Single-cell RNA-seq data from metastatic ovarian cancer for quality control study
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001005066 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:We performed a dye-swap microarray experiment using a total of 24 Rat 15k cDNA duplicates microarrays. The study included RNA from samples with high expected differential gene expression termed high contrasts compared to self-self hybridization (rat cell lines AR42J and NRK52E). We than optimized a pipeline to maximize the number of genes found differentially expressed between the two different RNA samples while at the same time making sure that the methodology finds no differentially expressed genes in selfself experiments with the same cell lines. In this high-contrast vs. self-self method (HCSSM) significantly expressed genes is determined by estimating the false discovery rate (FDR) using a null distribution obtained from self-self experiment. The optimization criterion requires only 4 microarrays per evaluation, and the effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA dT blocker gave the highest number of differentially expressed genes. When the criterion was used to evaluate steps in the computational analysis of microarray data we found that no background correction and weight based filtering gave the largest number of differentially expressed genes. Background correction method, however, has a greater influence on the number of differentially expressed genes found than filtering.
2007-01-19 | E-TABM-202 | biostudies-arrayexpress
Project description:Quality Protein Maize (QPM) was created by selecting for genetic modifiers that convert the starchy endosperm of an opaque2 (o2) mutant to a hard, vitreous phenotype. Genetic analysis has shown there are multiple, unlinked o2 modifiers (Opm), but their identity and mode of action are unknown. A microarray hybridization performed with RNA obtained from true breeding o2 progeny with vitreous and opaque kernel phenotypes identified a small group of differentially expressed genes, some of which map at or near the Opm QTLs. Keywords: Genetic modification
2008-02-08 | GSE10449 | GEO
Project description:<p><strong>INTRODUCTION:</strong> Isoprenoids are amongst the most abundant and diverse biological molecules and are involved in a broad range of biological functions. Functional understanding of their biosynthesis is thus key in many fundamental and applicative fields, including systems biology, medicine and biotechnology. However, available methods do not yet allow accurate quantification and tracing of stable isotopes incorporation for all the isoprenoids precursors.</p><p><strong>OBJECTIVES:</strong> We developed and validated a complete methodology for quantitative metabolomics and isotopologue profiling of isoprenoid precursors in the yeast Saccharomyces cerevisiae.</p><p><strong>METHODS:</strong> This workflow covers all the experimental and computational steps from sample collection and preparation to data acquisition and processing. It also includes a novel quantification method based on liquid chromatography coupled to high-resolution mass spectrometry. Method validation followed the Metabolomics Standards Initiative guidelines.</p><p><strong>RESULTS:</strong> This workflow ensures accurate absolute quantification (RSD < 20%) of all mevalonate and prenyl pyrophosphates intermediates with a high sensitivity over a large linear range (from 0.1 to 50 pmol). In addition, we demonstrate that this workflow brings crucial information to design more efficient phytoene producers. Results indicate stable turnover rates of prenyl pyrophosphate intermediates in the constructed strains and provide quantitative information on the change of the biosynthetic flux of phytoene precursors.</p><p><strong>CONCLUSION:</strong> This methodology fills one of the last technical gaps for functional studies of isoprenoids biosynthesis and should be applicable to other eukaryotic and prokaryotic (micro)organisms after adaptation of some organism-dependent steps. This methodology also opens the way to 13C-metabolic flux analysis of isoprenoid biosynthesis.</p>
2021-04-01 | MTBLS923 | MetaboLights
Project description:Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Illumina_HT12)
| PRJNA277480 | ENA
Project description:Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Affymetrix_HTA2.0)
| PRJNA277540 | ENA
Project description:Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Agilent_4x44K)
| PRJNA277482 | ENA
Project description:We have developed a robust methodology for the derivation of kidney organoids from human pluripotent stem cells further vascularized taking advantage of several in vivo approaches. Our methodology suffices for the generation of kidney derivatives transcriptomically comparable with 22 weeks of gestation kidney tissues and highlight the use of longer periods of exposure to 3D in order to promote renal differentiation in a time frame of 15 days. In order to ascertain the impact of extracellular matrix microenvironment in renal differentiation undifferentiated human pluripotent stem cells were further cultured in compliant substrates mirroring embryo-ECM microenvironment (1kPa) in order to promote renal differentiation and compared these conditions in front of rigid substrates (60 kPa) mimicking hard substrates normally used when differentiating human pluripotent stem cells
2018-12-20 | GSE108350 | GEO
Project description:Next generation sequencing platforms have become essential tools for understanding DNA in a wide range of contexts. Their success heavily relies on the accuracy, sensitivity and specificity of methods used to discern differences between the reference genome and genomes under investigation. Here we compare the relative performances of five popular single nucleotide variant callers with and without their associated recommended hard filtering criteria. We compare: FreeBayes; the Genome Analysis Toolkit’s Haplotype Caller and Unified Genotyper; SAMtools; and VarScan. We tailor this comparison to suit smaller projects with modest sample numbers (n = 10) and coverage (~10X) to fill a current gap in the literature. Other comparison studies are generally applicable only to larger projects in model species, where there is access to large amounts of sequencing data and curated callsets for base and variant quality score recalibration. We estimated the accuracy, sensitivity and specificity of each pipeline according to the genotype concordance rate and number with the “truth” dataset for 10 canine samples. The truth dataset was defined as genotypes obtained from the CanineHD BeadChip array. Whole genome sequencing data was performed on the Illumina HiSeq2000 or HiSeq2500 platform as 100-101 base pair, paired end reads to an average sample coverage of 10.3X. Apart from GATK Haplotype Caller, applying recommended hard filters did not improve the performance of genotyping concordance at the tested levels of minimum coverage. The default VarScan pipeline with no additional filters applied (VarScan uses SAMtools mpileup, without base alignment quality computation) generally outperformed other callers in terms of accuracy, sensitivity and specificity. The results of this study demonstrate that hard filtering of variant calls from low-powered genome studies can impair accuracy, sensitivity and specificity of callsets and provides some benchmark performance metrics on a range of low coverage levels.
2018-08-31 | GSE117010 | GEO