DENDRON is designed as an analytical tool for those interested in analyzing DNA fingerprinting gels.

This page will demonstrate some of DENDRON's vast capabilities.

Unwarping

Unwarping a gel is the optional process of straightening the linear distortions in a gel. The following two pictures show a gel before and after the unwarping process.

Detect Lanes

Once a gel is unwarped, the gel's lanes must then be detected. The lane detection step is designed to tell the database which sections and lanes/strains of the current gel image are of interest for analysis. DENDRON uses automatic lane detection, but  also allows the user to control and edit the selection process.  The user may change lane width and/or deselect lanes from analysis. This shows the gel with lanes detected.

Align Lanes

The aligning process is an optional step designed to take out any internal, horizontal distortions in the gel. It also helps to align the standard and conserved bands, resulting in easier linking and band matching, later. The following two images follows the procedure of aligning the bands of the second lane.

The bands of the second lane are aligned too low.

The second lane is now horizontally aligned.

Detect Bands

DENDRON automatically finds bands and assigns class values based on relative areas and intensities. As in all steps, DENDRON gives the user complete control over automatic functions and allows the user to add or subtract bands from the analysis as needed. This image shows the bands detected and bracketed in red.

Display and Edit Classes and Gel

The Display and Edit Classes option is designed to allow the user to make changes in the original information assigned to the gel during the Detect lanes and Detect bands steps. The display and edit steps provide for making changes in lane/strain names, the assignment of molecular weights to bands in each lane, and changes in band class/relative intensity values. This image shows the classes displayed for editing.

Calibrate to Global Standard

One of the major strengths of DENDRON resides in the capacity it offers the user for comparing large numbers of isolates. In large epidemiological studies, different gels must be compared. DENDRON normalizes all gels within any study against a global standard, making comparison between gels possible both visually and analytically. This figure shows a reference standard being normalized against the global standard.

Link Bands

The Link Bands step automatically matches the bands across the gel which DENDRON finds to be of the same molecular weight or relative position. As in previous steps, the user is given the full ability to edit and modify the links automatically determined by the system. This image shows a gel with its bands linked.

Write Bands to Data File

DENDRON creates an editable text map showing band positions, or molecular weights, and relative areas and/or intensities for each band. It is these text maps which DENDRON uses when calculating similarities and generating dendrograms. The gel name, strain/lane names, molecular weights, and relative class intensities are all included in the data file. These files are also exportable for use in other programs.

Computer Generated Gels

When comparing multiple strains and gels visually, it is often easier to make the comparisons with all of the noise and background subtracted. Computer Generated Gels provide normalized band position information and removes any other information which may make it difficult for visual comparisons.  These images may be made up of lanes from multiple gels used when making dendrograms.

Make Dendrogram

DENDRON computes similarity coefficients between every possible pair of strains in a gel, and for all possible pairs between gels, using any of multiple optional similarity coefficient formulas. New strains can be compared with strains analyzed years previously as long as the standards were contained within the gel for normalization. Dendrograms are created using these similarity coefficients and demonstrate clustering for genetically similar strains and to separate unrelated groups of strains. Any subset of strains in a study may be compared in a dendrogram or mixed with any other subset in a dendrogram. The following four images display single gel dendrograms, single gel dendrograms showing normalized gel lanes, single gel dendrograms showing computer generated gel model lanes, and an 11 gel dendrogram.

Neighbor Lanes

Neighboring allows the user to compare lanes from different gels or nonsequential lanes of the same gel by positioning lanes in a desired sequence. Neighboring can be used with normalized lanes so that visual comparison is possible. Neighbored lanes retain all of the band position and intensity data from previous steps, so analysis and dendrogram generation can be made from neighbored gels. After selecting the lanes of interest, DENDRON saves the lanes as a new gel and allows the user to analyze it as such.

Phenotypic Database Searches

DENDRON also includes a user-definable database for comparing strains based on any user selected, phenotypic, characteristics. Once strains have been analyzed, up to 10 additional fields of information may be defined and entered for each strain. Once completed, the database may be searched based on any of the characteristics or combinations thereof, the lane images automatically neighbored, and dendrograms created.

DENDRON® allows you to:

• Store and analyze a limitless number of gel images;
  

• Image process individual lanes to compensate for over or under loading;
  
• Image process the entire gel or portions of the gel for background;
  
• Analyze warped or distorted gel images by removing all geometric distortions i.e., smiles, frowns, other linear and non-linear distortions;
  
• Densitometrically scan the entire width of each lane for band intensities and positions;
  
• Automatically identify lanes and bands, and assign intensity classes and molecular weights to bands;
  
• Automatically subtract gel backgrounds in order to accurately assign intensity values to bands;
  
• Identify unique bands in different lanes;
  
• Normalize gel images nonlinearly to general standards to compare patterns on different gels;
  
• Compute similarity coefficients between every pair of lanes of interest on the same or different gels;
  
• Select from five formulas for calculating similarity coefficients;
  
• Generate matrices of similarity coefficients between every pair of up to 5000 patterns in a single grouping;
  
• Identify similar or identical strains in the same or different gels;
  
• Create dendrograms based upon similarity coefficients between any or all patterns in the same or different gels;
  
• Generate gel models;
  
• Display gel patterns horizontally next to their respective positions in a dendrogram;
  
• Test dendrogram stability mathematically;
  
• Normalize and neighbor any two or more lanes from the same or different gels for visual comparison;
  
• Create a database for cross-referencing and pattern selection from different gels based upon genotypic characteristics, phenotypic characteristics or patient characteristics;
  
• Export information to standard spreadsheet programs;
  
• Utilize additional features too numerous to describe here.