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Omics explorer v 3.2

Manufactured by Qlucore
Sourced in Sweden

Qlucore Omics Explorer (v.3.2) is a visual analytics software for exploring and analyzing high-dimensional data, such as genomics and other omics data. The software provides interactive visualization tools and statistical analysis capabilities to help researchers gain insights from complex data sets.

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5 protocols using omics explorer v 3.2

1

Microarray Analysis of miR-33 Knockout Mice

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Further details and an outline of resources used in this work can be found in the Supplemental Information. Briefly, microarray analysis was performed as previously described (Fang et al., 2017 (link)), using Agilent SurePrint G3 Mouse 8×60K Microarray. Gene network and pathway analysis were carried out using Qlucore Omics Explorer (v.3.2) (Qlucore) and ingenuity pathway analysis (Ingenuity Systems QIAGEN). Animal studies were approved by the Institutional Animal Care and Use committee of Yale University School of Medicine. WT C57BL/6 mice were purchased from The Jackson Laboratory (Bar Harbor, ME, USA). Generation of miR-33−/− mice was accomplished with the assistance of Cyagen Biosciences. Induction of diet-induced obesity was accomplished by feeding a HFD (60% fat) (D12492; Research Diets, New Brunswick, NJ, USA). Measurements of metabolic function, circulating lipids, and adipocyte proliferation/function were carried out using established techniques. Statistical differences were measured using an unpaired two-sided Student’s t test or one-way ANOVA with Bonferroni correction for multiple comparisons. Normality was checked using the Kolmogorov-Smirnov test. A nonparametric test (Mann-Whitney) was used when data did not pass the normality test. p < 0.05 was considered statistically significant.
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2

Microarray Analysis of miR-33 Knockout Mice

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Further details and an outline of resources used in this work can be found in the Supplemental Information. Briefly, microarray analysis was performed as previously described (Fang et al., 2017 (link)), using Agilent SurePrint G3 Mouse 8×60K Microarray. Gene network and pathway analysis were carried out using Qlucore Omics Explorer (v.3.2) (Qlucore) and ingenuity pathway analysis (Ingenuity Systems QIAGEN). Animal studies were approved by the Institutional Animal Care and Use committee of Yale University School of Medicine. WT C57BL/6 mice were purchased from The Jackson Laboratory (Bar Harbor, ME, USA). Generation of miR-33−/− mice was accomplished with the assistance of Cyagen Biosciences. Induction of diet-induced obesity was accomplished by feeding a HFD (60% fat) (D12492; Research Diets, New Brunswick, NJ, USA). Measurements of metabolic function, circulating lipids, and adipocyte proliferation/function were carried out using established techniques. Statistical differences were measured using an unpaired two-sided Student’s t test or one-way ANOVA with Bonferroni correction for multiple comparisons. Normality was checked using the Kolmogorov-Smirnov test. A nonparametric test (Mann-Whitney) was used when data did not pass the normality test. p < 0.05 was considered statistically significant.
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3

Microarray Analysis of Differential Gene Expression

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Microarray analysis was performed commercially with
OneArray® (Phalanx Biotech Group, San Diego, CA) with RNA
samples isolated from control (N=3), 2 week-1 dose (N=3), and 4 week-2 dose
mice(N=3). Qlucore Omics Explorer v 3.2 (Qlucore AB, Lund, Sweden) was used for
identifying differentially-expressed genes (q < 0.01) using a one-way
analysis of variance (ANOVA). Principal component analysis plots, unsupervised
hierarchical clustering, and heat maps were also generated in Qlucore.
Differentially expressed genes identified by Qlucore were subjected to further
analysis by Ingenuity Pathway Analysis (Ingenuity Systems QIAGEN Build: 389077M,
Content version: 27821452, Redwood City, CA, USA).
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4

Gene Expression Normalization and Analysis

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We used nSolver software v3.0 (NanoString Technologies) for the normalization of raw counts for various genes as determined by the NanoString nSolver platform. SPSS software v24.0 (IBM, Armonk, NY, USA) was utilized for other statistical evaluations. Hierarchical clustering and principal component analyses were performed employing Qlucore Omics Explorer v3.2 (Lund, Sweden). Results with fold change ≥2.0 and p-value < 0.05 were considered significant.
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5

Differentially-Expressed Transcripts and Proteins Analysis

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Qlucore Omics Explorer v 3.2 (Qlucore AB, Lund, Sweden) was used to identify differentially-expressed transcripts and proteins using a two-tailed Student’s unpaired t-test comparison between the knock-down and scramble control groups. The q-values (q< 0.1) were generated based on the FDR method [30 ]. Unsupervised hierarchical clustering and heat maps were also generated in the Qlucore program. Pathway analysis of differentially-expressed genes across groups was performed by using the Ingenuity Pathway Analysis Knowledge Base (IPA Build 458397M, version 39408507; Ingenuity Systems, QIAGEN). The top canonical pathways involving those differentially-expressed transcripts and proteins were calculated based on the Fisher’s right-tailed exact test (p < 0.05).
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