7199 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

in 16.88 milliseconds.

• OT2_Illumina_RNA_MET_CELL

  RNAseq on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample (OT2_cohort)

  Dataset EGAD00001003365

• Illumina_RNA_MET-XEN

  RNAseq of Patient-derived xenograft derived from colorectal cancer metastasis sample

  Dataset EGAD00001002076

• Spatial Transcriptomic data from Invasive lobular breast carcinoma (ILC)

  Spatial transcriptomic data from Invasive lobular breast carcinoma (ILC) Djerroudi et al, Nature Communication

  Study EGAS50000001735

• The Effects of Long-Term Heavy Metal Exposure on Transcriptome Landscape in Human Peripheral Blood Cells

  The present study investigates the impact of long-term residence in a mining area on transcriptome changes induced by heavy metal exposure in human peripheral blood mononuclear cells (PBMCs) from 65 healthy subjects selected from the general population. This study includes the same participants which were recruited in our previous investigation on heavy metal long-term environmental exposure-related gene-specific methylation changes (phs003392.v1.p1). We performed a differential expression analysis to compare the mRNA transcriptome of 31 residents from the mining region (MRR) - individuals living in the Kapan mining area with reported environmental exposures to heavy metals - with that of 34 residents from non-mining regions (NMR) - individuals residing at a considerable distance from mining locations. We also evaluated the potential association of gene expression profiles with the blood metallome, including levels of Ca, Mg, Co, Fe, Mn, Cu, Mo, Se, Zn, As, Sb, Tl, Be, V, Ni. Poly-A selected strand-specific mRNA library was prepared with Illumina Stranded mRNA Prep kit. The sequencing was performed on the Illumina NovaSeq-6000 platform with 38.5 million single-end 100 bp reads on average generated per sample. Quality checking of the sequencing data was performed using Illumina Basespace reports and the program FastQC (V0.10.1). Reads were aligned against the Human Genome Hg38 using STAR (version 2.7.1a). According to our findings, long-term residence in a mining area is correlated with alterations in the blood transcriptome, with responses varying by sex. Pathway analysis revealed upregulation of immune response related pathways, and downregulation of translation and ribosome biogenesis in the PBMCs of the MRR. Pathways related to metal ion transmembrane transport, epigenetic modifications (histone deacetylases (HDACs) and DNA methylation) were upregulated in males, while in females mostly transcripts involved in inflammation and cytokine mediated signaling were upregulated. Additionally, among the dysregulated pathways, the TNF-α signaling via NF-κB showed opposite changes in females and males.

  Study phs003657

• Rearrangements of the MAST Kinase and Notch Gene Families in Breast Cancer

  Paired-end transcriptome sequencing was performed on a panel of breast cancer cell lines and tissues and a set of benign cell line and tissue controls. Analyses of the paired end sequences were performed and chimeric transcripts derived from gene rearrangement events were identified. Sequencing was performed on Illumina GAII and HiSeq 2000 platforms with read lengths from 40 to 100 bases.

  Study phs000513

• GeoMx DSP of NGS mRNA expression in pre-treatment biopsies from patients with metastatic triple-negative breast cancer treated with PARP inhibitors.

  This dataset contains GeoMx digital spatial profiling (DSP) data from 12 FFPE pre-treatment biopsies of metastatic HR-altered breast cancer patients subsequently treated with PARP inhibitors (Olaparib or Talazoparib). Samples were collected from primary breast tumors (n=7) and metastatic sites including lymph nodes (n=2), bone (n=2), and brain (n=1). Tissue sections were stained for pan-cytokeratin (PANCK) to selectively profile tumor cells, with NGS-based transcriptome data generated for both PANCK+ and PANCK- regions. The dataset includes raw data files (176 fastq files) along with clinical annotations.

  Dataset EGAD50000001932

• Diverse modes of genomic alterations in hepatocellular carcinoma

  Hepatocellular carcinoma is the most prevalent type of liver cancer. We intended to study the genomic landscape of this disease. We conducted whole-genome, exome and transcriptome sequencing for 42 patients. We show diverse modes in which the HCC genome is affected in these patients, including well-known and novel mutations, structural variations, and Hepatitis B-virus integration into the genome.

  Study EGAS00001000824

• Whole-genome bisulfite sequencing analysis of low-grade astrocytomas in the ICGC PedBrain Tumor Project

  Pilocytic Astrocytoma (PA) is the most common pediatric brain tumor. While genome and transcriptome landscapes are well-studied, data of the complete methylome, tumor cell composition and immune infiltration are scarce. We generated whole genome bisulfite sequence data (WGBS) of nine PAs to find evidence for a link of focal methylation differences and differential gene expression to immune infiltration.

  Study EGAS00001004019

• Role of cohesin/CTCF in human monocyte differentiation

  Here we study genome architecture in a postmitotic differentiation setting, the differentiation of human blood monocytes (MO). We profiled and compared epigenetic, transcriptome and 3D conformation landscapes during MO differentiation (either into dendritic cells or macrophages) across the genome, with and without siRNA-mediated depletion of RD21 or CTCF, and detected numerous architectural changes, ranging from higher level compartments

  Study EGAS00001005508

• The role of gut microbiota in metabolic diseases

  Diabetes is a major disease in the elderly and is responsible for increased risk of myocardial infarction and stroke. Recently, the relationship between microbiota and diabetes has been reported in animals and humans. In this study, blood, stool, and saliva samples were collected from examinees at the University of Tokyo Health Screening Center, and 16S rRNA and metagenomic analyses were performed to determine the variation of microbiota. Furthermore, metabolome analysis and transcriptome analysis (CAGE analysis) using blood were performed to reveal changes in host metabolites and gene expression. By comparing the host- and bacteria- derived information with the metabolic parameters, we analyzed whether microbiota can be a predictor of metabolic diseases.

  Study JGAS000569