What is LIPEA?



Many bioinformatics approaches in genomics and proteomics aims to detect omics signatures, for instance the collection of genes that significantly change under a certain biological condition or that differ in case-control studies (Huang, Sherman, & Lempicki, 2009). Normally, such omic signatures need a secondary analysis in order to be understood in biological terms and linked to significant pathways (Chagoyen & Pazos, 2011). The methodology used in such cases is called functional enrichment analysis and, since it was originally proposed, a hundred of variations and different implementations have been developed. Nowadays, scientists in many omic fields make intensive use of enrichment analysis tools such as, to name a few, GSEA in genomics (Subramanian et al., 2005), MPEA (Kankainen, Gopalacharyulu, Holm, & Orešič, 2011) and MBRole (Chagoyen & Pazos, 2011) in metabolomics and, GeneTrail2 (Stöckel et al., 2016) in multiomics (transcriptomics, proteomics, miRNomics, genomics).

Lipidomics is an emerging field that aims at the large scale identification and quantification of diverse lipid repertoire in biologic systems that play critical roles in cellular functions (Gross & Holčapek, 2014). Although it is not the most developed omic field, its importance is increasing constantly over the years, particularly nowadays that absolute quantification methods by shotgun mass spectrometry are becoming widely available (Shevchenko & Simons, 2010). Therefore, we have developed and implemented a freely web platform called LIPEA (Lipid Pathway Enrichment Analysis) that can detect from a holistic point of view the pathways and categories that are significantly associated to the multiple lipids provided by the user.

Here, we introduce LIPEA algorithm, for functional analysis of lipids at the system level. LIPEA works with ID of lipid compounds contained in the Kyoto Encyclopedia of Genes and Genomes (KEGG Database; Ogata et al., 1999) and finds significantly perturbed pathways, applying statistical tests. LIPEA adopts the Fisher exact test, where the probability that the random event could happen is given by the hypergeometric distribution.

Additional details

  • Architecture The architecture of LIPEA was implemented adopting the Model-view-controller (MVC) pattern, which has been pursued for a clear design which separates different responsibilities within an interactive application (Veit & Herrmann, 2003). To simplify the use of this approach, we built our system using Symfony Framework, one of the most stable and documented tools in this field. Symfony allowed us to develop a modular platform, with a high degree of abstraction that provides a great scalability, allowing the addition of new modules and components in the future. The idea behind this architecture is to identify specific altered pathways - provided by the KEGG Database - using exclusively lipid compounds. The approach used to this task is the Over Representation Analysis (ORA).

  • Analysis workflow At the moment of the analysis submission, the server checks the inputs. If there are information not related with lipidomic data, the server will return an error. Instead, when the information is valid, the analysis starts and the lipid list and the background are transformed to KEGG IDs, using the internal mapping process (connected to Swiss Lipids, Lipid Maps, ChEBI, HMDB and KEGG databases via API REST). Once obtained the KEGG IDs, the server searches the pathways for the selected organism that correspond with the background. Then, the total lipid compounds from all the pathways are extracted and the Over Representation Analysis (ORA) starts in parallel for each pathway. For each ORA analysis completed, the server computes the Benja-mini and Bonferroni p-values corrections.

  • Results Once the analysis is finished, the server returns a list of enriched pathways sorted by p-value. The results are shown in an interactive table, where the user can change the order, view the conversion history, open the pathways maps, obtain the compounds details, among other features, and at the end download the list of pathways.