A biological pathway is the collection of interactions among molecules that are related to a function in a cell. The complexity of regulatory mechanisms and their interplay is formidable. Changing just one element is likely to cause downstream effects, disturb feedback-loops and trigger compensatory backup systems.
Bioinformatic pathway analysis seeks to answer which main cellular pathways are affected by the the genes that are differentially expressed between sample groups. This is done by comparing the mRNA results from the differential gene expression analysis with a pathway database. For miRNAs quantified by small RNA sequencing, target prediction is initially performed followed by pathway analysis based on the targeted mRNAs.
This type of analysis comes in many flavors; pathway analysis, gene ontology enrichment analysis, gene set enrichment analysis. The common goal is to ascribe a likely biological mechanisms affected by the difference between the samples being compared.
We mainly perform pathway analysis on gene ontology (GO) terms. GO terms are divided into three categories; biological process, cellular component and molecular function.
Alternatively, we also use the KEGG database.
Most significantly enriched GO terms. Gives you a visual representation of the pathways/terms most significantly affected by the difference between the samples.
All significantly enriched GO terms. Dive into the specifics behind each term and get exact individual info for each GO term, including GeneIDs, p-values, and FDR values
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