Genego metacore

Manufactured by Thomson Reuters

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GeneGo MetaCore is a software platform that provides a comprehensive analysis of biological systems and pathways. It offers a curated database of biological interactions and pathways, allowing researchers to investigate the complex relationships between genes, proteins, and other biomolecules.

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Lab products found in correlation

Wt ovation pico amplification kit, by Tecan (1 mentions) Hiscan scanner, by Illumina (1 mentions) Genego, by Thomson Reuters (1 mentions) Mousewg 6 v2.0 expression beadchip, by Illumina (1 mentions) Mirneasy kit, by Qiagen (1 mentions) Genespring gx v14, by Agilent Technologies (1 mentions) Ipa 9, by Qiagen (1 mentions)

22 protocols using genego metacore

Transcriptomic Analysis of Gene Expression

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Data were analyzed using the Partek Genomics Suite v 6.6 (Partek Inc., Louis, MO). Principal Component Analysis (PCA) was applied to assess sample distribution. Pre-processing of Affymetrix CEL-files was performed using the robust multi-chip analysis (RMA) algorithm, which performs background adjustment, quantile normalization and probe summarization. Differential expression analysis was realized using a one-way ANOVA. Class comparison was performed using ANOVAs, which included a multiple testing correction using False Discovery Rates (FDRs) set with a p-value <0.01 considered as significant for biological and molecular function analyses. Up- and down-regulated genes were identified using a fold-change of ≥1.5 and ≤ −1.5.
Enrichment analysis (EA) was performed using MetaCore (GeneGo, Thomson Reuters, NY), where genes with altered expression were mapped to Gene Ontology (GO). GO annotations were used as indicators of biological functions. GO describes gene products in terms of their associated biological processes, cellular components, and molecular functions [19 (link)]. Pathview (Luo et al. 2013) was used to construct canonical pathway maps.

Stur E., Aristizabal-Pachon A.F., Peronni K.C., Agostini L.P., Waigel S., Chariker J., Miller D.M., Thomas S.D., Rezzoug F., Detogni R.S., dos Reis R.S., Silva Junior W.A, & Louro I.D. (2019). Glyphosate-based herbicides at low doses affect canonical pathways in estrogen positive and negative breast cancer cell lines. PLoS ONE, 14(7), e0219610.

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Isolation and Analysis of Muscle Stem Cells

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Myogenic cells from pharyngeal and hindlimb (gastrocnemius and quadriceps) muscles were isolated, sorted using FACS, and collected from 10–30 mice per experiment. Samples were sent to the Emory University Integrated Genomics Core facility for total RNA isolation using Qiagen miRNEAsy kit with on-column DNAse treatment followed by one round of amplification using NuGEN’s WT-Ovation Pico amplification kit. Analysis of genomic gene expression was performed using an Illumina Mouse WG-6 v2.0 Expression BeadChip. Data was extracted using the Illumina HiScan Scanner and iScan control software. Illumina Genome Studio 2011.1 software suite was used to normalize probe level intensity data with background correction using manifest MouseWG-6_V2_0_R1_11278593_A.txt. Detection p-values were calculated as the proportion of negative control probes with expression greater than the regular probe in question using Partek Genome Studio. The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus [42 (link)] and are accessible through GEO Series accession number GSE69418 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE69418).
Data were further analyzed using both MetaCore genego (genego.com">https://portal.genego.com; Thomson Reuters) and Gene Set Enrichment Analysis (www.broadinstitute.org/gsea/index.jsp; Broad Institute).

Randolph M.E., Phillips B.L., Choo H.J., Vest K.E., Vera Y, & Pavlath G.K. (2015). Pharyngeal satellite cells undergo myogenesis under basal conditions and are required for pharyngeal muscle maintenance. Stem cells (Dayton, Ohio), 33(12), 3581-3595.

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Identifying Biomarkers and Resistance Mechanisms of BEZ-235 Treatment

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To determine which biological processes were altered following 24 hour BEZ-235 treatment, enrichment analysis using MetaCore GeneGO (Thomson Reuters) gene ontology⁴⁹ was performed using all protein/peptide pairs with a mean positive or negative fold change larger than 1.8 and a p-value ≤ 0.05 in each platform, analyzed separately or together. This information identified the top ten cellular processes impacted by BEZ-235 treatment, which could indicate potential biomarkers or drug resistance mechanisms. Proteins with changing ATP-uptake computed by both PRM and MRM datasets were used to generate a schematic representation of the altered signaling pathway, using MetaCore GeneGO pathway map creator to identify protein-protein interaction mechanisms.

Hoffman M.A., Fang B., Haura E.B., Rix U, & Koomen J.M. (2017). Comparison of Quantitative Mass Spectrometry Platforms for Monitoring Kinase ATP Probe Uptake in Lung Cancer. Journal of proteome research, 17(1), 63-75.

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Comprehensive Transcriptome Analysis of PDX Models

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Data were normalized and analyzed using GeneSpring GX v.14.8 software (Agilent Technologies). Data transformation was applied to set all the negative raw values at 1.0, then the quintile normalization was applied. The probes detected in at least one sample were used for statistical analyses. Unsupervised principal component analysis and correlation analysis (Pearson’s correlation) were performed to assess sample similarity and to assess the global gene expression profile of PDX models. Differentially expressed genes were selected to have a ≥2-fold expression difference between matching PDX and primaries and an adjusted p-value ≤ 0.05 at paired t-test, with Benjamini and Hoechberg correction for false positive reduction. Hierarchical clustering was performed for OS samples with GeneSpring clustering tool using the list of differentially expressed genes and the Manhattan correlation as a measure of similarity. Pathway and network analysis of differentially expressed genes was determined using the web-based software MetaCore (GeneGo, Thomson Reuters).

Nanni P., Landuzzi L., Manara M.C., Righi A., Nicoletti G., Cristalli C., Pasello M., Parra A., Carrabotta M., Ferracin M., Palladini A., Ianzano M.L., Giusti V., Ruzzi F., Magnani M., Donati D.M., Picci P., Lollini P.L, & Scotlandi K. (2019). Bone sarcoma patient-derived xenografts are faithful and stable preclinical models for molecular and therapeutic investigations. Scientific Reports, 9, 12174.

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Enrichment Analysis of Oligo-Array Data

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Published oligo-array data by Ueda et al was analyzed using GeneGo Metacore (Thomson Reuters) (27 (link)). The Enrichment Analysis Workflow was performed using the gene list, fold-change, and P-value scores generated by edgeR. A threshold P-value of <0.05, and threshold fold-change <0.5 was set when performing the analysis in GeneGo.

Matossian M.D., Elliott S., Rhodes L.V., Martin E.C., Hoang V.T., Burks H.E., Zuercher W.J., Drewry D.H., Collins-Burow B.M, & Burow M.E. (2021). Application of a small molecule inhibitor screen approach to identify CXCR4 downstream signaling pathways that promote a mesenchymal and fulvestrant-resistant phenotype in breast cancer cells. Oncology Letters, 21(5), 380.

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Differential Gene Expression Analysis Protocol

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Affymetrix CEL files were normalized using RMA (Irizarry et al., 2003 (link)). Differentially expressed genes were detected with a threshold of fold change ≥2 and adjusted p-value ≤0.01. Pathway enrichment analyses were performed using GeneGo Metacore from Thomson Reuters (Version 6.24 build 67895, https://portal.genego.com/). GSEA was performed using GSEA software (http://www.broadinstitute.org/gsea) (Subramanian et al., 2005 (link)) with default parameters.
Comparative analyses with other published gene expression data derived on different platforms, were performed by comparison of differentially expressed genes (log₂ fold-change).

Luc S., Huang J., McEldoon J.L., Somuncular E., Li D., Rhodes C., Mamoor S., Hou S., Xu J, & Orkin S.H. (2016). Bcl11a-deficiency leads to hematopoietic stem cell defects with an aging-like phenotype. Cell reports, 16(12), 3181-3194.

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Transcriptional Regulation Analysis Pipeline

Cited 1 time

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Quality Threshold Clustering (QTC) was performed with a sample jackknife correlation cut-off at 0.4, with a minimum cluster size of 15 genes. Significance Analysis of Microarrays (SAM) was performed with a FDR cut-off set at 0 in all analyses [20 (link)]. SAM and QTC gene lists are supplied in Additional file 1: Table S4. Literature derived associations between gene lists and transcriptional regulation was analyzed using GeneGo MetaCore™ (Thomson Reuters). Transcription factor binding motif enrichment was examined both on the full promoter sequence (−5000 - +1000 bp from TSS) as well as DNaseI footprint filtered sequence [21 (link)]. In-silico enrichment of ChIP-Seq binding was analyzed by two methods; a one-tailed Fisher’s exact test and a resampling based test examining both the number of bound promoters as well as the total number of identified ChIP-Seq peaks in a gene list compared to 100 000 randomly sampled gene lists of equal size. Only array probes mapping to RefSeq genes were included for each analysis.

Eriksson P., Aine M., Veerla S., Liedberg F., Sjödahl G, & Höglund M. (2015). Molecular subtypes of urothelial carcinoma are defined by specific gene regulatory systems. BMC Medical Genomics, 8, 25.

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Cytokine Enrichment in COPD

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The mean fold changes of the detected biomarkers were calculated between COPD and control subjects. Cytokines showing 1.5-fold changes were used for biological processes, pathways, and network enrichment analyses. The purpose of this analysis was to identify the enriched biological processes and the pathways associated with COPD. Interaction networks among the significantly elevated cytokines in COPD were constructed using Cytoscape and GeneGo Metacore™ software (Thomson Reuters, St Joseph, MI, USA).

Bade G., Khan M.A., Srivastava A.K., Khare P., Solaiappan K.K., Guleria R., Palaniyar N, & Talwar A. (2014). Serum cytokine profiling and enrichment analysis reveal the involvement of immunological and inflammatory pathways in stable patients with chronic obstructive pulmonary disease. International Journal of Chronic Obstructive Pulmonary Disease, 9, 759-773.

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Differential Proteome Analysis of ARCaP Sublines

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Normalized spectral counts from cell proteomics were assigned to a peptide sequence with 95% confidence. A minimum of two identified peptides was required to confirm a protein sequence with 95% confidence. Missing values were imputed with the minimum non-zero normalized spectral count. An unpaired, two-sample t-test was performed on normalized spectral counts in order to determine differentially expressed proteins between ARCaP_E and ARCaP_M, and a P-value of < 0.05 was used as a cutoff for statistical significance. Pathway analysis was performed using GeneGO MetaCore (Thomson Reuters, https://portal.genego.com/) on proteins with a cut-off mean expression set at least 1.5 fold difference between ARCaP_E and ARCaP_M.

Stewart P.A., Khamis Z.I., Zhau H.E., Duan P., Li Q., Chung L.W, & Sang Q.X. (2017). Upregulation of minichromosome maintenance complex component 3 during epithelial-to-mesenchymal transition in human prostate cancer. Oncotarget, 8(24), 39209-39217.

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Enrichment Analysis of Differentially Expressed Genes

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Differentially expressed protein-coding genes were utilized as the input list to perform enrichment analysis with GeneGo MetaCore from Thomson Reuters. GeneGo Enrichment analysis tool uses manually annotated reference pathways to calculate the enrichment of a given list of genes in each pathway and provides p value and FDR value that reflect the chance the given number of genes from a pathway would appear in the list by chance. Only pathways with FDR less than 0.1 were considered as significantly enriched.

Magistri M., Velmeshev D., Makhmutova M, & Faghihi M.A. (2015). Transcriptomics Profiling of Alzheimer’s Disease Reveal Neurovascular Defects, Altered Amyloid-β Homeostasis, and Deregulated Expression of Long Noncoding RNAs. Journal of Alzheimer's Disease, 48(3), 647-665.

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