Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA128069 | ENA |
REPOSITORIES: ENA
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Project description:Background: Many tools used to analyze microarrays in different conditions have been described. However, the integration of the deregulated genes within coherent metabolic pathways is lacking. Currently no objective selection criterion, based on biological functions exists, to determine a threshold demonstrating that a gene is indeed differentially expressed. Methodology/Principal Findings: To improve transcriptomic analysis of microarrays, we propose a new statistical approach, which takes into account biological parameters. We present an iterative method to optimise the selection of differentially expressed gene in two experimental conditions. The stringency level of gene selection was associated simultaneously with the p-value of expression variation and the occurrence rate parameter, which is associated with the percentage of donors whose transcriptomic profile is similar. Our method intertwines stringency level settings, biological data and a knowledge database to highlight molecular interactions using networks and pathways. Analysis performed during iterations helped us select the optimal threshold required for the most pertinent selection of differently expressed genes. Conclusions/significance: We have applied this approach to the well documented mechanism of human macrophage response to lipopolysaccharide stimulation. For example, we thus verified that our method was able to determine with the highest degree of accuracy the best threshold for selecting genes, which are truly differentially expressed. Macrophages isolated from six heathy donnor was/or not stimulated. Paired data, i.e. LPS stimulated macrophages versus unstimulated macrophages from the same donor have been compared (eg, Donor1_LPS vs Donor1_NT; see processed data file linked below). The six comparaisons have been globaly analyse using two parameters, i.e. threshod and occurency, associated with a request of a database knowledge. Both parameters has been tune to define the best setting allowing to optimize the selection of differentially expressed genes
2011-06-19 | E-GEOD-22858 | biostudies-arrayexpress
Project description:Background: Many tools used to analyze microarrays in different conditions have been described. However, the integration of the deregulated genes within coherent metabolic pathways is lacking. Currently no objective selection criterion, based on biological functions exists, to determine a threshold demonstrating that a gene is indeed differentially expressed. Methodology/Principal Findings: To improve transcriptomic analysis of microarrays, we propose a new statistical approach, which takes into account biological parameters. We present an iterative method to optimise the selection of differentially expressed gene in two experimental conditions. The stringency level of gene selection was associated simultaneously with the p-value of expression variation and the occurrence rate parameter, which is associated with the percentage of donors whose transcriptomic profile is similar. Our method intertwines stringency level settings, biological data and a knowledge database to highlight molecular interactions using networks and pathways. Analysis performed during iterations helped us select the optimal threshold required for the most pertinent selection of differently expressed genes. Conclusions/significance: We have applied this approach to the well documented mechanism of human macrophage response to lipopolysaccharide stimulation. For example, we thus verified that our method was able to determine with the highest degree of accuracy the best threshold for selecting genes, which are truly differentially expressed.
2011-06-19 | GSE22858 | GEO
Project description:Purpose: The aim of this study is to analyse and compare the differentially expressed genes between nitric oxide treated and thalidomide treated chick embryos Methods: The trancriptome sequencing was performed using Illumina HiSeq 2500 ® platform. The sequence reads were aligned to the reference genome of chicken (Galgal4) downloaded from Ensembl Release 75 database. Alignment was performed using TopHat (v2.0.8) program to the Ensembl Release 75 gene model of chicken with default parameter settings. After alignment, Cuffdiff (v2.2.0) program was used for performing differential expression analysis. Pathway analysis of differentially expressed genes was performed using DAVID program. Heat maps were constructed using R package software 3.1.0.
2017-01-01 | GSE69159 | GEO
Project description:Differentially expressed genes upon TbSAC3 depletion
| PRJNA316977 | ENA
Project description:Differentially expressed genes in c2c12 myoblasts
| PRJNA358619 | ENA
Project description:Differentially expressed genes following ARID1A depletion
| PRJNA477786 | ENA
Project description:Genes differentially expressed upon CHD8 knockdown
| PRJNA106441 | ENA
Project description:Differentially expressed genes during disuse atrophy.
| PRJNA174343 | ENA
Project description:Five distinct biological processes and 14 differentially expressed genes characterize TEL/AML1-positive leukemia
| PRJNA102731 | ENA
Project description:Here we used RNA-Seq to unravel the gene expression patterns and related signaling pathways that might be responsible for the observed changes in the lipidome upon GDF11 treatment of hepatocellular carcinoma cells (HCC), HepG2. RNA-seq analysis was performed after 24h of GDF11 (100ng/ml) treatment to investigate its involvement in lipid metabolism. Genes exhibiting absolute fold-change values >2 and p-values <0.05 were considered differentially expressed between contrasts and statistical differences in gene expression were assessed by the ANOVA test. The significance threshold was set to 0.05. Treatment with recombinant GDF11 had an extensive effect on the overall gene expression profile in HepG2 cells and heatmap analysis clearly segregated control and GDF11 treated samples. In total, we identified 3,357 differentially expressed genes, of which 2,422 were over-expressed, and 935 were downregulated. To gain more deep mechanistic insight into the biological processes and pathway associations with these differentially expressed genes, we analyzed our transcriptomic data by STRING pathway unbiased analysis for annotated molecular interactions of selected genes employing Kegg pathways database. The 5 top most significantly influenced canonical pathways/cellular processes were the ones related to TGF-β signaling, extracellular matrix remodeling, focal adhesion, PI3K-AKT signaling, and cytochrome P450-dependent metabolism.
2021-01-31 | GSE165842 | GEO