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

Abstract SIGMA2 is a system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes.

Multi-dimensional datasets can be simultaneously visualized and analyzed with respect to each dimension, allowing combinatorial integration of the different assays belonging to the different ‘omics’.

The identification of genes altered at multiple levels such as copy number, loss of heterozygosity (LOH), DNA methylation and the detection of consequential changes in gene expression can be concertedly performed, establishing SIGMA2 as a novel tool to facilitate the high throughput systems biology analysis of cancer.

Look and feel of SIGMA2 --

The novel multi-dimensional omics data analysis software SIGMA2 is built on the framework of a facile visualization tool called SIGMA, which can display alignment of genomic data from a built-in static database.

SIGMA2 provides the following features that are required for integrative analysis:

1) Built-in segmentation for array CGH;

2) Consensus calling using multiple segmentation algorithms;

3) Array platform-independent combined CGH analysis;

4) Custom microarray data handling;

5) Basic copy number and expression integration;

6) Alignment and analysis of genetic and epigenetic data;

7) Multi-dimensional visualization of genetic, epigenetic and gene expression data;

8) Two group statistical comparison;

9) Two group combinatorial gene dosage and gene expression comparison;

10) Linking to external biological databases;

11) Linking to external gene expression (GEO Profiles);

12) Context-based visualization of genome features;

13) Conversion of data between different genome assemblies; and

14) Free for academic/research use.

GEO Profiles - This database stores individual gene expression profiles from curated DataSets in the Gene Expression Omnibus (GEO) repository. You can search for specific profiles of interest based on gene annotation or pre-computed profile characteristics.

Approach to integration between array platforms and assays --

SIGMA2 treats all data in the context of genome position based on the relevant human genome build using the UCSC genome assemblies. An interval-based approach is used to sample across different array platforms and assays and data from each interval are merged together.

Description of user interface --

The main user interface in SIGMA2 utilizes a tabbed window-pane which allows the user to open multiple visualizations simultaneously. The left part of the window manages the analyses and projects which belong to the current user and button shortcuts for the main functionality are spread along the top of the window.

Using the highlighting toolbar button, the user can select a region of interest and subsequently, by clicking the right mouse button, the user can search for annotated genes within the specified genomic coordinates.

Analysis of data from a single assay type --

The first, and most basic, level of analysis is from a single assay type. For array CGH, multiple options for segmentation algorithms are available within the program and results from externally run segmentation can be imported as well.

A unique feature of SIGMA2 is the ability to take a consensus of multiple algorithms using “And” or “Or” logic between algorithms. Moreover, a level of consensus can be specified.

For example, if an experiment is analyzed using five (5) approaches, the user can select areas of gain and loss which were detected by one algorithm, at least three algorithms, all five algorithms, etc.

For LOH, basic analysis using the number of consecutive markers that exhibit LOH is used to determine its status.

Affinity-based approaches for DNA methylation and histone modification states or bead-based percentage of CpG island methylation is analyzed by either direct thresholding or z-transform thresholding.

For any of the different assay types, when examining across a number of samples, a frequency of alteration can be calculated and plotted.

For data from different array platforms, but assaying the same biological measurement, the algorithm for integration is used to derive common data.

This feature is most applicable to DNA copy number data due to the number of array CGH platforms. Similar to the multiple sample analysis of data on the sample platform, a frequency of altered states can be generated and plotted.

Analysis of data from multiple assays in a given omics dimension --

Within a given omics dimension, multiple assay types can be analyzed in combination. For example, it is useful to investigate copy number and LOH and the interplay between DNA methylation and different states of histone modification. Typically, in regions of copy number loss, LOH is also observed.

However, LOH can also occur in regions which are copy number neutral, indicating a change in allelic status which is Not interpretable by one dimension alone. In terms of epigenetics, DNA methylation and states of histone methylation and acetylation have been known to be biologically relevant.

Combinatorial analysis of multiple omics dimensions - gene dosage and gene expression --

The most common analysis of multiple omics dimensions is the influence of the genome on the transcriptome. In SIGMA2, there are multiple functionalities which allow the user to link DNA copy number to gene expression.

For a single group of samples, with matching DNA copy number and gene expression profiles, the user can determine associations through two (2) main options:

1) Using a correlation-based approach, correlating the log ratios with the normalized gene expression intensities; and

2) Using a statistical-based approach comparing the expression in samples with copy number changes against those without copy number change utilizing the Mann Whitney U test.

Spearman, Kendall or Pearson correlation coefficients can also be calculated for option (1). Similarly, this functionality is also available for correlating epigenetic profiles and gene expression.

In addition to single group analysis, two-dimensional genome/transcriptome analysis can be applied to two-group comparison analysis.

Group comparison analysis - single omics dimension --

For two (2) groups of samples, the user can compare the distribution of changes between two groups to determine if the patterns are statistically different using a Fisher’s Exact test.

For DNA copy number, it is the distribution of gain and losses; for DNA methylation or histone modification states, the proportion of samples that meet the threshold of enrichment for each group (low or high); and for LOH, it is the proportion of samples with LOH for a region for each group.

Group comparison analysis - integrating multiple omics dimensions --

This type of analysis can be performed with a single sample or multiple samples, thus allowing combinatorial (“and”) analysis for large datasets. In addition, the user can also identify “or” events, where a change in any of the dimensions can be flagged.

Exporting data and results --

High resolution images can be exported for all types of visualizations in SIGMA2. Histogram plots of gene expression, Heatmaps with clustering of gene expression, karyogram plots and frequency histogram plots are the main types of visualization available.

Frequency histogram data which is used to generate the plots can also be exported. Integrated plots with data plotted serially or overlaid are also available for analysis involving multiple genomic and epigenomic dimensions.

Genes which are obtained from the conjunctive (And) and disjunctive (Or) multi-dimensional analysis can be exported with their status.

Results of statistical analysis such as Fisher’s exact comparisons and U-test comparisons of gene expression can be exported against annotate gene lists based on user-specified human genome builds.

Data from multi-platform integration can be exported based on based pair position for additional external analysis, if necessary.

SIGMA2 documentation --

The manufacturers provide an extensive User Manual.

System Requirements

Contact manufacturer.


Manufacturer Web Site SIGMA2 (flintbox)

Price Contact manufacturer.

G6G Abstract Number 20770

G6G Manufacturer Number 100443