Search Results - EGA European Genome-Phenome Archive

Myeloid-specific KDM6B inhibition sensitizes Glioblastoma to PD1 blockade

This data set include FASTQ files for five experiments: Human scRNA-Seq data (6 samples), Human Visium spatial transcriptomic data (3 samples), Mouse scRNA-seq data (4 samples), Mouse scATAC-seq data (2 samples), Mouse ChIP-seq data (8 samples). For the mouse scATAC-seq data (2 samples), there are originally three FASTQ files, R1, R2 and R3 files. The R1 and R2 FASTQ files were merged into one larger file ("R1R2") per sample for submission as paired-end sequencing setting to follow the EGA guidelines. They can be split into individual R1 and R2 files in order to be processed by Cell Ranger software. The files with IC1 suffix are CHIP-seq Input control for anti-KDM6B antibody pull down experiments and the files with IC2 suffix are CHIP-seq Input control for anti-H3K27ME3 antibody pull down experiments in murine model.

Dataset EGAD00001010073

BLUEPRINT EpiVar ChIP-seq for naive CD4+ T-cells

Study EGAS00001000753

Mediator ChIP-Seq datasets in human islets

6 ChIP-Seq datasets of Mediator in human pancreatic islets from 6 donors

Dataset EGAD00001005202

Cohesin ChIP-Seq datasets in human islets

3 ChIP-Seq datasets of Cohesin in human pancreatic islets from 3 donors

Dataset EGAD00001005203

Plasma RNA sequencing

Study EGAS00001000731

Reference epigenome SMC05_ChIP-Seq(H3K27me3) data generated from KEP study

A SMC05_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

Dataset EGAD00001003849

Reference epigenome SMC06_ChIP-Seq(H3K27me3) data generated from KEP study

A SMC06_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

Dataset EGAD00001003850

Reference epigenome SMC01_ChIP-Seq(H3K27me3) data generated from KEP study

A SMC01_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

Dataset EGAD00001003845

Reference epigenome SMC02_ChIP-Seq(H3K27me3) data generated from KEP study

A SMC02_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

Dataset EGAD00001003846

Reference epigenome SMC03_ChIP-Seq(H3K27me3) data generated from KEP study

A SMC03_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

Dataset EGAD00001003847

Reference epigenome SMC04_ChIP-Seq(H3K27me3) data generated from KEP study

A SMC04_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

Dataset EGAD00001003848

Reference epigenome SMC07_ChIP-Seq(H3K27me3) data generated from KEP study

A SMC07_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

Dataset EGAD00001003851

Reference epigenome SMC08_ChIP-Seq(H3K27me3) data generated from KEP study

A SMC08_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

Dataset EGAD00001003852

Reference epigenome SMC09_ChIP-Seq(H3K27me3) data generated from KEP study

A SMC09_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

Dataset EGAD00001003853

STAG2-ChIP-Seq of STAG2-mutated and cohesin-wildtype adult AMLs

ChIP-Seq targeting the cohesin subunit STAG2 in STAG2-mutant or cohesin wildtype adult AMLs.

Dataset EGAD00001011205

RNA Splicing Dysregulation in the Pathogenesis of Chronic Lymphocytic Leukemia

RNA splicing dysregulation is a hallmark of cancers, promoting the onset and progression of disease. In chronic lymphocytic leukemia (CLL), spliceosome mutations leading to aberrant splicing occurs in approximately 20% of patients. However, the underlying mechanism for splicing defects in spliceosome unmutated CLL cases remains elusive. To discover posttranscriptional regulation of RNA splicing, we performed RNA sequencing using RNA derived from B cells from 6 healthy donors and 36 CLL patients, along with MAZTER sequencing from 9 CLL patients (8 matched with RNA sequencing cohort) and B cells from 5 healthy donors. We found that CLL cells have dysregulated m6A modification sites on transcripts from splicing factors, suggesting a critical role of m6A modification in RNA splicing dysregulation.

Study phs003191

BLUEPRINT Bisulfite-seq and Whole Genome Sequencing of mantle cell lymphoma

Bisulfite-seq and Whole Genome Sequencing of mantle cell lymphoma

Study EGAS00001001638

Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

Study EGAS00001006935

CPC-GENE H3K27ac ChIP-seq

CPC-GENE H3K27ac ChIP-seq data comprises 48 tumour samples and 6 benign samples sequenced with single end Illumina HiSeq 2000.

Dataset EGAD00001010296

CTCF-ChIP-Seq of cohesin-mutated and wildtype adult AMLs

ChIP-Seq targeting CTCF in cohesin-mutated (STAG2 or RAD21 mutations) and wildtype adult AMLs (CTRL-AMLs).

Dataset EGAD00001011200

Integrated Analysis of Multimodal Single-Cell Datasets for SARS-CoV-2 Vaccination

The study aimed to explore immune responses during a time course of BNT162b2 mRNA vaccination. To better characterize these responses, we utilize a suite of multi-modal single-cell sequencing technologies to identify and characterize antigen-specific CD8+ T cells. We leverage an integrative analysis strategy to characterize five molecular modalities in these cells. Our dataset enables the discovery of new subpopulations, molecular signatures, and developmental regulators of these cells. Moreover, we identify these cells in SARS-CoV-2 infected patients and demonstrate their positive predictive value for subsequent clinical recovery. The sequence data of CITE-seq, ASAP-seq and ECCITE-seq experiments are deposited in dbGaP. Peripheral blood mononuclear cell (PBMC) samples for CITE-seq and ASAP-seq were collected from six healthy donors at four time points: immediately before (Day 0) vaccination, after primary vaccination (Day 2, Day 10), and seven days after boost vaccination (Day 28). PBMC samples for ECCITE-seq were collected from eight healthy donors on Day 28.

Study phs003322

Gene regulation of human CD4+ Treg ChM-seq

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). The final quality filtered set included 91 individuals with H3K27ac ChM-seq and 88 with H3K4me3 ChM-seq.

Dataset EGAD00001004828

ChIP-seq fastq and alignment files

ChIP-seq experiments: fastq files; both ChIP and Input for each sample. Illumina HiSeq 2500. ChIP-seq alignment files for trimmed, mapping q20 and nonredundant reads; both ChIP and Input for each sample. Software: Trim Galore v0.3.7; Bowtie 2 v2.1.0; samtools v1.7

Dataset EGAD00001006279

Whole genome landscape of adult T-cell leukemia/lymphoma

Whole-genome sequence (WGS) data of tumor-normal pairs from 139 ATL patients and RNA sequence (RNA-seq) data of tumors from 28 ATL patients.

Dataset EGAD00001008289

RNA, ATAC, ChIP datasets from Ankylosing Spondylitis patients and Healthy Controls

This dataset consists of functional genomic data from 20 Ankylosing Spondylitis patients and 35 Healthy Controls taken from CD4+ T cells, CD8+ T cells and CD14 Monocytes. It contains 364 paired end fastq files consisting of 104 total RNA-seq samples and 116 ATAC samples, for ChIP there are 46 H3K4me3 samples, 46 H3K27ac samples and 3 H3K4me1 samples, along with 49 paired input samples. The samples were sequenced on Illumina HiSeq4000, Illumina NextSeq500 and Illumina NovaSeq 6000 platforms.

Dataset EGAD00001008758

scRNAseq of colonic organoids derived from biopsies taken from healthy human individuals treated with IL22

scRNAseq dataset of colonic organoids derived from epithelium from biopsies taken from three healthy human individuals. The organoids have either been grown in standard conditions (control) or treated with IL22 (treated). Includes 6 samples in total, one control from each individual (ctrl1, ctrl2, ctrl3) and one treated from each (treat1, treat2, treat3). The samples have been multiplexed using the antibody hashing technique. The 6 samples have been pooled into the one organoids sample. In order to analyse the raw files, they have to be demultiplexed first. Information necessary for demultiplexing, as well as which files belong to which sample, can be found in the map_file.csv, attached to each sample. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into HTO (hashtag) and RNA (transcriptome) files. HTO has one index (I1) and two read (R1, R2) files and RNA has two index (I1, I2) and two read (R1, R2) files. The fastq files are for the pooled (organoids) sample and need to be demultiplexed. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Since count matrices have been created after the demultiplexing step, there’s one matrix for each of the 6 individual samples. scRNA-seq data from human colon organoids was analysed in the same manner as for the Colitis dataset, apart from the following changes. Data was generated with the Cell Hashing technique, which uses oligo-tagged antibodies against surface proteins to barcode single cells. This allows for samples to be multiplexed together and run in a single experiment. The data was demultiplexed using the HTODemux() function from Seurat (Hao et al., 2021).

Dataset EGAD00001010168

ChIP-seq for G3-MB

ChIP-seq for H3K27ac and NeuroD1 in Group 3 Medulloblastoma cell models. Input DNA for each sample and target is also included.

Dataset EGAD50000002303

Reference epigenome ADMSC01_ChIP-Seq(H3K27me3) data generated from KEP study

A ADMSC01_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

Dataset EGAD00001003854

Reference epigenome ADMSC02_ChIP-Seq(H3K27me3) data generated from KEP study

A ADMSC02_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

Dataset EGAD00001003855

Reference epigenome ADMSC03_ChIP-Seq(H3K27me3) data generated from KEP study

A ADMSC03_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

Dataset EGAD00001003856

Reference epigenome ADMSC04_ChIP-Seq(H3K27me3) data generated from KEP study

A ADMSC04_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

Dataset EGAD00001003857

Melanoma and Cancer-Associated Fibroblast Short-Term Cultures Derived from Patient Metastases

The purpose of this study was to obtain tissue specimens derived from patients with melanoma to generate research tools to advance our understanding of the genetics, pathogenesis, and therapeutics of melanoma. Briefly, tissue was obtained from metastatic lesions and used to generate clonal primary cell lines from melanoma cells and fibroblasts from the tumor microenvironment. RNA was extracted from low passage cell lines using Trizol reagent. cDNA libraries were prepared using the TruSeq mRNA sample preparation kit, v2 (Illumina) and sequenced on the HiSeq 2000 platform (Illumina). The submitted files are bam files that contain both unaligned and aligned reads (human genome, build hg19).

Study phs001115

Dynamics of tumor ecosystems and microbiome in response to neoadjuvant atezolizumab, bevacizumab, and FOLFOX treatment in patients with unresectable colorectal cancer with liver metastasis

This study aims to explore the effects of neoadjuvant atezolizumab, bevacizumab, leucovorin, 5-fluorouracil, and oxaliplatin (ABFOLFOX) in patients with unresectable colorectal liver metastases (CRLM), focusing on the molecular dynamics of tumor ecosystems (TE) of CRLM and their impact on treatment outcomes. The study comprises two cohorts with CRLM tissue samples analyzed with RNA sequencing and immunohistochemical staining: cross-sectional cohort A (n = 60, CRLM treated with or without neoadjuvant chemotherapy) and prospective cohort B (n = 20 with serial sampling and treated with ABFOLFOX). Shotgun metagenomic sequencing was done for stool samples from cohort B.

Study EGAS50000000677

Single Chromatin Fiber Profiling in the Human Brain

We developed a human postmortem brain-applicable ‘Fiber-seq' protocol for genome-scale, PCR-free single molecule sequencing of on average 8-10kb long chromatin fibers, to map nucleosome positioning and nucleosome-depleted regions which include, for example, active promoters and enhancers. We generated two Fiber-seq reference sets, one from sorted non-neuronal NeuN- prefrontal cortex (PFC) nuclei from a 32 year old female donor, with total of 11,143,795 reads/fibers, and median of 30-fold genomic coverage. The other reference set was generated on sorted prefrontal NeuN+ neurons, from two 24 year old brain donors (1 female/1 male), with a combined total read/fiber count of 4,749,556 and median of 20-fold genomic coverage. Each of the peaks in the Fiber-seq libraries seq signal correlated with the ATAC peak levels in the neuronal and non-neuronal ATAC-seq libraries, respectively (promoters, clusters 1, 3; NeuN+, r = 0.574; NeuN-, r=0.683, PHowever, Fiber-seq detected 19,978 highly significant peaks which, while showing some non-significant/near-background ATAC-Seq alignments, lacked a corresponding site-specific enrichment in conventional short-read ATAC- and ChIP-seq datasets. However, 60% of these peaks were in repetitive DNA elements. Therefore, long read single chromatin fiber sequencing, which exceed the base pair length of conventional short-read libraries by two orders of magnitude, could capture many actively regulated repeat elements at the site of specific gene loci, that otherwise would remain unmappable by conventional ATAC-, and histone- ChiP-seq.

Study phs003771

MuTHER_adipose_tissue_small_RNA_expression

We investigate the naturally occurring variation of small RNA expression in conjunction with genetic and gene expression variation. We shall assess the variation in subabdominal fat tissue small RNA levels in 168 unrelated MuTHER individuals. Using gene expression data from the same samples, we can survey how much the small RNA expression contributes to the variance in gene expression profiles. We can also take advantage of the high density genotyping data on these samples to identify genetic associations of small RNA expression levels, and the downstream effect of the genetic variants in small RNA sequence. Previous small RNA sequencing efforts have also extended the repertoire of small RNAs, and we hope to potentially find additional small RNAs active in adipose tissue biology. Altogether, the project should provide an exciting view into small RNA biology in humans, and lead to development of new methodology for analysis of molecular phenotype data.

Study EGAS00001000212

Next generation sequencing of diffuse intrinsic pontine glioma samples to identify recurrent mutations, variations, and expression patterns to define novel therapies

Diffuse intrinsic pontine glioma (DIPG) is an extremely rare (~350 cases/year) and universally fatal childhood brain cancer. Standard clinical strategies such as chemotherapy and radiotherapy show only transient improvement in patient condition and result in negligible change in survival, DIPG remains at below 1% survival after 5 years. Prioritization of panobinostat through previous cooperative work resulted in a phase 1 clinical trial. Nonetheless, new therapies for DIPG must be identified to further dramatically change the statistics for DIPG. To identify novel therapy strategies for DIPG, we performed whole exome(16 new samples, 22 previously published samples, 38 in total with 26 matched normal) and RNA deep sequencing (17 new samples, 11 previously published samples) on a cohort of new patient samples. Sequencing results aid in the identification of recurrent mutations/variations and endotypic expression profiling to identify new therapeutic and treatment strategies for DIPG.

Study phs001526

MP2PRT-MNG: Identifying Novel Molecular Markers of Response to Radiotherapy in Meningiomas Using Samples from the RTOG-0539 (NCT00895622)

The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. NRG RTOG (Radiation Therapy Oncology Group)-0539, which was a nonrandomized phase II cooperative group trial in 2009, was selected for inclusion in this program. NRG RTOG-0539 assigned patients with histologically confirmed diagnosis of meningioma to 1 of 3 risk groups based on 2007 WHO grade, resection extent, and recurrence status, and radiotherapy was given per protocol to the intermediate- and high-risk cases. Under the MP2PRT program, DNA methylation profiling, RNA sequencing, and whole exome sequencing were performed on clinical trial cases with available tissue for molecular analyte extraction and subsequent sequencing. Raw molecular data with metadata are available for this study.

Study phs003707

Epigenomics and Single-cell Sequencing Define a Developmental Hierarchy in Langerhans Cell Histiocytosis

Langerhans cell histiocytosis (LCH) is a rare neoplasm predominantly affecting children. It occupies a hybrid position between cancers and inflammatory diseases, and it provides an attractive model for studying cancer development. To explore the molecular mechanisms underlying the pathophysiology of LCH and its characteristic clinical heterogeneity, we investigated the transcriptomic and epigenomic diversity in primary LCH lesions. Using single-cell RNA sequencing, we identified multiple recurrent types of LCH cells within these biopsies, including putative LCH progenitor cells and several subsets of differentiated LCH cells. We confirmed the presence of proliferative LCH cells in all analysed biopsies using immunohistochemistry, and we defined an epigenomic and gene-regulatory basis of the different LCH cell subsets by chromatin accessibility profiling. In summary, our single-cell analysis of LCH uncovered an unexpected degree of cellular, transcriptomic, and epigenomic heterogeneity among LCH cells, indicative of complex developmental hierarchies in LCH lesions.

Study EGAS00001003822

Nivolumab plus chemotherapy or ipilimumab in gastroesophageal cancer: CheckMate 649 biomarker analyses

First-line nivolumab-plus-chemotherapy demonstrated superior overall survival (OS) versus chemotherapy for advanced gastroesophageal adenocarcinoma (CheckMate 649). Nivolumab-plus-ipilimumab provided durable responses and higher survival rates versus chemotherapy; however, the prespecified OS significance boundary was not met. To identify biomarkers predictive of differential efficacy outcomes, exploratory analyses were performed using whole-exome sequencing and RNA sequencing. Nivolumab-based therapies demonstrated improved efficacy versus chemotherapy in hypermutated and, to a lesser degree, Epstein Bar Virus-positive tumors compared with chromosomally unstable and genomically stable tumors. Within the KRAS-altered subgroup, only patients treated with nivolumab-plus-chemotherapy demonstrated improved OS benefit versus chemotherapy. Low stroma gene expression signature scores were associated with OS benefit with nivolumab-based regimens; high regulatory T-cell signatures were associated with OS benefit only with nivolumab-plus-ipilimumab. Our analyses suggest that distinct and overlapping pathways contribute to the efficacy of nivolumab-based regimens in gastroesophageal adenocarcinoma.

Study EGAS50000000747

Comprehensive Genomic and Transcriptomic Analysis of Rare Cancers for Guiding of Therapy (H021)

Here we analyzed the molecular profiles and clinical outcomes of 1,310 patients (proportion of rare cancers, 75%) enrolled in a prospective observational study by the German Cancer Consortium that applies whole-genome/exome and RNA sequencing to inform the care of adults with incurable cancers. Based on 472 single and six composite biomarkers, a cross-institutional molecular tumor board provided evidence-based management recommendations, including diagnostic reevaluation, genetic counseling, and experimental treatment, in 88% of cases. Recommended therapies were administered in 362 of 1,138 patients (31.8%) and resulted in significantly improved response and disease control rates (23.9% and 55.3%, respectively) compared to previous therapies, translating into a progression-free survival ratio >1.3 in 35.7% of patients.

Study EGAS00001004813

The Proteogenomic Subtypes of Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is an aggressive blood cancer with poor prognosis. We report a comprehensive proteogenomic analysis of bone-marrow biopsies from 252 uniformly treated AML patients to elucidate the molecular pathophysiology of AML in order to inform future diagnostic and therapeutic approaches. In addition to in-depth quantitative proteomics, our analysis includes cytogenetic profiling and DNA/RNA sequencing. We identify five proteomic AML subtypes, each reflecting specific biological features spanning genomic boundaries. Two of these proteomic subtypes correlate with patient outcome, but none are exclusively associated with specific genomic aberrations. Remarkably, one subtype (Mito-AML), which is only captured in the proteome, is characterized by high expression of mitochondrial proteins and confers poor outcome, with reduced remission rate and shorter overall survival upon treatment with intensive induction chemotherapy. Functional analyses reveal that Mito-AML is metabolically wired towards stronger complex I dependent respiration and is more responsive to treatment with the BCL2 inhibitor venetoclax.

Study EGAS00001005950

Chip-Seq sequencing data of Atypical teratoid/rhabdoid tumors (ATRT)

Dataset EGAD00001003408

Integrated clinical, whole genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

We report the first combined analysis of whole genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole genome and transcriptome sequence was obtained from 9 anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 years prior to death. Transcriptome analysis revealed increased expression of AR-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only 1 of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today given this knowledge, use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations is critical for actionability, and can only be determined through analysis of multiple sites of metastasis. Our findings suggest that a large set of deeply analyzed cases could serve as powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials.

Dataset EGAD00001001869

RNA-sequencing of ex situ stimulated donors blood cells

Cells from whole blood stimulation assay were cryopreserved. The cryopreserved cells were thawed and subjected to RNA preparation. RNA obtained were subjected to for bulk sequencing.

Study EGAS50000001077

RNA-seq of MPNSTs

Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are highly aggressive soft-tissue sarcomas with a poor prognosis and a lack of therapeutic options. In this study, we analyse the whole-transcriptome MPNST and combine them with WGS data from a partially overlapping sample set. These analyses and the inclusion of another public dataset allow us to identify three genomic MPNST subgroups with distinct biological and clinicopathological features that can inform management and precision treatments. Published in "Identification of Malignant Peripheral Nerve Sheath Tumor (MPNST) subtypes with distinct genomic identities."

Study EGAS50000001733

Long read mRNA sequencing of human neural retinal samples - Usher syndrome transcript landscape

Long-read (PacBio) RNA sequencing dataset of three neural retinal samples. Three PacBio libraries were prepared according the 'standard workflow' optimized for sequencing transcripts centered around 2kb. Additionally one Library (input HNR_S2) was prepared according an optimized 'long workflow' to enrich for larger transcripts up to >10kb. To further enhance the capture of full-length transcripts for USH2A and ADGRV1 (USH2C) genes, we also employed a targeted enrichment approach using the Samplix Xdrop System, followed by PacBio long-read sequencing. USH2A and ADGRV1 enrichment was performed by targeting '5- mid and 3' targets of the respective genes. Finally, we also added ONT (Oxford Nanopore technology) long-read mRNA sequencing of three independent neural retina samples. These data were used for the validation of events observed from the Iso-Seq and Samplix data. The ONT datasets contain sequencing data of the Usher-associated genes. Files are raw BAM, and CRAM format files generated by a Sequel II machine. Additionally, the ccs3 BAM format files are included.

Dataset EGAD50000000720

Single Cell RNAseq at various stages of HiPSCs differentiating toward definitive endoderm and endoderm derived lineages

When comparing the differentiation capacities of pluripotent stem cell lines that have different genetic backgrounds, batch to batch experimental variablility poses a significant challenge, especially when trying to identify smaller effects. One way to address this issue is to differentiate several different lines in the same culture dish, thereby elimating experimental variation. In addition, it allows researchers to analyze many more lines with less experiments. Parallel single cell RNA-Seq exploits that individual cells are tagged and hence each cell can be reliably assigned to the donor of origin based on the genetic variants it contains. In addition, analyzing the genetic signature of single cells within a differentiating population can reveal differentation stages that are not easily detected in bulk RNAseq data. 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/

Dataset EGAD00001005741

RNAseq of circulating monocytes of familial hypercholesterolaemia (FH) patients before and after treatment, and healthy controls.

RNAseq of circulating monocytes of familial hypercholesterolaemia (FH) patients before and after treatment, and healthy controls. Please cite original paper: Monocyte and macrophage lipid accumulation results in downregulated type-I interferon responses. Willemsen et al. Frontiers in Cardiovascular Medicine (2022) Familial hypercholesterolemic patients (n=10) and healthy subjects (n=9): the study population, design, and further processing of these human study subjects and their samples have been extensively described (Stiekema et al., 2021). Briefly, untreated FH patients who indicated to start lipid-lowering therapy (statin, PCSK9 antibody, and/or ezetimibe) according to their treating physician were included. The healthy controls were age, sex, and body mass index (BMI) matched with the FH patients. After inclusion, FH patients fasted for at least 9 hours before blood samples were drawn for lipid measurements and monocyte isolation. This was repeated after 12 weeks of lipid-lowering therapy. RNA-seq was performed on circulating monocytes. V1 = visit 1. V2 = visit 2.

Dataset EGAD00001008967

RNA sequencing of lung fibroblasts

Study EGAS00001007857

bulk TCR seq

bulk TCR-seq data IMCISION on the PBMCs of responding patients bulkTCR-seq data generated with the immunoSEQ platform (Adaptive Biotechnologies) on PBMCs of responding patients, pre- and post-treatment.

Dataset EGAD00010002546

12214 results for "cancer rna-seq"

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