Unknown,Transcriptomics,Genomics,Proteomics

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The gene expression profiling array of mRNAs between portal vein tumor thrombus tissues and paired tumor tissues in hapatocellular carcinoma.

ABSTRACT: Investigation of whole genome gene expression level changes of mRNAs in portal vein tumor thrombus tissues and paired tumor tissues in hapatocellular carcinoma. The different expression genes were further analyzed. The human mRNA microarray analysis of the 6 samples (3 portal vein tumor thrombus tissues and 3 paired tumor tissues) were completed. Total RNA from each sample was quantified using the NanoDrop ND-1000 and RNA integrity was assessed using standard denaturing agarose gel electrophoresis. Total RNA of each sample was used for labeling and array hybridization as the following steps: 1) Reverse transcription with by 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 Agilent Scanner G2505C. 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. All mRNAs level files were imported into Agilent GeneSpring GX software (version 11.5.1) for further analysis.mRNAs that at least 3 out of 6 samples have values greater than or equal to lower cut-off: 50.0 (“All Targets Value”) were chosen for further data analysis. Differentially expressed mRNAs were identified through Volcano Plot 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 the distinguishable mRNAs expression pattern among samples. .

ORGANISM(S): Homo sapiens

SUBMITTER: WEIXING GUO

PROVIDER: E-GEOD-43630 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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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.

Dataset Information

The gene expression profiling array of mRNAs between portal vein tumor thrombus tissues and paired tumor tissues in hapatocellular carcinoma.

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