Transcriptome analysis of paired luminal breast tumor and para-carcinoma tissues
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE115144 | GEO | 2018/06/01
REPOSITORIES: GEO
Similar Datasets
Project description:The lncRNA expression profiles in three pairs of hTERT-positive gastric cancer tissue sand hTERT-negative para-cancerous tissues. The para-cancerous tissue is at least 5cm away from the cancer tissue. The expression of hTERT of identified by immunohistochemistry before RNA extraction for lncRNA assay. LncRNAs/mRNAs in 3 gastric cancer tissue and 3 paired para-cancerous tissue (Control) by microarray using Arraystar Human LncRNA Microarray v2.0
2014-06-26 | E-GEOD-58828 | biostudies-arrayexpress
Project description:Transcriptome analysis of paired luminal breast tumor and para-carcinoma tissues
| PRJNA473920 | ENA
Project description:LncRNA expression profiles were sucessfully contructed in 370 patients with NSCLC and 198 corresponding adjacent noncancerous tissues using a custom microarray containing probes for 2412 lncRNAs and an outcome prediction of lncRNA signature was successfully identified for predicting prognosis in NSCLC.
2020-08-31 | GSE143018 | GEO
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.
2022-11-24 | E-MTAB-9167 | biostudies-arrayexpress
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.
2022-11-23 | E-MTAB-8730 | biostudies-arrayexpress
Project description:The human LncRNA microarray analysis of the 6 plasma samples from Coronary Artery Disease patients and non Coronary Artery Disease Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization was performed using Expander6 and subsequent data processing was performed using the GeneSpring GX v11.5.1 software package (Agilent Technologies). After low intensity filtering, LncRNAs and mRNAs that at least 2 out of 12 samples have flags in Present or Marginal (“All Targets Value”) were chosen for quantile normalization and further data analysis. Differentially expressed LncRNAs and mRNAs with statistical significance 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 LncRNAs expression pattern among samples.
2015-05-05 | E-GEOD-68506 | biostudies-arrayexpress
Project description:Hypoxic microenvironment plays important roles in the progression of solid tumors including oral squamous cell carcinoma (OSCC). Long noncoding RNAs (lncRNAs) have gained much attention in the past few years. However, it is not clear whether lncRNAs could regulate hypoxia-adaptation of OSCC, and which lncRNAs participate in this process. Using an lncRNA microarray, we analyzed the aberrant lncRNA expression profiles in OSCC tissues compared with paired normal oral mucosa as well as in hypoxic OSCC cells compared with normoxic OSCC cells. Our data revealed 2053 differentially expressed (Fold Change >= 2.0, P-value <= 0.05) lncRNAs, among which 934 lncRNAs were significantly up-regulated and 1119 lncRNAs were down-regulated in OSCC compared with paired normal mucosa. Six OSCC tissues and paired normal oral mucosa were obtained from 6 patients with OSCC. LncRNA expression profiles were evaluated by an Agilent Human LncRNA Array v3.0 (8 x 60K, Arraystar).
2016-07-26 | E-GEOD-84805 | biostudies-arrayexpress
Project description:To comprehensively identify the glucose-regulated lncRNAs, we have employed ArraryStar LncRNA Microarry discovery platform to detect lncRNA expression in glucose-starved and glucose-stimulated triple-negative breast cancer cells. Differentially expressed LncRNAs with statistical significance were identified through Volcano Plot filtering between two groups.
2019-06-03 | GSE106729 | GEO
Project description:Long non-coding RNAs (lncRNAs) play multiple key regulatory roles in various biological processes. However, their function in influenza A virus (IAV) pathogenicity remains largely unexplored. Here, using next generation sequencing, we systemically compared the whole-transcriptome response of the mouse lung infected either with high-pathogenic (A/Chicken/Jiangsu/k0402/2010, CK10) or with nonpathogenic (A/Goose/Jiangsu/k0403/2010, GS10) H5N1 strains. A total of 370 significantly differentially expressed (DE) lncRNAs from three replicates were identified associated with the high virulence of CK10, whereas the corresponding number for GS10 was 229.
2018-09-06 | GSE100522 | GEO
Project description:We developed a stringent selection pipeline for lncRNA identification, combining high-throughput RNA sequencing and computational approaches. Using this pipeline, we annotated 1,353 lncRNAs in Arabidopsis thaliana. We further found that one fifth of the lncRNAs were associated with Polycomb repressive complex 2 (PRC2). Some PRC2-associated lncRNAs could repress the transcription of their neighboring genes through mediating histone H3 lysine 27 trimethylation.
2015-11-28 | GSE42695 | GEO