Category Genomics>Gene Expression Analysis/Profiling/Tools and Genomics>Genetic Data Analysis/Tools

Abstract Genatomy is a visualizing tool for biological data, such as gene expression, genotypes, growth curves, copy number variation (CNV) and more.

It can be used to analyze the data mathematically and to study the biological aspects of the data and the results.

Genatomy is a tool, aimed to meet the requirements of ‘system biologists’.

Currently, Genatomy does Not contain algorithms to create regulatory programs, but it does contain views and tests to change and check results, as well as special functions and features that handle results in various formats.

Unlike other visualization tools, Genatomy “understands” biology, and does Not handle data simply as Strings or numbers. It knows what a gene is and what the difference is between organisms. It connects with ‘online databases’ and helps the user understand the biology behind the numbers.

The manufacturer's vision was to create a tool which incorporates many of the functions that are usually run to test and change algorithm results and performed in computational programs, such as MATLAB and R.

From the manufacturer’s experience, these changes are essential in order to understand and create better algorithms. Many of them are Not used due to difficulties in connecting tools such as a visualizer and algorithms with raw data, algorithm results and biological resources.

The manufacturer's development team maintains a database (DB) for several species that contains full genome information, Gene Ontology (GO) categories, gene sets, and more.

It can also perform many tasks widely used by Bioinformaticians, such as gene sets enrichments; clustering, GSEA - (see G6G Abstract Number 20266) and SAM - (see G6G Abstract Number 20066).

Genatomy Genome Information --

Genatomy can load and use information about genes, including unique gene ID, symbol name and genome location. Moreover, Genatomy handles genome data from different organisms differently.

For example, right clicking on a gene name will give you specific options such as opening the gene's ‘data page’ in the main website of that organism.

Genatomy can load that information from different ‘files types’:

Genatomy Repository and Local files --

Dana Pe'er's lab manages a file repository containing full genome information files for several organisms. Whenever you are connected to the internet, you will be able to download those files to your computer and use them.

Genatomy Attributes --

Genatomy can load and manage attributes both for the rows (genes most of the time) and for the columns (samples or experiments). It can load more than one table of attributes, and load non-binary attributes.

Note: The most commonly used source of attributes is Gene Ontology (GO), in which each gene is annotated with its functions in the cell.

Genatomy Filters --

“Filters” is a way to filter out data and view only part of it (both on the gene and samples axis of the visualized data). Each filter contains ‘modules’, where each module describes a set of genes and samples that you want to display.

A module can also contain ‘regulatory information’ (such as a module network or linear regression), and also specifies the order of genes and samples.

By Attributes Filter - The simplest type of filters creates modules from an ‘attributes table’, where each module is an attribute, and contains all genes (or samples) with a value greater than 0 for that attribute (which means that it is annotated in binary data).

Module Networks - Another type of filter is the Module Network filter. A module network module contains a set of genes (or other features) and samples, governed by a regulation tree.

Linear Regression (and non-linear interactions) - Another type of modules is linear regression modules. These are sets of genes (or features) and samples, governed by a set of ‘regulators’ creating a linear dependency between them and the features.

Note: As in every filter file, this file is also in XML format, and the modules can be created in any program outside of Genatomy.

An important feature for all modules with regulatory information containing gene-markers is the genomic information added to genes in the module.

Simple Sets - Another type of filter is the simple sets filter, in which the module is only a set of features and samples, without a ‘regulatory program’. A simple set module allows you to perform actions on both axes (features and samples) such as clustering.

Clustering --

Genatomy can perform a hierarchical clustering on both axes, using several functions. You can perform clustering on all the data from the main data file, only on the selected module, or on all modules from a specific filter file.

You can also choose the method to use for the clustering - currently available functions are: Pearson, Absolute Pearson and Euclidean distance.

Filters and Attributes options --

Hyper Geometric Enrichment - Genatomy can calculate hypergeometric enrichment in both axes. There are two ways of viewing the p-values. The first is a table with p-values for all modules vs. all attributes (gene sets).

The other is on-the-fly p-values, which are calculated after every change to modules and presented as red squares next to the attribute names.

Module Editor - Genatomy helps you make many changes to modules, and understand which genes should be in the module, and which genes should Not be in the module.

Module Overview - Genatomy helps you review and understand algorithm results. The module overview window brings you a summary of the module by collecting data from all Genatomy's resources, and creates a ‘virtual path’ between the modules loaded to Genatomy.

Gene Lookup - Another option for reviewing results is the gene lookup window. The window lists all genes, samples and regulators in the project, and for each one it lists all modules that the feature is involved in - both as gene or sample in a module, and as a regulator.

Gene Interactions - Gene-interactions is one of the most useful features in Genatomy. Dana Pe'er's lab manages a gene interaction DB for each organism, incorporating public databases (as stated above...). Genatomy can query this DB and create a ‘network of interactions’, in which each node is a gene.

To display this network the manufacturer uses Cytoscape - (see G6G Abstract Number 20092).

Bird’s Eye view - Another simple and yet useful feature is Bird’s Eye View. This window displays all ‘modules’ of a selected filter sequentially, allowing you to see an overview of the modules.

GLSA - Genome Location Set Analysis - GLSA is an on-going/working algorithm, an expansion of GSEA (Subramanian, Tamayo et al. 2005).

It searches inside modules for several genes in a small genomic region. The algorithm scores the ‘genomic distribution’ of a module's genes, one score for each chromosome, and performs a permutation test to identify statistically significant regions.

Genatomy Documentation --

The manufacturer provides an extensive well documented User Manual and Tutorial, both in PDF format.

System Requirements

Genatomy is a Java program, so it can run on virtually any operating system. It has been tested on Mac OS, Windows and Linux, with Java versions 1.5 and 1.6 or above. Genatomy is Not compatible with older Java releases.


Manufacturer Web Site Genatomy

Price Contact manufacturer.

G6G Abstract Number 20603

G6G Manufacturer Number 104203