As the sheer volume of bioinformatic sequence data increases, the only way to take advantage of this content is to more completely automate robust analysis workflows. Analysis bottlenecks are often mundane and overlooked processing steps. Idiosyncrasies in reading and/or writing bioinformatics file formats can halt or impair analysis workflows by interfering with the transfer of data from one informatics tools to another. Fasta-O-Matic automates handling of common but minor format issues that otherwise may halt pipelines. The need for automation must be balanced by the need for manual confirmation that any formatting error is actually minor rather than indicative of a corrupt data file. To that end Fasta-O-Matic reports any issues detected to the user with optionally color coded and quiet or verbose logs. Fasta-O-Matic can be used as a general pre-processing tool in bioinformatics workflows (e.g. to automatically wrap FASTA files so that they can be read by BioPerl). It was also developed as a sanity check for bioinformatic core facilities that tend to repeat common analysis steps on FASTA files received from disparate sources. Fasta-O-Matic can be set with format requirements specific to downstream tools as a first step in a larger analysis workflow. Fasta-O-Matic is available free of charge to academic and non-profit institutions at https://github.com/i5K-KINBRE-script-share/read-cleaning-format-conversion/tree/master/KSU_bioinfo_lab/fasta-o-matic.
BACKGROUND: Genome assembly remains an unsolved problem. Assembly projects face a range of hurdles that confound assembly. Thus a variety of tools and approaches are needed to improve draft genomes. RESULTS: We used a custom assembly workflow to optimize consensus genome map assembly, resulting in an assembly equal to the estimated length of the _Tribolium castaneum_ genome and with an N50 of more than 1 Mb. We used this map for super scaffolding the _T. castaneum_ sequence assembly, more than tripling its N50 with the program Stitch. CONCLUSIONS: In this article we present software that leverages consensus genome maps assembled from extremely long single molecule maps to increase the contiguity of sequence assemblies. We report the results of applying these tools to validate and improve a 7x Sanger draft of the _T. castaneum_ genome. KEYWORDS: Genome map; BioNano; Genome scaffolding; Genome validation; Genome finishing