Project description:LncRNA expression profiling for liver tissues of mice fed for NFD, LSF and HSF groups Summary: An abstract of the experiment and the data analysis. Experiment Workflow: A workflow of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: Mouse 8 x 60K LncRNA expression array information. Summary Table of Files for Data Delivery: Contains summary table of files for data delivery and the recommended software programs for viewing the data. Data Analysis for LncRNAs 1. Raw LncRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity LncRNAs were filtered (LncRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these LncRNAs can be found from the LncRNA Expression Profiling Data.xls file). 2. Quality assessment of LncRNA data after filtering: Contains Box Plot and Scatter Plot for LncRNAs after filtering (This data can be found from the LncRNA Expression Profiling Data.xls file). 3. Differentially expressed LncRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed LncRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed LncRNAs (The heat map can be found from the LncRNA Expression Profiling Data.xls file). Data Analysis for mRNAs 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity mRNAs were filtered (mRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these mRNAs can be found from the mRNA Expression Profiling Data.xls file). 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering (This data can be found from the mRNA Expression Profiling Data.xls file). 3. Differentially expressed mRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed mRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed mRNAs (The heat map can be found from the mRNA Expression Profiling Data.xls file). 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs. LncRNA Classification and Subgroup Analysis 1. Rinn lincRNAs profiling: Contains profiling data of all lincRNAs based on John Rinn's papers (This data can be found from the Rinn lincRNAs profiling.xls file). 2. LincRNAs nearby coding gene data table: Contains the differentially expressed lincRNAs and nearby coding gene pairs (distance < 300 kb) (This data can be found from the LincRNAs nearby coding gene data table.xls file). Sample RNA Quality Control: Sample quality control data file from NanoDrop ND-1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction of methods for sample preparation, microarray design, experiment, and data analysis.

Project description:LncRNA expression profiling for liver tissues of mice fed for a normal diet (NFD, 3mice) and a high-fat diet (HFD, 3mice) Summary: An abstract of the experiment and the data analysis. Experiment Workflow: A workflow of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: Mouse 8 x 60K LncRNA expression array information. Summary Table of Files for Data Delivery: Contains summary table of files for data delivery and the recommended software programs for viewing the data. Data Analysis for LncRNAs 1. Raw LncRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity LncRNAs were filtered (LncRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these LncRNAs can be found from the LncRNA Expression Profiling Data.xls file). 2. Quality assessment of LncRNA data after filtering: Contains Box Plot and Scatter Plot for LncRNAs after filtering (This data can be found from the LncRNA Expression Profiling Data.xls file). 3. Differentially expressed LncRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed LncRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed LncRNAs (The heat map can be found from the LncRNA Expression Profiling Data.xls file). Data Analysis for mRNAs 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity mRNAs were filtered (mRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these mRNAs can be found from the mRNA Expression Profiling Data.xls file). 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering (This data can be found from the mRNA Expression Profiling Data.xls file). 3. Differentially expressed mRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed mRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed mRNAs (The heat map can be found from the mRNA Expression Profiling Data.xls file). 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs. LncRNA Classification and Subgroup Analysis 1. Rinn lincRNAs profiling: Contains profiling data of all lincRNAs based on John Rinn's papers (This data can be found from the Rinn lincRNAs profiling.xls file). 2. LincRNAs nearby coding gene data table: Contains the differentially expressed lincRNAs and nearby coding gene pairs (distance < 300 kb) (This data can be found from the LincRNAs nearby coding gene data table.xls file). Sample RNA Quality Control: Sample quality control data file from NanoDrop ND-1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction of methods for sample preparation, microarray design, experiment, and data analysis.

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.

			Action	DRS
	SRR29412515_1.fastq.gz	Fastqsanger.gz
	SRR29412515_2.fastq.gz	Fastqsanger.gz
	SRR29412516_1.fastq.gz	Fastqsanger.gz
	SRR29412516_2.fastq.gz	Fastqsanger.gz
	SRR29412517_1.fastq.gz	Fastqsanger.gz

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