Dataset features


Application: miRNA array analysis
Number of samples: 9
Release date: Oct 31 2017
Last update date: Jul 27 2018
Access: Public
Diseases: Breast Neoplasms, Neoplasms
Dataset link miRNA expression data in MCF-7 breast cancer Cell line post BCAS2 and FST knockdown

Experimental Protocol

We used affymetrix miRNA expression profile of the two transcriptional targets of Estrogen Related Receptor β (ERRβ) post BCAS2 and FST knockdown to identify the downstream signaling of ERR β in Breast Cancer. The total RNA from control siRNA (triplicate), BCAS2 (triplicate) and FST (triplicate) knock-down samples were run in Affymetrix miRNA 3.0 platform and hybridized with miRNA-specific probes for 16hr at 60 rpm and at 48°C. Microarray scanner 3000 7G was used for signal detection. Raw data sets were extracted from all Cel files (raw intensity file) after scanning of slides. These raw data sets were separately analysed using Affymetrix Expression Console and GeneSpring GX12.1 software followed by differential miRNA expression, fold change and cluster analysis. All the original microarray data (CEL files-) for the control & test experiment were pre-processed using RMA (Robust Multichip Average) algorithm that consists of three steps: a background adjustment, quantile normalization and finally summarization. All the above procedures were done by selecting default RMA algorithm, data adjustment and background correction (GABG) in Affymetrix Expression Console The normalized intensity files were exported from Expression Consoles tool. In the next step, miRNA probesets representing Homo sapiens were filtered from the normalized intensity file. After generating Homo sapiens miRNA probesets intensity files, these files were imported in GeneSpring GX 12.1 software for differential miRNAs expression study followed by statistical analysis. Furthermore, differentially expressed miRNAs were preceded for fold change analysis and cluster analysis for the identification of co expressed miRNAs or similar type of experiment profiles. The total number of Homo sapiens miRNA probesets detected for the experiment is 5,617. After data processing and quality control only 2288 probesets left out of 5,617. Then, all normalized data were imported in Gene Spring 12.1 for the differential expression and cluster analysis. After normalization, experimental grouping was done according to the experiment conditions. The averages over the replicate sets were taken during the experimental grouping. Differential miRNA expression analysis was performed by comparing experiment conditions with control. One-way ANOVA method was applied for assessing the statistically significant and differentially expressed miRNAs. The cut off for significant p-value was 0.05. Next, cluster analysis was performed for the identification of co-expressed miRNA sets across the samples. miRNA expression alteration was illustrated using heat map image of hierarchical clustering. Hierarcheal clustering (hcl) was performed for the miRNAs expressed with fold change>=2.0.








Sandeep Mishra