruSight RNA Pan-Cancer Panel and sequenced on an Illumina MiSeq platform running 2x75 cycles ii) total RNA-seq of 6 DNMT3B rearrangement positive samples and 4 ETV6-RUNX1 positive samples utilizing TruSeq Stranded Total RNA Library Prep Gold kit and running 2x100 cycles on an Illumina NovaSeq 6000 platform.

  Dataset EGAD00001011122

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001009048

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 37 samples was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001010139

• Spatial transcriptome analysis of aging of healthy skin samples

  Previous studies have revealed that skin T cells accumulate and maintain immune responses in the elderly. However, we questioned why these functional T cells fail to recognize and eliminate malignant cells, making elderly skin more prone to developing malignant tumors. To address this question, we examined the overall skin microenvironment in aging using Xenium digital spatial RNA sequencing.

  Study JGAS000771

• RNA data for MMML (EGAS00001002422)

  RNA sequencing data for MMML (3 tumor samples and 1 gcbcell)

  Dataset EGAD00001003285

• RNASeq of bone marrow endothelial cells upon regeneration, (fetal) niche formation, and steady-state.

  Comprehensive transcriptional characterization of bone marrow endothelial cells by RNA sequencing was performed to determine the molecular properties/signatures of endothelium during bone marrow recovery and niche formation. Regenerative bone marrow endothelium was FACS-isolated from bone marrow aspirates of Acute Myeloid Leukemia patients 17 days after receiving chemotherapy (n=3). Niche-forming endothelial cells were FACS-isolated from fetal bones (gestational age 15-20 weeks) (n=3). Healthy adult bone marrow endothelial cells (n=7) were used as steady-state controls. cDNA was prepared using the SMARTer procedure (SMARTer Ultra Low RNA Kit, Clonetech). The provided file type is FASTQ.

  Dataset EGAD00001003904

• Single-cell omics data for COVID-19 patients

  Single-cell RNA-seq, single-cell ATAC-seq, and genotypes used in the analysis for the study "Altered and allele-specific open chromatin landscape reveal epigenetic and genetic regulators of innate immunity in COVID-19". The RNA-seq and ATAC-seq are raw data in FASTQ format while the genotypes are in the VCF format which was filtered and imputed (more details are available in the main text of the study).

  Dataset EGAD00001009331

• Single cell RNA-seq, TCR-seq and bulk TCR-seq on HNSCC patients treated with ICB

  We performed single cell RNA- and TCR-sequencing (10x Genomics) on immune infiltrates (CD45+ cells) from 18 HNSCC patients enrolled in the IMCISION trial (Vos et al. 2021). Viable immune cells were isolated from pre-treatment and post-treatment primary tumor biopsies of 10 patients responding (1 partial pathological response and 9 major pathological responses) and 7 patients non-responding to anti-PD-1 and anti-CTLA4 combination immunotherapy. One patient treated with anti-PD-1 monotherapy (1 major pathological response) was included in the dataset. Bulk TCR-seq was performed on the PBMCs of responding patients, pre- and post-treatment.

  Dataset EGAD00001011311