Ingenuity pathway analysis ipa

Each list of DEGs was further investigated using Ingenuity Pathway Analysis (IPA; Ingenuity Systems, Redwood City, CA, USA). DEGs, along with their respective fold-changes and adjusted P-values were submitted to IPA for analysis. Ingenuity pathway analysis allows examination of over-represented biological pathways and biological functions [39 (link)]. Ingenuity pathway core analysis was performed on genes identified as statistically significant (adjusted P < 0.1) following DESeq2 analysis. However, if too few genes reached an adjusted P-value < 0.1 within a diet-breed combination for IPA to be performed, that combination would be excluded from IPA. Consequently, 160 and 158 genes were uploaded to IPA for the CH H1, ZG and H2 diets, respectively, while 27 genes were uploaded to IPA for the HF H1, diet.
Genes were then mapped to IPA biological functions and canonical pathways. Biological functions and canonical pathways were significantly enriched if the P-value of the overlap between the input gene list and the genes within the database for a given function or pathway was less than 0.05. Upregulation or downregulation of functions or pathways was determined by a z-score, as calculated by IPA from the expression levels of input genes in a function or pathway. A negative z-score represented downregulation of a function or pathway, while a positive z-score represented upregulation.

The network analysis of transcriptomics data was conducted using Ingenuity Pathway Analysis (IPA; Ingenuity Systems). The list of DEG was uploaded to run the core analysis, focusing on upstream transcription regulators and their downstream target genes. For the metabolomics network reconstruction, the list of significant compounds were annotated against the PubChem biochemical database and used for the IPA analysis.

The microarray gene expression data was analyzed using Ingenuity Pathway Analysis (IPA; Ingenuity Systems, Redwood City, CA, USA) to determine whether genes associated with particular diseases, biological functions, or canonical signaling pathways were preferentially up- or downregulated in IIP patients relative to control subjects. Diseases and biological functions for which differential gene expression was observed were grouped into three categories: (1) diseases and disorders; (2) molecular and cellular functions; and (3) physiological system development and function.

Cardiac tissue from each treatment group was digested following the Filter Aided Sample Preparation (FASP) method. To identify and simultaneously quantify proteins expressed in the hearts, label‐free shotgun proteomics experiments were carried out according to detailed protocols described in the Online Supplement. Mass spectrometry proteomics data are deposited to the ProteomeXchange Consortium via the PRIDE³¹ partner repository with PXD017413 data set identifier. A panel of differential proteins (considering only unique proteins) was subjected to an in‐silico analysis by the Ingenuity Pathway Analysis (IPA) (Ingenuity Systems, Mountain View, CA) and Gene Ontology.

The Ingenuity Pathway Analysis (IPA, Ingenuity Systems, Mountain View, CA; http://www.ingenuity.com) was used to identify the pathways and biological functions of genes affected by DPMs. The significance was set at a p-value of 0.01 by the right-tailed Fisher Exact Test.

To determine the biological processes enriched within genes of differential methylation in the comparisons, we uploaded the gene lists into the Ingenuity Pathway Analysis (IPA; Ingenuity Systems, Redwood City, CA, USA). Each gene symbol was linked to its corresponding gene object in the Ingenuity Pathways Knowledge Base. Then the IPA integrates the genes and molecules that share part of the same biological functions or regulatory networks interacting together. The over-represented cellular and molecular functions were ranked according to the calculated P-value.