Welcome to PIUMet
Frequently Asked Questions
What is PIUMet?
PIUMet, a web-based tool for integrative analysis of untargeted metabolomic data. PIUMet provides as easy to use tool for discovering the biological contexts of metabolite peaks with unclear identities.
What are the inputs to PIUMet?
PIUMet can analyze both single-omic or multi-omic inputs. In the single-omic analysis, the inputs consist of only one type of molecular measurement, either untargeted lipidomics or metabolomics, targeted lipidomics or metabolomics, or proteomics. A user can further investigate any combinations of these inputs for multi-omic analysis.
The inputs from these molecular measurements are any metabolite peaks, characterized metabolites, or proteins with significantly different levels between two phenotypic conditions. For targeted metabolomics and lipidomics input, PIUMet accepts the HMDB IDs, while for proteomic inputs, PIUMet accepts gene symbols.
What a node prize means?
A user must assign a prize to each input data point to show the significance of their alterations. For example, the prizes can be considered as –log (P values) of the significance of changes between two phenotypic conditions.
What are PIUMet parameters?
- w: A parameter for tuning the number of trees in the resulting network
- mu: A parameter for tuning the number of input nodes that are included in the output
- beta: A parameter for controlling the bias toward high degree nodes.
- R: A parameter for running PIUMet for R times by adding random noise to the interactome and calculating robustness scores.
What are the output of PIUMet?
For a parameter set of w, beta and mu, PIUMet provides the following results:
- Result_summary: a summary of input files and the resulting network
- output_network.html: an HTML file that shows the visualization of the resulting network (when zooming in, the name of each node and associated robustness score will display)
- Result_union_net: a binary interaction file
- Result_node_frq: Node attribute file, includes information about each node, such as their robustness score
- Result_edge_frq: Edge attribute file, includes information about each edge, such as their robustness score, as well as confidence score from their source database
- peaks_putative_metabolites: information about the peaks in the resulting network, their matched metabolites, the score they are matched to the peak, and more info about the metabolites
- result_AllMatched_Met: include all the matched metabolites to the input metabolite peaks, and additional information about each metabolite