Umea Lucidea Experiment
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Pinus sylvestris
PROVIDER: GSE29400 | GEO | 2011/05/21
SECONDARY ACCESSION(S): PRJNA140173
REPOSITORIES: GEO
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Project description:The experiment was designed to enable validation of pre-processing and test algorithms. The in-house produced cDNA-array contains 44 clones: 19 clones from mice, 4 clones from Pine (involved in photosynthesis) and 21 artificial clones from the Lucidea Universal ScoreCard (Amersham Bioscienses), where each clone was printed 480 times in 48 identically designed sub-grids. The experiment contains eight arrays with identical experimental design. Total RNA from murine cell line was divided in two samples; the reference sample was labeled with the fluorophore Cy5 and spiked with the Lucidea Universal ScoreCard reference reaction, the test sample was labeled with Cy3 and spiked with the Lucidea Universal ScoreCard test reaction. The concentrations of the Lucidea reactions are known and consequently so are the true ratios between the reference and test channels. Approximately 40% of the artificial genes were differentially expressed. The particular design of the experiment makes the data suitable for validating algorithms for pre-processing and tests for identifying differentially expressed genes. - The 80.I.1 normalization algorithm : all spots flagged as not found during image analysis considered missing values (complete filtration). Print-tip MA-loess dye normalization based on the calibration clones was applied to the raw data and the B-statistic was calculated. - The 80.II.1 normalization algorithm : all spots flagged as not found during image analysis considered missing values (complete filtration). Local background correction was applied and all spots with negative values were excluded. Print-tip MA-loess dye normalization based on the calibration clones was applied to the background corrected data and the B-statistic was calculated. - The 80.II.64 normalization algorithm : all spots flagged as not found during image analysis considered missing values (complete filtration). Local background correction was applied, negative values were excluded and all spots with a value below 64 were set to 64 (censored). Print-tip MA-loess dye normalization based on the calibration clones was applied to the background corrected data and the B-statistic was calculated. - The 80.V.1 normalization algorithm : The intensities of all spots flagged not found were treated as missing values during normalization, but prior to calculating test-statistics the spot's log-ratios were set to zero. In the special case when all arrays generated not-found spots, the gene was removed from the experiment (Partial filtration). Local background correction was applied and all negative values were considered missing values. Print-tip MA-loess dye normalization based on the calibration clones was applied to the background corrected data and the B-statistic was calculated. The experiment contains eight arrays with identical experimental design. The reference sample was labeled with the fluorophore Cy5 and spiked with the Lucidea Universal ScoreCard reference reaction, the test sample was labeled with Cy3 and spiked with the Lucidea Universal ScoreCard test reaction.
2011-05-21 | E-GEOD-29400 | biostudies-arrayexpress
Project description:Data processing included: 1. Filtering of those bad quality image spots (these includes alterations on the shape or hybridization) 2. Filtering of low intensity which was done flagging with -50 those spots whose feature intensity was lower in any of both channels than the average of the local background in the corresponding channel for all spots. However, those genes whose feature intensity in one channel was under the limit but in the other channel was 5 times over limit were considered as on-off genes and were not filtered. 3. Filtering of low reproducibility intrachip replicated spots. Normal distribution was created with the value obtained from the formula: log2(Rax1/Rb) which means logarithm (two-based) of one ratio multiplied by the inverse of its replicate. This value for each gene shoud keep between the range of average ± 3SD. Those genes out of these range are flagged as -25 4. Normalization of ratios was done by Lowess mathematical method. Correction factor was 0.33 Keywords: other
2005-03-01 | GSE2105 | GEO
Project description:The local background was subtracted from the fluorescent value of each spot. Feature intensities were extracted from scanned microarray images using GenePix Pro 5.1. (Axon Instruments). The images were visually inspected, and spots from low-quality areas of the array were flagged and excluded from further analysis. Spots were also excluded from analysis if both the combined fluorescent intensity for both channels was less than 1.4 times that of the local background and the pixel-by-pixel correlation coefficient of the spot was less than 0.4. The fluorescence ratios were normalized as previously described (Turton and Gant oncogene 2001website). A hierarchical clustering algorithm (M. Eisen Brown and Botstein PNAS 98 website) was applied to those genes that fulfilled all of the following conditions: they were not flagged; they were differentially expressed (equal or higher than 1.5 fold upregulated or equal or lower than 2 fold downregulated); they had p-values equal or less than 0.02; and they were consistent on at least 4 out of the 5 arrays. Keywords: repeat sample
2004-12-21 | GSE2069 | GEO
Project description:Data processing included: 1. Filtering of those bad quality image spots (these includes alterations on the shape or hybridization) 2. Filtering of low intensity which was done flagging with -50 those spots whose feature intensity was lower in any of both channels than the average of the local background in the corresponding channel for all spots. However, those genes whose feature intensity in one channel was under the limit but in the other channel was 5 times over limit were considered as on-off genes and were not filtered. 3. Filtering of low reproducibility intrachip replicated spots. Normal distribution was created with the value obtained from the formula: log2(Rax1/Rb) which means logarithm (two-based) of one ratio multiplied by the inverse of its replicate. This value for each gene shoud keep between the range of average ± 3SD. Those genes out of these range are flagged as -25 4. Normalization of ratios was done by Lowess mathematical method. Correction factor was 0.33 This SuperSeries is composed of the SubSeries listed below.
2004-02-16 | GSE959 | GEO
Project description:We examined the antifungal activity of artemisinin against Aspergillus fumigatus (A. fumigatus), a pathogenic filamentous fungus responsible for allergic and invasive aspergillosis in humans and analyzed transcript profiles of the fungus on exposure to Artemisinin. A. fumigatus spores were cultured for 48 h and then treated with artemisinin (at MIC50 concentration) or solvent control (DMSO) for 3 h to study its transcriptomic profiles. Total RNA (7 M-BM-5g) from A. fumigatus treated with solvent control (DMSO) or artemisinin was reverse transcribed separately using fluorescein-labeled dCTP or biotin-labeled dCTP from Micromax TSA labeling kit (Cy3 or Cy5 dyes are differentially deposited to these labeled cDNAs, post-hybridization, using tyramide signal amplification (TSA) protocol). Labeled cDNAs from test and control sample were mixed in equal amount and hybridized to microarray slide(s). After hybridization, the slides were processed as per the protocol of the Micromax TSA labeling kit and scanned in both the Cy3 and the Cy5 channels with a model 4200 Axon Instruments scanner with a 10-M-BM-5m resolution. Each of the signals was converted into a resolution of 16 bits per pixel. A dye swap experiment with a biological replicate was performed to ensure the reproducibility of each gene expression pattern.TIFF images were analyzed using GenePix Pro 6.0 software. The signal intensity value of each spot was reduced by the local background level for each spot. Diagnosis and normalization of microarray data (DNMAD) program was used for print-tip loess normalization of microarray data and for merging the data from dye-swap experiments . M-values obtained from this program were converted to log ratio (test/reference) and fold modulation. Genes having less than 3 spots in 2 dye swap slides were discarded and only those having their all fold change values (from 3 or 4 replicates in 2 slides; as each target is spotted twice on the slide) within a coefficient of variation M-BM-1 0.5 were used for analysis. Gene expression ratios of M-bM-^IM-%2 (fold upregulation or downregulation) in both replicates (dye swap) were considered to be differentially expressed genes.
2011-05-11 | E-GEOD-21297 | biostudies-arrayexpress
Project description:To determine the transcriptional effects of a novel plant-based compound, dehydrobrachylaenolide, on P. falciparum, parasite cultures were treated with the compound over time. Samples were taken for analysis 2, 6, and 12 hours post-invasion of human red blood cells. Control cultures were treated simultaneously with DMSO, and samples isolated at 2, 6, and 12 hours for transcriptional analysis. Background Antimalarial drug resistance threatens to undermine efforts to eliminate this deadly disease. The resulting omnipresent requirement for drugs with novel modes of action prompted a national consortium initiative to discover new antiplasmodial agents from South African medicinal plants. One of the plants selected for investigation was Dicoma anomala subsp. gerrardii, based on its ethnomedicinal profile. Methods Standard phytochemical analysis techniques including solvent-solvent extraction, thin-layer and column chromatography, were used to isolate the main active constituent of Dicoma anomala subsp. gerrardii. The crystallised pure compound was identified using nuclear magnetic resonance spectroscopy, mass spectrometry and X-ray crystallography. The compound was tested in vitro on Plasmodium falciparum cultures using the parasite lactate dehydrogenase assay. The effects of treatment on the P. falciparum transcriptome were subsequently investigated by treating ring-stage parasites (alongside untreated controls) with the pure compound, followed by oligonucleotide microarray and data analysis. Results The main active constituent was identified as dehydrobrachylaenolide, a eudesmanolide-type sesquiterpene lactone. The compound demonstrated an in vitro IC50 of 245.6 nM, which was comparable to the IC50 of chloroquine, against a chloroquine-resistant strain (K1) of P. falciparum. Microarray data analysis identified a cluster of unique genes that were differentially expressed as a result of the treatment and gene ontology analysis identified various biological processes that were significantly affected. Comparison of the dehydrobrachylaenolide treatment transcriptional dataset with a published artesunate (also a sesquiterpene lactone) dataset revealed little overlap. This suggests differentiated modes of action between the two compounds. Conclusions Dehydrobrachylaenolide could play a valuable role as a drug candidate to generate new antimalarial compounds with novel modes of action and favourable ADMET properties. Reference design. Transcriptional analysis was performed as described in GSE18075 with the following modification. Profiles from parasite cultures isolated 2hrs after drug treatment during early ring-stage development were contrasted against untreated control cultures isolated at this timepoint. Profiles from parasites isolated 6 and 12 hours following drug treatment were contrasted to against untreated control cultures isolated at 6 hours. A detailed description of the statistical methodology used for this dataset is outlined in the accompanying manuscript. A reference design was employed for array hybridisation, utilising the URR pool described previously in the NCBI GEO Series GSE18075 dataset. All solvent-control and drug-treated samples were hybridised to Operon slides, along with the URR. In contrast to the hybridisation protocol described in GSE18075, 40 pmoles of each dye was hybridised to each array, utilising Cy3 (sample) and Cy5 (reference) dyes from GE Healthcare (#RPN5661), specifically optimised for nucleic acid labelling. A total of nineteen slides were processed in the study. Two independent cDNA samples (biological replicates) were prepared for each untreated and drug-treated sample at each time point. One of the biological replicate cDNA samples were additionally hybridised to a third slide (representing the technical replicate). In the case of the 2 hour DMSO treated control culture, an additional technical microarray replicate was included for quality control purposes. GenePix results (gpr) files were generated using GenePix 6.0 (Molecular Devices) software, without normalization. For clustering analyses, results files were normalized with DNMAD (Diagnosis and Normalization for MicroArray Data) using print-tip loess. The normalized values were subsequently downloaded and analyzed with the Multiexperiment Viewer (MeV) in the TM4 software suite. Hierarchical Clustering (HCL, average linkage) was performed to estimate technical and biological variation between samples and at which point cytostasis most likely occurred for comparative purposes in downstream analyses. Intensity data for individual slides were imported into LIMMA (linear models for microarray data) in the R computing environment. Pre- and post-normalization diagnostic plots were performed using MARRAY. Data from each microarray slide was normalized using print-tip loess. Data between microarrays was normalized using R-Quantile normalisation. Pearson correlations were computed in MS Excel to estimate variation between technical and biological replicates. Spots excluded from slide correlations and normalisation were those weighted by the limma script or flagged in the genepix results file (gpr). Additionally, spots termed Alien, Empty, Null and Operon Use Only were excluded from the correlation analyses. These spots were similarly excluded for correlations between untreated and treated samples at each time point following normalisation. Results from biological and slide replicates within each of the time points were collated, and linear models were computed to contrast gene expression between time points. A two-fold change in gene expression was used as cut-off, in conjunction with correction for false discovery (false discovery rate (FDR) = 5%). Analysis of differentially expressed genes was performed in MADIBA (Micro Array Data Interface for Biological Annotation).
2011-11-01 | E-GEOD-29874 | biostudies-arrayexpress
Project description:Transcriptional profiling of P. falciparum cultures treated with cyclohexylamine over time (18, 25 and 30 hours post invasion) A control experiment was also set up in which P. falciparum was not treated with cyclohexylamine, and samples were taken at 18, 25 and 30 h post invasion). Background Plasmodium falciparum, the causative agent of severe human malaria, has evolved to become resistant to previously successful antimalarial chemotherapies, most notably chloroquine and the antifolates. The prevalence of resistant strains has necessitated the discovery and development of new chemical entities with novel modes-of-action. Although much effort has been invested in the creation of analogues based on existing drugs and the screening of chemical and natural compound libraries, a crucial shortcoming in current Plasmodial drug discovery efforts remains the lack of an extensive set of novel, validated drug targets. A requirement of these targets (or the pathways in which they function) is that they prove essential for parasite survival. The polyamine biosynthetic pathway, responsible for the metabolism of highly abundant amines crucial for parasite growth, proliferation and differentiation, is currently under investigation as an antimalarial target. Chemotherapeutic strategies targeting this pathway have been successfully utilized for the treatment of Trypanosomes causing West African sleeping sickness. In order to further evaluate polyamine depletion as possible antimalarial intervention, the consequences of inhibiting P. falciparum spermidine synthase (PfSpdSyn) were examined on a morphological, transcriptomic, proteomic and metabolic level. Results Morphological analysis of P. falciparum 3D7 following application of the PfSpdSyn inhibitor cyclohexylamine confirmed that parasite development was completely arrested at the early trophozoite stage. This is in contrast to untreated parasites which progressed to late trophozoites at comparable time points. Global gene expression analyses confirmed a transcriptional arrest in the parasite. Several of the differentially expressed genes mapped to the polyamine biosynthetic and associated metabolic pathways. Differential expression of corresponding parasite proteins involved in polyamine biosynthesis was also observed. Most notably, uridine phosphorylase, adenosine deaminase, lysine decarboxylase (LDC) and S-adenosylmethionine synthetase were differentially expressed at the transcript and/or protein level. Several genes in associated metabolic pathways (purine metabolism and various methyltransferases) were also affected. The specific nature of the perturbation was additionally reflected by changes in polyamine metabolite levels. Conclusions This study details the malaria parasite’s response to PfSpdSyn inhibition on the transcriptomic, proteomic and metabolic levels. The results corroborate and significantly expand previous functional genomics studies relating to polyamine depletion in this parasite. Moreover, they confirm the role of transcriptional regulation in P. falciparum, particularly in this pathway. The findings promote this essential pathway as a target for antimalarial chemotherapeutic intervention strategies. Keywords: Time course experiment in response to a drug treatment Reference design. All timepoints compared with t = 18 hours (untreated) post invasion. Two biological replicates and one technical sample per treatment and per time point. A reference design was employed for array hybridisation, utilising the URR pool described previously. All solvent-control and drug-treated sampled were hybridised to Operon slides, along with the URR. For each time point and each untreated/treated sample, three microarray slides were processed, such that a total of eighteen slides were processed in the study. Two independent cDNA samples (biological replicates) were prepared for each untreated and drug-treated sample at each time point. One of the biological replicate cDNA samples were additionally hybridised to a third slide (representing the technical replicate). GenePix results (gpr) files were generated using GenePix 6.0 (Molecular Devices) software, without normalization. For clustering analyses, results files were normalized with DNMAD (Diagnosis and Normalization for MicroArray Data) using print-tip loess. The normalized values were subsequently downloaded and analyzed with the Multiexperiment Viewer (MeV) in the TM4 software suite. Hierarchical Clustering (HCL, average linkage) was performed to estimate technical and biological variation between samples and at which point cytostasis most likely occurred for comparative purposes in downstream analyses. Intensity data for individual slides were imported into LIMMA (linear models for microarray data) in the R computing environment. Pre- and post-normalization diagnostic plots were performed using MARRAY. Data from each microarray slide was normalized using print-tip loess. Data between microarrays was normalized using rquantile normalisation. Pearson correlations were computed in ExCel to estimate variation between technical and biological replicates. Spots excluded from slide correlations and normalisation were those weighted by the limma script or flagged in the genepix results file (gpr). Additionally, spots termed Alien, Empty, Null and Operon Use Only were excluded from the correlation analyses. These spots were similarly excluded for correlations between untreated and treated samples at each time point following normalisation. Results from biological and slide replicates within each of the time points were collated, and linear models were computed to contrast gene expression between time points. A two-fold change in gene expression was used as cut-off, in conjunction with correction for false discovery (false discovery rate (FDR) = 5%). Normalised data was deposited in the Gene Expression Omnibus (GEO) database, number GSE18075. Analysis of differentially expressed genes was performed in MADIBA (Micro Array Data Interface for Biological Annotation).
2010-04-19 | E-GEOD-18075 | biostudies-arrayexpress
Project description:The ubiquitome dataset by imputing missing values and normalization of 6844 ubiquitin modified peptides, 7026 lysine ubiquitination (Kub) site were defined in 2720 proteins, of which 3718 Kub site in 1379 proteins were quantified. Among these quantified Kub sites and proteins, 139 sites in 100 proteins were identified as upregulated ubiquitination sites, and 55 sites in 48 proteins were identified as downregulated ubiquitination sites at a threshold of 1.5 (P < 0.05)
2023-03-11 | PXD036672 | Pride
Project description:RNA from 11 individual mouse cell lines were reverse-transcribed to cDNA, labeled with Cy5 and cohybridized with Cy3-labeled UMRR onto 7,500-spot mouse oligo microarrays (UNC). The data was analyzed using GeneTraffic software. 300-1000 spots out of 8,000 were flagged on each microarray and excluded from further analysis. Spots with hybridization signals in Cy5 channel higher than 1000 and with Cy5/Cy3 ratio greater than 2 were collected and the number of spots with these characteristics on only one microarray was determined. A reference experiment design type is where all samples are compared to a common reference. Keywords: reference_design
2006-01-05 | GSE3974 | GEO
Project description:Data processing included: 1. Filtering of those bad quality image spots (these includes alterations on the shape or hybridization) 2. Filtering of low intensity which was done flagging with -50 those spots whose feature intensity was lower in any of both channels than the average of the local background in the corresponding channel for all spots. However, those genes whose feature intensity in one channel was under the limit but in the other channel was 5 times over limit were considered as on-off genes and were not filtered. 3. Filtering of low reproducibility intrachip replicated spots. Normal distribution was created with the value obtained from the formula: log2(Rax1/Rb) which means logarithm (two-based) of one ratio multiplied by the inverse of its replicate. This value for each gene shoud keep between the range of average ± 3SD. Those genes out of these range are flagged as -25 4. Normalization of ratios was done by Lowess mathematical method. Correction factor was 0.33
2010-06-10 | E-GEOD-2105 | biostudies-arrayexpress