AutoSeqMan: batch assembly of contigs for Sanger sequences

Area of Science:

• Bioinformatics
• Genomics
• Computational Biology

Background:

• Sanger sequencing remains a key DNA sequencing technology, generating large volumes of sequence data.
• SeqMan software facilitates Sanger sequence assembly into contigs but requires extensive manual operations for large datasets.
• Increasing data complexity necessitates more efficient assembly methods to handle larger sample sets and more sequenced loci.

Purpose of the Study:

• To introduce autoSeqMan, a novel software program designed to automate the assembly of Sanger sequences using SeqMan's scripting capabilities.
• To provide a solution for researchers dealing with large-scale Sanger sequencing data who wish to simplify the contig assembly process.
• To reduce the time and manual effort required for preprocessing and assembling Sanger sequences.

Main Methods:

• Developed autoSeqMan software with two primary modules: 'Classification' for preprocessing and 'Assembly' for automated contig generation.
• Utilized SeqMan's scripting language to enable automated execution of assembly tasks.
• Compared the performance of autoSeqMan against manual operation for Sanger sequence assembly.

Main Results:

• AutoSeqMan successfully automates the contig assembly process for Sanger sequences.
• The software demonstrated substantial time savings in both the preprocessing and assembly stages compared to manual methods.
• The 'Classification' and 'Assembly' modules effectively manage data preprocessing and script generation for sequential assembly.

Conclusions:

• AutoSeqMan offers a significant improvement in efficiency for assembling large sets of Sanger sequences.
• The tool is particularly beneficial for researchers with large sample sizes and limited programming expertise.
• AutoSeqMan provides a valuable, automated solution to streamline bioinformatics workflows in genomics research.