7188 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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• RNA-Seq of Whole Blood from Pediatric Sickle Cell Anemia (SCA) Patients

  The aim of this study is to define the immune cell transcriptome by next generation RNA sequencing in blood from individuals with SCA, in comparison to healthy African American controls. This study has a cross-sectional case-control design. We will compare the transcriptome profiles of blood mononuclear cells from healthy age-matched African American children without cardiovascular disease or risk factors (“Controls”) to those of children with SCA, age 5 -21 years, who are not receiving chronic red blood cell transfusions or hydroxyurea therapy to identify genes that are differentially expressed in SCA. 

  Study phs002687

• RNA seq before and after cold pressor test

  The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken for RNA-sequencing.

  Study EGAS00001006690

• RNAseq of pre- and post-5AZA-treated head and neck cancer patients refractory to anti-PD-1 therapy

  RNA sequencing (RNA-seq) was performed on baseline (before low-dose 5-aza treatment) and on-treatment (low-dose 5-aza treatment for 5 or 10 days) tumor samples from eight participants with head and neck cancer who were refractory to anti-PD-1 therapy. RNA library preparations, sequencing reactions, and initial bioinformatics analyses were conducted at GENEWIZ, LLC. In total, 16 150-bp pair-end RNAseq data were generated.

  Dataset EGAD50000001010

• Human glioblastoma single cell RNA-seq from two patient, sampled at different positions within as well as outside tumor

  We performed deep single-cell RNA sequencing of two rare glioblastoma cases where tissue could be sampled from tumor core to macroscopically normal cortex. We processed two to three replicates per sample with the 10X Genomics V3.1 kits. Deep sequencing was performed to about 100,000 reads per cell on the Illumina NovaSeq 6000 platform, resulting in a total of 37 BAM files.

  Dataset EGAD50000001500

• RNA-seq after drug perturbation of primary lymphoma samples

  3'-end low-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule inhibitors (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). Sequencing was performed on the Illumina HiSeq4000. The dataset contains FASTQ files.

  Dataset EGAD50000002166

• RNA-Seq of GM adipose tissue samples

  This dataset contains 210 fastq files (RNA sequencing was performed in two centers) from 105 individuals (106 files in subcutaneous tissue and 104 files in visceral tissue). Of the 210 fastq files, 129 files are in PEx100 mode (appeared in a single fastq file) and 81 files are in PEx49bp mode (appeared in two separate fastq files). Sequencing was done on the Illumina HiSeq2000 platform.

  Dataset EGAD00001010253

• UCL COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of COVID19 patients recruited from University College London. 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 derived from previous single-cell RNA-sequencing are provided (VCF) to aid demultiplexing of single-cell and assignment to specific patient donor samples.

  Dataset EGAD00001007865

• RNA Sequencing datasets - Project "Multi-omics analysis of Parkinson’s disease midbrains"

  The dataset contains FASTQ files referring to the study "Multi-omics analysis of Parkinson’s disease midbrains". For this project, RNA was isolated from human postmortem midbrain tissue (PD and Control samples). Libraries were prepared with the TruSeq Small RNA library prep (Small RNA Seq) and the TruSeq Stranded Total RNA Kit (for transcriptomics), both from Illumina. Sequencing for both experimental setups was conducted in the Illumina HiSeq4000.

  Dataset EGAD00001006883

• Bulk RNA-sequencing data of advanced hepatocellular carcinoma (HCC) patients treated with atezolizumab plus bevacizumab.

  The dataset includes FASTq files and normalised gene expression counts from bulk RNA-sequencing of pre-treatment tumour (n=39) and adjacent non-tumour tissue samples (n=13) from advanced hepatocellular carcinoma (HCC) patients treated with atezolizumab plus bevacizumab. Specifically, RNA was extracted from the FFPE tumour tissue using RNeasy Plus Mini Kit (Qiagen), according to the manufacturer’s instructions. RNA quality and quantity were evaluated using Agilent RNA 600 Pico Chips (Agilent Technologies). Sequencing libraries were prepared using the SMARTer Stranded Total RNA-seq kit v3 (Takara Bio). Sequencing was performed on an Illumina NovaSeq 6000 system. After obtaining the Fastq files, read 2 UMIs and adapters were trimmed using seqtk (v1.2), reads were aligned using STAR (v2.7.7a) to the human reference genome (GRCh38) and quantified with HTSeq (v2.0.2).

  Dataset EGAD50000001227

• Assessing gene expression profiling from FFPE Patient Samples: A Comparison of Two Library Preparation Approaches and Recommendations

  Next-Generation Sequencing (NGS) has transformed cancer research and clinical practice, with Whole Exome Sequencing (WES) driving advances in mutational profiling and personalized oncology. Yet, transcriptomic signatures remain essential for understanding disease mechanisms, including therapy resistance pathways. RNA sequencing (RNA-seq), however, faces unique challenges when dealing with low-input or degraded RNA, as often found in archival formalin-fixed paraffin-embedded (FFPE) tissues. Although previous studies have compared library preparation protocols, rapidly evolving technologies call for updated evaluations. Here, we present a direct comparison of two FFPE-compatible stranded RNA-seq library preparation kits: TaKaRa™ SMARTer® Stranded Total RNA-Seq Kit v2 (Kit A) and Illumina Stranded Total RNA Prep Ligation with Ribo-Zero Plus (Kit B). Both kits generated high-quality RNA-seq data, yet important differences emerged. Notably, Kit A achieved comparable gene expression quantification to Kit B while requiring 20-fold less RNA input, a crucial advantage for limited samples, albeit with increased sequencing depth. We critically discuss these results in relation to RNA availability, technical performance, cost-effectiveness, processing time, and automation potential, offering practical guidance for selecting optimal RNA-seq strategies in clinical and translational research settings

  Study EGAS50000001066