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Pipeline publication

[…] platform at the Genome Institute of Singapore or in the S. Albani lab (SingHealth Translational Immunology and Inflammation Centre, Singapore). Probe counts were analysed with the nSolver software (Nanostring Technologies). We used the geometric mean of six normalization genes (Cnga2 was discarded because of its low counts) as normalization factor. Triplicates were run, each corresponding to an independent neuron preparation with both miR-27b CT and KD conditions. We used log2-transformed fold-change (FC) to display differential gene expression: log2FC = log2(KD) –log2(CT); FC = 2 ^ log2FC. For combinatorial intersection analysis of nCounter datasets, we used the open source CRAN R package UpSet []., Microarray analysis was performed by the Duke-NUS Genome Biology Facility on an Illumina platform (San Diego, CA). Biotin-labeled cRNA was prepared using the TotalPrep RNA amplification Kit (Ambion) from 500 ng total RNA. 1.5 ug of biotin-labeled cRNA was hybridized to MouseWG-6 v2.0 expression beadchips, and chips were washed and stained according the manufacturer’s instructions. Beadchips were scanned using the Illumina BeadArray reader. Expression data were analysed using the R-Bioconductor open source software (limma R package) and are derived from triplicate experiments, each corresponding to one neuronal preparation with both miR-27b CT and KD conditions. Genes with fold-change > 1.5 and a false discovery rate < 0.05 were considered as differentially-regulated. Hierarchical clustering, dendrograms and heat maps were performed and displayed using the clustergram function in Matlab. For GSEA analysis of microarray data, we used the GSEA software available on the GSEA-Broad Institute website. We ran our expression dataset against a library of 1330 curated gene sets for canonical pathways (c2.cp.v5.1.symbols.gmt; MSigDB v 5.1). Qualitatively similar results were obtained with a gene ontology (GO) gene set library (c2.bp.v5.1.symbols.gmt). The statistical significance (nominal p value) of the enrichment score (ES) was estimated by running 1000 gene set permutations. The ES was normalized (NES) to account for the size of the gene set. To adjust for multiple testing across the 1330 gene sets, we computed the false discovery rate (FDR) and controlled the FDR at 25 %. Gene network […]

Pipeline specifications

Software tools UpSet, Beadarray, limma, GSEA
Diseases Hearing Disorders, Sensation Disorders, Neurologic Manifestations, Nervous System Diseases