'Vikodak' word is originated from 'Sanskrit' language, which means 'Decoder'. iVikodak being an 'improved' version of Vikodak has hence been named iVikodak.

In simplest terms, iVikodak is a tool for inferring, analysing, visualizing, storing and sharing functional information from 16S microbiome data. Validation experiments (corresponding results and their interactive visualizations) on over 1400 metagenomic samples have confirmed the utility of iVikodak in:

1. Automated 16S driven functional metagenomic anaysis
2. Simultaneous comparative functional metagenomics for multiple environments at a time
3. Indepth probing of pathways of interest
4. Highly interactive visualizations like Ordination (2D and 3D) plots, Cladograms, Heatmaps, Dendrobars, Box Plots and Network diagrams ensure meaningful insights to the data of interest.
5. Co-Metabolism and Independent contributions algorithms ensure that two typical community behaviors (Co-metabolic existence and independent thriving) are taken into consideration for functional inferences
6. iVikodak also brings into picture the concept of 'Function driven microbial interaction patterns (networks)'.
7. iVikodak provides to end users the options of inferring functions in terms of KEGG, COG, TIGRfam and Pfam. 8. iVikodak also provides the end users with 'Personalized' Dashboards and 'Portable Dashboards', wherein each execution is tagged to a 10 character alphanumeric job-id and the JOB ID can be used to access personal Results Dashboard for upto 7 days after job submission. A user can download .dash file from his/her dashboard which can help the user to recreate the dashboard (with all the results) anytime in future. The dash file therefore represents a Packaged ensemble of functional results which can be stored as well as shared for easy and portable access to results anytime in future.

In short, iVikodak facilitates end-users to concomitantly infer, statistically analyse, and compare multiple microbial communities, and in the process generate a plethora of intuitive self-explanatory visual outputs in an automated fashion.

Yes! iVikodak accepts taxonomic abundance data generated using Greengenes reference databaswe (v13.5). It also accepts RDP and SILVA derived taxonomic profiles. Samples of the appropriate data structure are provided in each module.

Note that iVikodak automatically detects the format/ Nature of data and does the needful processing.

Global Mapper provides to end-users the choice of two distinct algorithmic work-flows viz. ' Co- metabolism ' and 'Independent Contributions' . The principle behind these two work-flows is as follows:

The Co-metabolism algorithm is based on the underlying assumption that the genes/enzymes expressed by various microbes residing in an environment may pool together and contribute to the functioning of specific metabolic pathway(s). Therefore, the effective abundance of a metabolic pathway (in an environment with co-metabolising microbes) is expected to be a function of the total enzyme pool contributed by the co-metabolising microbes.

In contrast, the Independent contributions algorithm assumes the independent existence of microbes in the environment. Under this assumption, the effective abundance of a metabolic pathway is the sum total of the pathway abundances computed from individual microbes residing in that environment. Independent Contributions algorithm can therefore enable a user to look into the functional inferences from an entirely different perspective. He/She can find out the 'Individual Contributions' of each resident microbe towards various functions inferred for the metagenomic environment.

A major limitation of the current methods for function prediction is the inability to account for the constituents of a metabolic pathway. In other words, a metabolic pathway might be effected by the joint expression of over 30 genes/enzymes, but mere expression/presence of 1-5 genes/enzymes might not effect the expression of the associated pathway. It is thus crucial to define a parameter for filtration of pathways based upon the proportion of various pathway associated genes/enzymes expressed by the microbiota.

Considering the need for such a parameter, Pathway Exclusion Cut-off (PEC) value has been defined in both algorithms of Global Mapper. PEC value is defined as the minimum percentage of genes/enzymes belonging to any metabolic pathway, that must be expressed by a given microbiota for tagging that pathway as being expressed by the microbiome. For example, a PEC value of 30 would mean that a given microbe/microbiota must express atleast 30% of genes/enzymes belonging to any metabolic pathway for considering that pathway as being expressed by that microbe/microbiome.

Both modules of Global Mapper have been developed in such a way that apart from providing the raw hits (where raw hits refer to the most inclusive criteria wherein even the expression of single enzyme/gene is considered for presence of a metabolic pathway) they provide the KEGG pathway (all three level) expression profiles for the microbial abundance data at various PEC values (50-90) as well.

iVikodak provides the end users with 'Personalized' Dashboards and 'Portable Dashboards', wherein each successful job execution/ submission is tagged to a 10 character alphanumeric JOB ID and the JOB ID can be used to access personal Results Dashboard for upto 7 days after job submission. A user can download .dash file from his/her dashboard which can help the user to recreate the dashboard (with all the results) anytime in future using the Recreate Dashboard module in Auxiliary menu option. The dash file therefore represents a Packaged ensemble of functional results which can be stored as well as shared for easy and portable access to one's results anytime in future.