Software

Root Phenotyping Suite

RootTip, RTipC, PBRCThe Image Analysis Suite for Root Phenotyping presented here contains three different software tools for phenotyping plant root images; RootAnalyzer, RTipC and RootGraph.

It is available to download at the sourceforge http://sourceforge.net/projects/rootphenotypingsuite/.

RootAnalyzer is a fully automated tool, for efficiently extracting and analyzing anatomical traits from root-cross section images. Using a range of image processing techniques such as local thresholding and nearest neighbor identification, RootAnalyzer segments the plant root from the image's background, classifies and characterizes the cortex, stele, endodermis and metaxylem, and subsequently produces statistics about the morphological properties of the root cells and tissues.

RTipC is a system for the fully automated detection and classification of root tips in root images obtained either by 2d flat bed scanning or by 3D digital camera imaging. The software provides a robust, efficient and accurate means of phenotyping of roots, by detecting individual root tips and classifying them as belonging to a primary or lateral root.

RootGraph is a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root.


Experimental Design and Analysis

Over the course of a few years the Biometrics Group of the PBRC have developed a number of R-based codes related to the design of high throughput plant experiments. These are available through CRAN (note that they are not standalone pieces of software) via the following links.

dae: https://cran.r-project.org/package=dae

imageData: https://cran.r-project.org/package=imageData

asremlPlus: https://cran.r-project.org/package=asremlPlus


RootAnalyzer

Root Analyzer, PBRC
RootAnalyzer, developed at the PBRC, is a fully automated tool for efficiently extracting and analyzing anatomical traits from root cross section images. Using a range of image processing techniques such as local thresholding and nearest neighbor identification, RootAnalyzer segments the plant root from the image's background, classifies and characterizes the cortex, stele, endodermis and metaxylem, and subsequently produces statistics about the morphological properties of the root cells and tissues.

RootAnalyzer is available to download at http://sourceforge.net/projects/rootanalyzer/


RootGraph

RootGraph, PBRC
RootGraph: The software tool represents a numerical scheme for accurate, detailed and high-throughput analysis of scanned images of plant roots. The tool is a fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. The program associates lateral roots and their properties with the specific primary root from which the laterals emerge. The program’s performance has compared favourably against results based on manual measurements.

RootGraph is available to download at http://www.plant-image-analysis.org/software/rootgraph


Cell Mobility

Cell Mobility is a program to simulate the dynamics of charged particles moving under an oscillating electric field. It calculates the

  • dynamic mobility
  • electrical conductivity, and
  • permitivity

of concentrated charged colloidal systems.

For more information and to purchase this software please contact Professor Stan Miklavcic


Sequencing error correction without a reference genome

This code provides a method for sequencing error correction for Illumina next generation sequencing data sets, when a reference genome is not available. It is available for download at http://ep.unisa.edu.au/view/view.php?id=46870.

This work is described in the paper:

Julie A Sleep, Andreas W Schreiber and Ute Baumann, Sequencing error correction without a reference genome, BMC Bioinformatics, 14:367, 2013.

This paper was a BMC Bioinformatics Highly Accessed article with over 11,500 accesses and 2,000+ software page visits.

Please contact Ms Julie Sleep for more information. Sequencing Error Correction, PBRC

Areas of study and research

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