Global transcriptional response to transient cell wall damage
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ABSTRACT:
ORGANISM(S): Saccharomyces cerevisiae
PROVIDER: GSE959 | GEO | 2004/02/16
SECONDARY ACCESSION(S): PRJNA87999
REPOSITORIES: GEO
Similar Datasets
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: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
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 following subset Series: GSE960: wild type 0 hours exposure to congo red GSE961: wild type 2 hours exposure to congo red GSE962: wild type 4 hours exposure to congo red GSE963: wild type 6 hours exposure to congo red GSE964: slt2 mutant 4 hours exposure to congo red GSE965: rlm1 mutant 4 hours exposure to congo red GSE966: wild type two hours exposure to zymolyase Keywords: SuperSeries Refer to individual Series
2010-06-09 | E-GEOD-959 | biostudies-arrayexpress
Project description:124 gastric biopsies comprising of Normals, Intestinal Metaplasia, Chronic Gastritis and Carcinomas are profiled. The ratio metric is given by (Biological sample / Universal Reference). The Biological Samples are labeled with Cy5 (Green) and the Pooled Normal Biopsies RNA is always labeled with Cy3 (Red). The arrays were scanned using a ScanArray 5000 scanner (Perkin-Elmer) and data extraction was done using Quantarray (GSI Lumonics). Subsequently, the data was imported into GeneSpring (Silicon Genetics) and intensity dependent LOWESS normalization was performed. The 7383 genes were filtered using an intensity in the reference channel (Cy3) of 300. This corresponded to 2 standard deviations above the mean for the background signal. Background singal was calculated using the empty wells/spots on the array and the average of 4 different positions on the slide were used. Keywords: other
2005-07-25 | GSE2669 | GEO
Project description:124 gastric biopsies comprising of Normals, Intestinal Metaplasia, Chronic Gastritis and Carcinomas are profiled. The ratio metric is given by (Biological sample / Universal Reference). The Biological Samples are labeled with Cy5 (Green) and the Pooled Normal Biopsies RNA is always labeled with Cy3 (Red). The arrays were scanned using a ScanArray 5000 scanner (Perkin-Elmer) and data extraction was done using Quantarray (GSI Lumonics). Subsequently, the data was imported into GeneSpring (Silicon Genetics) and intensity dependent LOWESS normalization was performed. The 7383 genes were filtered using an intensity in the reference channel (Cy3) of 300. This corresponded to 2 standard deviations above the mean for the background signal. Background singal was calculated using the empty wells/spots on the array and the average of 4 different positions on the slide were used.
2010-06-10 | E-GEOD-2669 | biostudies-arrayexpress
Project description:Exon tiling array encompassing 837,251 probes across the mouse genome. 12 tissue pools. Composition of the 12 mRNA pools analyzed (mRNA per array hybridization): 1- Heart (2 microgram), Skeletal muscle (2 microgram) 2- Liver (2 microgram) 3- Whole brain (1.5 microgram), Cerebellum (0.48 microgram), Olfactory bulb (0.15 microgram) 4- Colon (0.96 microgram), Intestine (1.04 microgram) 5- Testis (3 microgram), Epididymis (0.4 microgram) 6- Femur (0.9 microgram), Knee (0.4 microgram), Calvaria (0.06 microgram), Teeth+mandible (1.3 microgram), Teeth (0.4 microgram) 7- 15 day Embryo (1.3 microgram), 12.5 day Embryo (12.5 microgram), 9.5 day Embryo (0.3 microgram), 14.5 day Embryo head (0.25 microgram), ES cells (0.24 microgram) 8- Digit (1.3 microgram), Tongue (0.6 microgram), Trachea (0.15 microgram) 9- Pancreas (1 microgram), Mammary gland (0.9 microgram), Adrenal gland (0.25 microgram), Prostate gland (0.25 microgram) 10- Salivary gland (1.26 microgram), Lymph node (0.74 microgram) 11- 12.5 day Placenta (1.15 microgram), 9.5 day Placenta (0.5 microgram), 15 day Placenta (0.35 microgram) 12- Lung (1 microgram), Kidney (1 microgram), Adipose (1 microgram), Bladder (0.05 microgram) Labeling and hybridization: mRNA pools were reverse-transcribed with random nonamer primers (1 microgram/reaction) and T18VN (0.25 microgram/reaction) to synthesize cDNA. The reaction contained a 1:1 mixture of 5-(3-aminoallyl) thymidine 5'-triphosphate (Sigma, St. Louis, MO) and thymidine triphosphate (TTP) in place of TTP. cDNA products were bound to QIAquick PCR Purification columns (Qiagen, Germany) following the manufacturer's instructions, washed three times with 80% ethanol, and eluted with water. Purified cDNA was reacted with N-hydroxy succinimide esters of Cy3 or Cy5 (Amersham Pharmacia Biotech, Piscataway, NJ) following the manufacturer's instructions. Hydroxylamine-quenched Cy-labeled cDNAs were separated from free dye molecules using QIAquick columns. Mixed labeled cDNAs were added to hybridization buffer containing 1 M NaCl, 0.5% sodium sarcosine, 50 mM methyl ethane sulfonate (MES), pH 6.5, 33% formamide and 40 µg herring sperm DNA (Invitrogen, Carlsbad, California). Hybridizations were carried out in a final volume of 0.5 ml injecting into an Agilent hybridization chamber at 42°C on a rotating platform in a hybridization oven (Robbins Scientific Corporation, Sunnyvale, California) for 16-24 h. Slides were then washed (rocking ~30 seconds in 6x SSPE, 0.005% sarcosine, then rocking ~30 seconds in 0.06x SSPE) and scanned with a 4000A microarray scanner (Axon Instruments, Union City, California). Each array was hybridized with two samples simultaneously, each from a different pool. Image processing and data normalization: TIFF images were quantitated with GenePix (Axon Instruments). Individual channels were spatially detrended (i.e overall correlations were removed between spot intensity and position on the slide) by subtracting from each spot's log intensity a weighted average of the log intensities of nearby spots. Most weights were a product of two Gaussian functions, one of the difference in rows between the spots and one of the difference in columns, however 10% of the spots ("high expressors") were always assigned a weight of zero. The widths of the row and column Gaussians were chosen to minimize the sum, across all spots, of the squared difference between the weighted average and the actual log intensity of the spots. The "high expressors" spots were those with the largest difference between their log intensity and the median log intensity over a 7x7 window of neighboring spots. After spatial detrending, we transformed the log intensities back into linear intensities and all single-channels were normalized to each other (in the linear domain), using channel-specific affine transforms. That is, for each single channel, we normalized all the detrending intensities by adding an offset parameter (which was possibly negative) and then multiplying by a positive scale parameter. The scale and offset parameters of each channel's transform were set so that the median intensities and the difference between the 75th and 25th percentile intensities were identical across channels.
2010-07-01 | E-GEOD-3047 | biostudies-arrayexpress
Project description:We have completed the Human lncRNA microarray analysis of the 4 samples that you submitted. Total RNA from each sample was quantified using the Nanodrop 1000 and the RNA integrity was assessed by Agilent 2100 Bioanalyzer. About 5 μg total RNA of each sample was used for labeling and array hybridization as the following steps: 1) Reverse transcription with invitrogen Superscript ds-cDNA synthesis kit; 2) ds-cDNA labeling with Nimblegen one-color DNA labeling kit; 3) Array hybridization using the NimbleGen Hybridization System and followed by washing with the Nimblegen wash buffer kit. 4) Array scanning using the Axon GenePix 4000B microarray scanner (Molecular Devices Corporation). Scanned images (TIFF format) were then imported into NimbleScan software (version 2.5) for grid alignment and expression data analysis. Expression data were normalized through quantile normalization and the Robust Multichip Average (RMA) algorithm included in the NimbleScan software. The Probe level (*_norm_RMA.pair) files and mRNA level (*_RMA.calls) files were generated after normalization. The 4 mRNA level files were imported into Agilent GeneSpring Software (version 11.0) for further analysis. lncRNAs and mRNAs that at least 2 out of 4 samples have values greater than or equal to lower cut-off: 50.0 (“All Targets Value”) were chosen for data analysis. Differentially expressed lncRNAs and mRNAs were identified through Fold Change filtering. Pathway Analysis and GO analysis were applied to determine the roles of these differentially expressed mRNAs played in these biological pathways or GO terms. Finally, Hierarchical Clustering was performed to show distinguishable lncRNA and mRNA expression profiling among samples. Array Information: Human 4x44K lncRNA expression array information. Data Analysis for lncRNAs. Data Analysis for lncRNAs. Data Analysis for mRNAs. 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in RMA method by NimbleScan v2.5, and low intensity mRNAs were filtered. (mRNAs that at least 2 out of 4 samples have values greater than or equal to lower cut-off: 50.0 were chosen for further analysis) 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering. 3. Differentially expressed mRNAs screening: Contains significant differentially expressed mRNAs that passed Fold Change filtering (Fold Change >= 2.0). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of the mRNAs after filtering. 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs. 1. Raw lncRNA data normalization and low intensity filtering: Raw signal intensities were normalized in RMA method by NimbleScan v2.5, and low intensity lncRNAs were filtered. (lncRNAs that at least 2 out of 4 samples have values greater than or equal to lower cut-off: 50.0 were chosen for further analysis). 2. Quality assessment of lncRNA data after filtering: Contains Box Plot and Scatter Plot for lncRNAs after filtering. 3. Differentially expressed lncRNAs screening: Contains significant differentially expressed lncRNAs that passed Fold Change filtering (Fold Change >= 2.0). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of the lncRNAs after filtering. Data Analysis for mRNAs 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in RMA method by NimbleScan v2.5, and low intensity mRNAs were filtered. (mRNAs that at least 2 out of 4 samples have values greater than or equal to lower cut-off: 50.0 were chosen for further analysis) 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering. 3. Differentially expressed mRNAs screening: Contains significant differentially expressed mRNAs that passed Fold Change filtering (Fold Change >= 2.0). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of the mRNAs after filtering. 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs. 1. Raw lncRNA data normalization and low intensity filtering: Raw signal intensities were normalized in RMA method by NimbleScan v2.5, and low intensity lncRNAs were filtered. (lncRNAs that at least 2 out of 4 samples have values greater than or equal to lower cut-off: 50.0 were chosen for further analysis). 2. Quality assessment of lncRNA data after filtering: Contains Box Plot and Scatter Plot for lncRNAs after filtering. 3. Differentially expressed lncRNAs screening: Contains significant differentially expressed lncRNAs that passed Fold Change filtering (Fold Change >= 2.0). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of the lncRNAs after filtering. Data Analysis for mRNAs 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in RMA method by NimbleScan v2.5, and low intensity mRNAs were filtered. (mRNAs that at least 2 out of 4 samples have values greater than or equal to lower cut-off: 50.0 were chosen for further analysis) 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering. 3. Differentially expressed mRNAs screening: Contains significant differentially expressed mRNAs that passed Fold Change filtering (Fold Change >= 2.0). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of the mRNAs after filtering. 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs.
2024-11-27 | GSE282877 | GEO
Project description:Transcriptional profiling of murine erythroleukemia cells induced to differentiate Murine erythroleukemia (MEL) cells are derived from mice infected with the Friend erythroleukemia viral complex, which causes a lethal expansion of erythroid cells. The transformed, immortalized cells (MEL cells) isolated from infected mice are committed to erythroid differentiation, but are blocked roughly at the proerythoblast stage. Treatment with small, oxidized organic compounds like dimethyl sulfoxide or hydroxymethyl-bis-acetamide (HMBA) induce the cells to mature further, to roughly the erythroblast stage or beyond in some lines (Friend et al. 1971). During this induction, the amount of hemoglobin, some heme biosynthetic enzymes and other proteins characteristic of mature erythroid cells increases, largely as a result of changes in transcription (Aviv et al. 1976). A full description of changes in transcription of all mouse genes during this process is not available. To improve this situation, we have conducted transcriptional profiling of the RL5 line of MEL cells, using microarrays containing almost 7000 mouse genes. The RL5 line has a "random locus" containing a positive-negative selectable marker (HyTK) flanked by loxP sites, thus facilitating site-directed integration into the cells (Bouhassira et al. 1997; Feng et al. 1999; Molete et al. 2001). This particular line is not highly inducible, with less than half the cells accumulating large amounts of hemoglobin. However, they are advantageous for integration of expression constructs, which is our particular interest. MEL_RL5 cells were treated with 4 millimolar HMBA for 6 days to induce maturation, and RNA was isolated each day. Complementary DNA was synthesized and labeled with either Cy5 (red fluorescence) for the induced samples or Cy3 (green fluorescence) the untreated cells grown in parallel. For most time points, at least two independent experiments were run, some with dyes switched (SD). The microarrays were spotted at the PSU Microarray Facility. Hybridization was carried out in our laboratory, and hybridized chips were scanned on a GenePix scanner and quantified using GenePix software. The signals from each channel (red and green) were normalized so that the total red intensity equals the total green intensity. Data were filtered to remove "bad" spots, which are those in which the noise exceeded the signal. We calculated the median of the pixel intensities for each spot and standard deviation around the median, and with these values we computed a "modified Z-score" for each channel on each spot. A lenient threshold for the "modified Z-score" was applied to remove "bad" spots. After filtering, we performed global mean normalization for each chip, followed by lowess normalization for each chip to remove intensity-dependent effects. Keywords: time-course
2005-02-01 | GSE2217 | GEO
Project description:Aiming at defining the protein content and composition of a single mitochondrion of Arabidopsis thaliana, shotgun analyses were performed on purified mitochondria from cultured heterotrophic Arabidopsis cells. Based on microscopic observations on the size of mitochondria, as well as biochemical properties, such as protein concentration, average molecular mass of proteins, and the average length of the signal peptide, intensity-based absolute quantification (iBAQ) values were applied to calculate the copy number of each identified protein species within a single mitochondrion. Copy numbers of the individual proteins span five orders of magnitude, ranging from >40,000 for Voltage-Dependent Anion Channel 1 (VDAC1) to sub-stoichiometric copy numbers, i.e. less than a single copy per single mitochondrion, for several pentatricopeptide repeat (PPR) proteins that modify mitochondrial transcripts. Aiming at defining the protein content and composition of a single mitochondrion of Arabidopsis thaliana, shotgun analyses were performed on purified mitochondria from cultured heterotrophic Arabidopsis cells. Based on microscopic observations on the size of mitochondria, as well as biochemical properties, such as protein concentration, average molecular mass of proteins, and the average length of the signal peptide, intensity-based absolute quantification (iBAQ) values were applied to calculate the copy number of each identified protein species within a single mitochondrion. Copy numbers of the individual proteins span five orders of magnitude, ranging from >40,000 for Voltage-Dependent Anion Channel 1 (VDAC1) to sub-stoichiometric copy numbers, i.e. less than a single copy per single mitochondrion, for several pentatricopeptide repeat (PPR) proteins that modify mitochondrial transcripts. Aiming at defining the protein content and composition of a single mitochondrion of Arabidopsis thaliana, shotgun analyses were performed on purified mitochondria from cultured heterotrophic Arabidopsis cells. Based on microscopic observations on the size of mitochondria, as well as biochemical properties, such as protein concentration, average molecular mass of proteins, and the average length of the signal peptide, intensity-based absolute quantification (iBAQ) values were applied to calculate the copy number of each identified protein species within a single mitochondrion. Copy numbers of the individual proteins span five orders of magnitude, ranging from >40,000 for Voltage-Dependent Anion Channel 1 (VDAC1) to sub-stoichiometric copy numbers, i.e. less than a single copy per single mitochondrion, for several pentatricopeptide repeat (PPR) proteins that modify mitochondrial transcripts.
2019-09-11 | PXD014292 | Pride
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