A new algorithm for band detection and pattern extraction on pulsed-field gel electrophoresis images
Author and article information
Abstract
This paper presents a new approach for band detection and pattern recognition for molecule types. Although a few studies have examined band detection, but there is still no automatic method that can perform well despite the high noise. The band detection algorithm was designed in two parts, including band location and lane pattern recognition. In order to improve band detection and remove undesirable bands, the shape and light intensity of the bands were used as features. One-hundred lane images were selected for the training stage and 350 lane images for the testing stage to evaluate the proposed algorithm in a random fashion. All the images were prepared using PFGE BIORAD at the Microbiology Laboratory of Kermanshah University of Medical Sciences. An adaptive median filter with a filter size of 5x5 was selected as the optimal filter for removing noise. The results showed that the proposed algorithm has a 98.45% accuracy and is associated with less errors compared to other methods. The proposed algorithm has a good accuracy for band detection in pulsed-field gel electrophoresis images. Considering the shape of the peaks caused by the bands in the vertical projection profile of the signal, this method can reduce band detection errors. To improve accuracy, we recommend that the designed algorithm be examined for other types of molecules as well.
Cite this as
2019. A new algorithm for band detection and pattern extraction on pulsed-field gel electrophoresis images. PeerJ Preprints 7:e27771v1 https://doi.org/10.7287/peerj.preprints.27771v1Author comment
This is a submission to PeerJ Computer Science for review.
Sections
Supplemental Information
A Matlab script to detect bands from each of lanes which was tracked
unction to remove undesirable peaks which was detected using "peakfind" function
Matlab script for automatically lane tracking on Pulsed-Field Gel Electrophoresis images
Function to create curve fitted on lane which was tracked using "lane_traking" script
The main matlab script to track lanes and to detect bands on Pulsed-Field Gel Electrophoresis images
Funtion to calculate width of lanes for optimal lane tracking
Function to remove undesirable peaks which was detected by "peakfind" function
A sample Pulsed-Field Gel Electrophoresis image provided by PFGE BIORAD model
A video to show running the main matlab script
Additional Information
Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Mohammad Rezaei conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables, performed the computation work, authored or reviewed drafts of the paper, approved the final draft, mr Mohammad Rezaei Pre analyzed data.
Naser Zohorian conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, performed the computation work, authored or reviewed drafts of the paper, approved the final draft.
Nemat Soltani conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, performed the computation work, authored or reviewed drafts of the paper, approved the final draft.
Parviz Mohajeri conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.
Data Deposition
The following information was supplied regarding data availability:
Data is available at Mendeley Data, DOI:10.17632/mcnfncf25t.1
Funding
This work was supported by Research Council of Kermanshah University of Medical Sciences (Grant Number: 93246). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
