093cacae-4ce9-4afd-b9f0-bdb220977e15 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001006961 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Multiomics of faecal samples collected from individuals in families with multiple cases of type 1 diabetes mellitus (T1DM) over 3 or 4 months. Metagenomic and metatranscriptomic sequencing and metaproteomics were carried out, as well as whole human genome sequencing. Phenotypic data is available.
2016-08-22 | PXD003791 | Pride
Project description:This RNA-seq dataset contains whole blood transcriptome profiles from individuals with X-linked familial Kallmann syndrome associated with a new variant in the ANOS1 gene (c.452G>C). Samples were collected from two affected male siblings, their mother, and controls. Total RNA was extracted from whole blood, and ribosomal RNA was depleted prior to library preparation using the KAPA RNA HyperPrep Kit with RiboErase. Paired-end RNA sequencing was performed on the Illumina NovaSeq X Plus platform, generating approximately 100 million paired-end reads per sample. Sequencing utilized 1% of a 10B, 300-cycle flow cell, which produces up to 20 billion paired-end reads per flow cell. This dataset enables a comprehensive analysis of gene expression and splicing patterns associated with ANOS1-related Kallmann syndrome, providing a valuable resource for studying transcriptomic alterations in hypogonadotropic hypogonadism.
2026-02-16 | GSE318901 | GEO
Project description:Multiomics of faecal samples collected from individuals in families with multiple cases of type 1 diabetes mellitus (T1DM) over 3 or 4 months. Metagenomic and metatranscriptomic sequencing and metaproteomics were carried out, as well as whole human genome sequencing. Phenotypic data is available.
2017-10-19 | MSV000081630 | MassIVE
Project description:The study aimed to investigate molecular signatures in peripheral blood of individuals affected by metabolic syndrome (MetS) and different degrees of obesity. Metabolic health of 1204 individuals was assessed, and 32 subjects were recruited to four study groups: MetS lean, MetS obese, “healthy obese” and healthy lean. Whole-blood transcriptome next generation sequencing with functional data analysis was carried out.
2020-02-18 | GSE145412 | GEO
Project description:Intervention type:DRUG. Intervention1:Huaier, Dose form:GRANULES, Route of administration:ORAL, intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary. Control intervention1:None.
Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
For small RNA libraries, data analysis includes sequencing data process and sequencing data process QC, small RNA distribution across the genome, rRNA, tRNA, alignment with snRNA and snoRNA, construction of known miRNA expression pattern, prediction New miRNA and Study of their secondary structure Based on the expression pattern of miRNA, we perform not only GO / KEGG annotation and enrichment, but also different expression analysis.. Timepoint:RNA sequencing of 240 blood samples of 80 cases and its analysis, scheduled from June 30, 2022..
| 2612481 | ecrin-mdr-crc
Project description:We compared the DNA methylation patterns in blood from individuals with two rare neurodevelopmental disorders (Childhood-onset dystonia (DYT-KMT2B) and Kabuki syndrome) and healthy control samples
2022-04-17 | GSE199836 | GEO
Project description:To study the difference of gene expression pattern of whole blood between klinefelter’s syndrome and normal individuals and discovered the disease-related genes and biological pathway. 717 differentially expressed genes (480 up regulated, 237 down regulated) were identified between whole blood samples of the klinefelter’s patients and normal volunteers. Function enrichment analysis identified a number of genes involved in immune response, metabolism etc. Three genes with significant down-regulation in Klinefelter’s patients were also confirmed by qRT-PCR.Using the whole blood as material in patients with klinefelter’s syndrome, the differentially expressed genes was identified. It is noticed that genes involved in metabolism pathways were significantly decreased. These observations may suggest aberrant of metabolism may be important for developing the klinefelter’s syndrome. In addition, our results also show that no X-linked genes are overexpression in the peripheral blood cells of KS patients.
2013-09-01 | GSE47584 | GEO
Project description:The etiology of severe forms of COVID19, especially in young patients, remains a salient unanswered question. Here we build on a 3-tier cohort where all individuals/patients were strictly below 50 years of age and where a number of comorbidities were excluded at study onset. Besides healthy controls (N=22), these include patients in the intensive care unit with Acute Respiratory Distress Syndrome (ARDS) (“critical group”; N=47), and those in a non-critical care ward under supplemental oxygen (“non-critical group”, N=25). This highly curated cohort allowed us to perform a deep multi-omics approach which included whole genome sequencing, whole blood RNA-sequencing, plasma and peripheral-blood mononuclear cells proteomics, multiplex cytokine profiling, mass-cytometry-based immune cell profiling in conjunction with viral parameters i.e. anti-SARS-Cov-2 neutralizing antibodies and multi-target antiviral serology. Critical patients were characterized by an exacerbated inflammatory state, perturbed lymphoid and myeloid cell compartments, signatures of dysregulated blood coagulation and active regulation of viral entry into the cells. A unique gene signature that differentiates critical from non-critical patients was identified by an ensemble machine learning, deep learning and quantum computing approach. Within this gene network, Structural Causal Modeling identified several ARDS driver genes, among which the up-regulated metalloprotease ADAM9 seems to be a key driver. Inhibition of ADAM9 ex vivo interfered with SARS-Cov-2 uptake and replication in human epithelial cells. Hence we apply a machine learning approach to identify driver genes for severe forms of COVID-19 in a small, uncluttered cohort of patients.
2021-11-25 | PXD025265 | Pride
Project description:Primary objectives: The primary objective is to investigate circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Primary endpoints: circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
| 2533916 | ecrin-mdr-crc
Project description:Whole blood gene expression data from PFAPA syndrome
| PRJNA118383 | ENA