ICGC Breast Cancer Project, RNA seq - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001001323 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:A comprehensive characterisation and analysis of human breast cancers through genome-wide approaches including genomics, transcriptomics and epigenomics.
| EGAS00001001195 | EGA
Project description:A comprehensive characterisation and analysis of 560 human breast cancers through genome-wide approaches including genomics, transcriptomics and epigenomics.
| EGAS00001001178 | EGA
Project description:We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.
| EGAS00001000420 | EGA
Project description:RNA-seq was performed on breast cancer cell lines and primary tumors RNA-seq was performed on 28 breast cancer cell lines, 42 Triple Negative Breast Cancer (TNBC) primary tumors, and 42 Estrogen Receptor Positive (ER+) and HER2 Negative Breast Cancer primary tumors, 30 uninovlved breast tissue samples that were adjacent to ER+ primary tumors, 5 breast tissue samples from reduction mammoplasty procedures performed on patients with no known cancer, and 21 uninvolved breast tissue samples that were adjacent to TNBC primary tumors.
| S-ECPF-GEOD-58135 | biostudies-other
Project description:We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.
2013-01-30 | E-ERAD-145 | biostudies-arrayexpress
Project description:To evaluate the characterisation of N1E-115 neuroblast cells, we conducted the comprehensive gene expression in the N1E-115 cells using RNA-seq.
2025-03-23 | GSE292236 | GEO
Project description:IntroductionOver the last decade, the field of systems vaccinology has emerged, in which high throughput transcriptomics and other omics assays are used to probe changes of the innate and adaptive immune system in response to vaccination. The goal of this study was to benchmark key technical and analytical parameters of RNA sequencing (RNA-seq) in the context of a multi-site, double-blind randomized vaccine clinical trial.MethodsWe collected longitudinal peripheral blood mononuclear cell (PBMC) samples from 10 subjects before and after vaccination with a live attenuated Francisella tularensis vaccine and performed RNA-Seq at two different sites using aliquots from the same sample to generate two replicate datasets (5 time points for 50 samples each). We evaluated the impact of (i) filtering lowly-expressed genes, (ii) using external RNA controls, (iii) fold change and false discovery rate (FDR) filtering, (iv) read length, and (v) sequencing depth on differential expressed genes (DEGs) concordance between replicate datasets. Using synthetic mRNA spike-ins, we developed a method for empirically establishing minimal read-count thresholds for maintaining fold change accuracy on a per-experiment basis. We defined a reference PBMC transcriptome by pooling sequence data and established the impact of sequencing depth and gene filtering on transcriptome representation. Lastly, we modeled statistical power to detect DEGs for a range of sample sizes, effect sizes, and sequencing depths.Results and discussionOur results showed that (i) filtering lowly-expressed genes is recommended to improve fold-change accuracy and inter-site agreement, if possible guided by mRNA spike-ins (ii) read length did not have a major impact on DEG detection, (iii) applying fold-change cutoffs for DEG detection reduced inter-set agreement and should be used with caution, if at all, (iv) reduction in sequencing depth had a minimal impact on statistical power but reduced the identifiable fraction of the PBMC transcriptome, (v) after sample size, effect size (i.e. the magnitude of fold change) was the most important driver of statistical power to detect DEG. The results from this study provide RNA sequencing benchmarks and guidelines for planning future similar vaccine studies.
| S-EPMC9893923 | biostudies-literature
Project description: Not available
| S-BSST1200 | biostudies-other
Project description:Lipids play an important role in energy storage, membrane structure stabilization and signaling. Parasitoids are excellent models to study lipidomics because a majority of them do not accumulate during their free-living life-stage. Studies on parasitoids have mostly focused on the changes in the lipids and gene transcripts in hosts and little attention has been devoted to lipidomics and transcriptomics changes in parasitoids. In this study, a relative quantitative analysis of lipids and their gene transcripts in 3-days-old Lysiphlebia japonica larva (3 days after spawning) and pupae were performed using liquid chromatography, mass spectrometry and RNA-seq. Thirty-three glycerolipids and 250 glycerophospholipids were identified in this study; all triglycerides and the vast majority of phospholipids accumulated in the pupal stage. This was accompanied by differentially regulated lipid uptake and remolding. Furthermore, our data showed that gene transcription was up-regulated in key nutrient metabolic pathways involved in lipid synthesis in 3-days-old larvae. Finally, our data suggests that larva and pupa of L. japonica may lack the ability for fatty acids synthesis. A comprehensive, quantitative, and expandable resource was provided for further studies of metabolic regulation and molecular mechanisms underlying parasitic response to hosts defense.
2021-10-06 | MTBLS409 | MetaboLights
Project description:A comprehensive characterisation and analysis of human breast cancers through whole-genome sequencing.
| EGAD00001001322 | EGA