# MOMIC: A Multi-Omics Pipeline for Data Analysis, Integration and Interpretation
## 4 Results  
This section shows the different outputs that can be obtained by MOMIC analysis pipelines. Different sources of data have been used to illustrate its functionality, including synthetic data, therefore the lists of significant genes obtained from this type of data are not evaluated here. The subsection below, Use cases: Application on real projects, briefly describe two successful published studies carried out using MOMIC and a gene priorization project, serving as a good validation of this tool.  
GWES from Microarrays. This protocol makes use of Gene Expression Omnibus (GEO) [32] datasets GSE48350, which contains brain expression data from normal controls and AD cases, and GSE11882/GSE15222 datasets, also a brain transcriptomic study on normal controls and AD cases. Figure 6a illustrates the results provided by MOMIC in tabular format for the differential expression analysis, including information such as log2 fold changes (logFC), lower and upper confidence intervals (CLL, CLU), \(p\)-value, FDR adjusted \(p\)-value and Entrez Gene IDs (Supplementary Data Tables S1 and S2). Graphical outputs include Volcano (Figure 6b) and Heatmap (Figure 6c) plots, enabling quick visual identification of the most biologically relevant genes. To illustrate the meta-analysis protocol, the results from these two analyses are combined in MOMIC (Supplementary Data Table S1 and S2).  
Figure 6: Results obtained from Microarray DE analysis. (a) candidate genes in tabular format. (**b**,**c**), Volcano and Heatmap plots highlighting top DE genes.  
GWES from RNAseq. Synthetic data from astrocytes with fake genotype and phenotype have been created to depict the RNAseq pipeline. The various outputs obtained from this pipeline comprises summary statistics about number and quality of reads (Figure 7a,b), tabular data with log2 fold changes, \(p\) values and adjusted \(p\) values, and Volcano and Heatmap plots for the visualisation of the differential expression results.  
GWAS. Given the restrictions applying to raw genotypic data, which is needed to illustrate the GWAS protocol, we used whole genome genotypes from the 1000 Genomes (1 KG) project [31], adding a simulated dichotomic case status for running the association analysis. The 1 KG project ran between 2008 and 2015, creating the largest public catalogue of human variation and genotype data. Figure 8 lists the top 6 annotated SNPs obtained, along with chromosome and allele information, and statistics like \(p\)-value, standard error (ES) and Estimated odds ratio (OR). Figure 8b shows an example of PCA plot generated by MOMIC, showing PC means and suggestive thresholds for the Caucasian population represented by red and blue dotted lines. Manhattan and QQ plots graphically summarizes the results from individual association studies (Figure 8c,d).  
Proteomics. Proteomics data from postmortem brain tissue collected through The National Institute on Aging's Baltimore Longitudinal Study of Aging (BLSA) [33] were obtained from Synapse (10.7303/syn3606086). Differential expression is explored similarly to GWES Microarray on both graphical and tabular fashion (Supplementary Data Table S3) as depicted in Figure 6a-c.  
Integrative Analysis. Integrative analysis using the RRA approach was applied to the output gene lists obtained from the above analysis. RRA output includes exact and  
Figure 7: NGS quality plots generated by MultiQC integrated in MOMIC. (**a**) Sequence Quality Histograms, (**b**) number of reads.  
adjusted \(p\)-values (data not shown). As mentioned earlier, this analysis is not expected to have biological significance. Another application of this integrative analysis is gene prioritization, which is mentioned below.  
Enrichment Analysis. Given a list of candidates genes generated by MAGMA, DE meta-analysis or integrative analysis, it can be explored for identifying relevant gene functions. Figure 9 shows a graphical representation of the enrichment analysis carried out on integrative results.