Performance comparison of Affymetrix and Illumina microarray technologies_IlluminaDataSet
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE10213 | GEO | 2008/06/27
SECONDARY ACCESSION(S): PRJNA109007
REPOSITORIES: GEO
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Project description:The present study was conducted to compare the ability of Affymetrix and Illumina microarray technologies to characterize the differential gene expression profiles of human monocytes and monocyte-derived-macrophages. Keywords: Type Cross-platform comparison Summary
2008-06-27 | GSE11430 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2008-06-27 | GSE11540 | GEO
Project description:Here we compared the performance of Affymetrix HTA 2.0 microarray and Illumina 2000 RNA-sequencing techniques on the clinical samples collected from patients with lung squamous cell carcinoma.
2017-06-09 | GSE84784 | GEO
Project description:Cross-presentation of cell-associated antigens is carried out by classical DCs (cDCs) and monocyte-derived DCs (Mo-DCs), but whether a similar or distinct program exists for this process is unknown. In examining this issue, we discovered that only Ly-6ChiTremL4– monocytes, but not Ly-6ChiTremL4+ monocytes, can differentiate into Zbtb46+ Mo-DCs in response to GM-CSF and IL-4. However, Ly-6ChiTremL4+ monocytes were committed to Nur77-dependent development of Ly-6CloTremL4+ monocytes. Further, differentiation of monocytes with GM-CSF required addition of IL-4 to generate Zbtb46+ Mo-DCs that cross-presented as efficiently as CD24+ cDCs, which was accompanied by increased Batf3 and Irf4 expression. Unlike cDCs, Mo-DCs required only IRF4, and not Batf3, for cross-presentation. Further, Irf4–/– monocytes failed to develop into Zbtb46+ Mo-DCs, and instead developed into macrophages. Thus, cDCs and Mo-DCs use distinct transcriptional programs for cross-presentation that may drive different antigen-processing pathways. These differences may influence development of therapeutic DC vaccines based on Mo-DCs.
2016-05-25 | GSE75013 | GEO
Project description:BackgroundSystematic processing noise, which includes batch effects, is very common in microarray experiments but is often ignored despite its potential to confound or compromise experimental results. Compromised results are most likely when re-analysing or integrating datasets from public repositories due to the different conditions under which each dataset is generated. To better understand the relative noise-contributions of various factors in experimental-design, we assessed several Illumina and Affymetrix datasets for technical variation between replicate hybridisations of Universal Human Reference (UHRR) and individual or pooled breast-tumour RNA.ResultsA varying degree of systematic noise was observed in each of the datasets, however in all cases the relative amount of variation between standard control RNA replicates was found to be greatest at earlier points in the sample-preparation workflow. For example, 40.6% of the total variation in reported expressions were attributed to replicate extractions, compared to 13.9% due to amplification/labelling and 10.8% between replicate hybridisations. Deliberate probe-wise batch-correction methods were effective in reducing the magnitude of this variation, although the level of improvement was dependent on the sources of noise included in the model. Systematic noise introduced at the chip, run, and experiment levels of a combined Illumina dataset were found to be highly dependent upon the experimental design. Both UHRR and pools of RNA, which were derived from the samples of interest, modelled technical variation well although the pools were significantly better correlated (4% average improvement) and better emulated the effects of systematic noise, over all probes, than the UHRRs. The effect of this noise was not uniform over all probes, with low GC-content probes found to be more vulnerable to batch variation than probes with a higher GC-content.ConclusionsThe magnitude of systematic processing noise in a microarray experiment is variable across probes and experiments, however it is generally the case that procedures earlier in the sample-preparation workflow are liable to introduce the most noise. Careful experimental design is important to protect against noise, detailed meta-data should always be provided, and diagnostic procedures should be routinely performed prior to downstream analyses for the detection of bias in microarray studies.
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Project description:Cross-presentation of cell-associated antigens is carried out by classical DCs (cDCs) and monocyte-derived DCs (Mo-DCs), but whether a similar or distinct program exists for this process is unknown. In examining this issue, we discovered that only Ly-6ChiTremL4– monocytes, but not Ly-6ChiTremL4+ monocytes, can differentiate into Zbtb46+ Mo-DCs in response to GM-CSF and IL-4. However, Ly-6ChiTremL4+ monocytes were committed to Nur77-dependent development of Ly-6CloTremL4+ monocytes. Further, differentiation of monocytes with GM-CSF required addition of IL-4 to generate Zbtb46+ Mo-DCs that cross-presented as efficiently as CD24+ cDCs, which was accompanied by increased Batf3 and Irf4 expression. Unlike cDCs, Mo-DCs required only IRF4, and not Batf3, for cross-presentation. Further, Irf4–/– monocytes failed to develop into Zbtb46+ Mo-DCs, and instead developed into macrophages. Thus, cDCs and Mo-DCs use distinct transcriptional programs for cross-presentation that may drive different antigen-processing pathways. These differences may influence development of therapeutic DC vaccines based on Mo-DCs.
2016-05-25 | GSE75012 | GEO
Project description:Cross-presentation of cell-associated antigens is carried out by classical DCs (cDCs) and monocyte-derived DCs (Mo-DCs), but whether a similar or distinct program exists for this process is unknown. In examining this issue, we discovered that only Ly-6ChiTremL4– monocytes, but not Ly-6ChiTremL4+ monocytes, can differentiate into Zbtb46+ Mo-DCs in response to GM-CSF and IL-4. However, Ly-6ChiTremL4+ monocytes were committed to Nur77-dependent development of Ly-6CloTremL4+ monocytes. Further, differentiation of monocytes with GM-CSF required addition of IL-4 to generate Zbtb46+ Mo-DCs that cross-presented as efficiently as CD24+ cDCs, which was accompanied by increased Batf3 and Irf4 expression. Unlike cDCs, Mo-DCs required only IRF4, and not Batf3, for cross-presentation. Further, Irf4–/– monocytes failed to develop into Zbtb46+ Mo-DCs, and instead developed into macrophages. Thus, cDCs and Mo-DCs use distinct transcriptional programs for cross-presentation that may drive different antigen-processing pathways. These differences may influence development of therapeutic DC vaccines based on Mo-DCs.
2016-05-25 | GSE75014 | GEO
Project description:Here we compared the performance of Affymetrix HTA 2.0 microarray and Illumina 2000 RNA-sequencing techniques on the clinical samples collected from patients with lung squamous cell carcinoma.
2017-06-09 | GSE84776 | GEO
Project description:The growth in popularity of RNA expression microarrays has been accompanied by concerns about the reliability of the data especially when comparing between different platforms. Here we present an evaluation of the reproducibility of microarray results using two platforms, Affymetrix GeneChips and Illumina BeadArrays. The study design is based on a dilution series of two human tissues (blood and placenta), tested in duplicate on each platform. By a variety of measures the two platforms yielded data of similar quality and properties. The results of a comparison between the platforms indicate very high agreement, particularly for genes which are predicted to be differentially expressed between the two tissues. Agreement was strongly correlated with the level of expression of a gene. Concordance was also improved when probes on the two platforms could be identified as being likely to target the same set of transcripts of a given gene. These results shed light on the causes or failures of agreement across microarray platforms. The set of probes we found to be most highly reproducible can be used by others to help increase confidence in analyses of other data sets using these platforms. Keywords: Dilution series, platform comparison, Affymetrix, Illumina
2005-11-08 | GSE3077 | GEO
Project description:BackgroundAs the use of microarray technology becomes more prevalent it is not unusual to find several laboratories employing the same microarray technology to identify genes related to the same condition in the same species. Although the experimental specifics are similar, typically a different list of statistically significant genes result from each data analysis.ResultsWe propose a statistically-based meta-analytic approach to microarray analysis for the purpose of systematically combining results from the different laboratories. This approach provides a more precise view of genes that are significantly related to the condition of interest while simultaneously allowing for differences between laboratories. Of particular interest is the widely used Affymetrix oligonucleotide array, the results of which are naturally suited to a meta-analysis. A simulation model based on the Affymetrix platform is developed to examine the adaptive nature of the meta-analytic approach and to illustrate the usefulness of such an approach in combining microarray results across laboratories. The approach is then applied to real data involving a mouse model for multiple sclerosis.ConclusionThe quantitative estimates from the meta-analysis model tend to be closer to the "true" degree of differential expression than any single lab. Meta-analytic methods can systematically combine Affymetrix results from different laboratories to gain a clearer understanding of genes' relationships to specific conditions of interest.
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