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Get started with MMiRNA-Viewer 2

OVERVIEW

MMiRNA-Viewer2 is a bioinformatics tool for identifying mRNA and miRNA interacting clusters and visualize the functional annotation of miRNA-mRNA pairs in a network. This tool provides sample input files of difference cancer type data extracted from The Cancer Genome Atlas (TCGA). Moreover, the user can upload their own data files to identify significant cluster of miRNA and mRNA interactions through the tool web site.

INPUT FILES

At the top of the page there is a button for selecting an input data set, this will take you to a file explorer view where you can select a single file for upload. The following is the format for the input data set. The file should be a text file with tab seperated values. The tools section includes a link to a conversion tool for most miRNA naming conventions.

For example:

DATA GRAPH

This graph is an interactive representation of the clusters of miRNA and mRNA interactions, individual nodes can be selected and moved using the mouse.

FEATURES

Moving the graph:

Drag any node on the graph by clicking and holding down your mouse. Right click to anchor a node to a new area of the graph. Zoom using your mouse's scroll wheel.

Node information:

Each node is sized depending on their expression values (the larger the node, the larger the expression). Circular nodes are microRNA and square nodes are mRNA/gene. Left clicking on a node will display the given information, left clicking on a second adjacent node will display the information about their relationship. Two lines are displayed between each node, the red represents the tumor connection and the green represents the normal connection. The lighter colored lines represent more database predictions and the size of the line represents the strength of correlations between each nodes (all of this is explained in the legend on the bottom right of the screen).

Center on Node:

This feature allows you to search the graph for a specific mRNA or miRNA, if found the view will center on that node.

FILTER OPTIONS:

In the upper left corner of the screen is the filter options for the present graph. The selection of a filter will change the graph temporarily. Once you choose your filters use the remove Nodes button to get rid of non selected nodes. If you need to retrieve the removed data, the reset graph button will restore all nodes to the graph.

Node:

Filter to show only mRNA or only miRNA

Abs Fold Change:

Filter by the absolute value of the fold change of the nodes.

Connections:

Filters by number of connections made by a single node.

Database:

Filter by the number of database predictions.

Corr Norm Exp/Corr Tumor Exp:

Filter based on the correlation of either the tumor (experimental) or the normal (control) data.

Show labels:

Show the geneIDs or the names of the miRNA names of all nodes currently displayed.

Multiple Filters:

Multiple filters can be applied at the same time.

INTEGRATED BIOLOGICAL DATABASE:

microRNA DATABASE:

Circular nodes are microRNA. Right clicking on a microRNA node will display a list of microRNA databases. Selecting a particular microRNA database will display information related to the microRNA present in the database.

HMDD (The Human microRNA Disease Database):

The Human microRNA Disease Database (HMDD), (Li, Yang et al, 2013, http://www.cuilab.cn/hmdd) is a database that curated experiment-supported evidence for human microRNA (miRNA) and disease associations. miRNAs are one class of important regulatory RNAs, which mainly repress gene express at the post-transcriptional level. Increasing reports have shown that miRNAs play important roles in various critical biological processes.

HMDD Genetics:

HMDD Epigenetics:

HMDD Target:

SomamiR (Somatic mutations in microRNA):

SomamiR, (Bhattacharya, Anindya, and Yan Cui, 2016, http://compbio.uthsc.edu/SomamiR/home.php) is a database of cancer somatic mutations in microRNAs (miRNA) and their target sites that potentially alter the interactions between miRNAs and competing endogenous RNAs (ceRNA) including mRNAs, circular RNAs (circRNA) and long noncoding RNAs (lncRNA).

miRBase (Database of published miRNA sequences and annotation):

The miRBase, (Kozomara, Ana, and Sam Griffiths-Jones, 2014, http://www.mirbase.org/) is a database of published miRNA sequences and annotation. Each entry in the miRBase Sequence database represents a predicted hairpin portion of a miRNA transcript (termed mir in the database), with information on the location and sequence of the mature miRNA sequence (termed miR). Both hairpin and mature sequences are available for searching and browsing, and entries can also be retrieved by name, keyword, references and annotation.

KEGG (Kyoto Encyclopedia of Genes and Genomes):

KEGG, (Kanehisa, Minoru, and Susumu Goto, 2000, http://www.genome.ad.jp/kegg/) is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies.

mRNA DATABASE:

Square nodes are mRNA/gene. Right clicking on a gene node will display a list of gene databases. Selecting a particular gene database will display information related to the gene present in the database.

DAVID (Database for Annotation, Visualization and Integrated Discovery):

The Database for Annotation, Visualization and Integrated Discovery (DAVID), (Huang Da Wei et al, 2009; Huang Da Wei et al, 2009, https://david.ncifcrf.gov/) v6.8 comprises a full Knowledgebase update to the sixth version of our original web-accessible programs. DAVID now provides a comprehensive set of functional annotation tools for investigators to understand biological meaning behind large list of genes.

COSMIC (Catalogue Of Somatic Mutations In Cancer):

The Catalogue Of Somatic Mutations In Cancer (COSMIC), (Forbes, Simon A. et al 2017, http://cancer.sanger.ac.uk/cosmic) is the Catalogue Of Somatic Mutations In Cancer and it is the world's largest and most comprehensive resource for exploring the impact of somatic mutations in human cancer.

Cancer Gene Census

Resistance Mutations

Target Screens Mutant Export

CANCERTOPE

Cancetope, (Gupta, Sudheer et al. 2017, http://crdd.osdd.net/raghava/cancertope/) is a Platform for Designing Genome-Based Personalized Immunotherapy or Vaccine against Cancer. [NOTE: Cancertope information appears in a new browser window.]

KEGG (Kyoto Encyclopedia of Genes and Genomes):

KEGG, (Kanehisa, Minoru, and Susumu Goto, 2000, http://www.genome.ad.jp/kegg/) is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies.

REFERENCES:

Li Y, Qiu C, Tu J, et al. HMDD v2.0: a database for experimentally supported human microRNA and disease associations. Nucleic Acids Research. 2014;42(Database issue):D1070-D1074. doi:10.1093/nar/gkt1023.

Bhattacharya A, Cui Y. SomamiR 2.0: a database of cancer somatic mutations altering microRNA–ceRNA interactions. Nucleic Acids Research. 2016;44(Database issue):D1005-D1010. doi:10.1093/nar/gkv1220.

Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Research. 2014;42(Database issue):D68-D73. doi:10.1093/nar/gkt1181.

Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research. 2000;28(1):27-30.

Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Protoc. 2009;4(1):44-57.

Huang DW, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009;37(1):1-13.

Forbes SA, Beare D, Boutselakis H, et al. COSMIC: somatic cancer genetics at high-resolution. Nucleic Acids Research. 2017;45(Database issue):D777-D783. doi:10.1093/nar/gkw1121.

Gupta S, Chaudhary K, Dhanda SK, et al. A Platform for Designing Genome-Based Personalized Immunotherapy or Vaccine against Cancer. Schönbach C, ed. PLoS ONE. 2016;11(11):e0166372. doi:10.1371/journal.pone.0166372.

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