bioinformatics.uconn.edu - This tutorial will serve as an example of how to use free and open-source genome assembly and secondary scaffolding tools to generate high quality assemblies of bacterial sequence data. The bacterial sample used in this tutorial will be...
www.ncbi.nlm.nih.gov - NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).
Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional...
academic.oup.com - GMcloser uses likelihood-based classifiers calculated from the alignment statistics between scaffolds, contigs and paired-end reads to correctly assign contigs or long reads to gap regions of scaffolds, thereby achieving accurate and efficient gap...
ufmg-simba.sourceforge.net - SIMBA, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS)...
ucdavis-bioinformatics-training.github.io - Our team offers custom bioinformatics services to academic and private organizations. We have a strong academic background with a focus on cutting edge, open source software. We replicate standard analysis pipelines (best practices) when...
github.com - Just import the assembly, bam and ALE scores. You can convert the .ale file to a set of .wig files with ale2wiggle.py and IGV can read those directly. Depending on your genome size you may want to convert the .wig files to the BigWig format.
samstat.sourceforge.net - SAMStat is an efficient C program to quickly display statistics of large sequence files from next generation sequencing projects. When applied to SAM/BAM files all statistics are reported for unmapped, poorly and accurately mapped reads...
github.com - Key features
Filters SNVs from any variant caller to remove false positives
Calculates metrics based on BAM files and provides filtering not possible with other tools
Fully user-configurable filtering (including which filters to use and their...
talks.biogo.googlecode.com - Another good lecture for Illumina sequencing data analysis from
Dan Kortschak, Bioinformatics Group, School of Molecular and Biomedical Science ,The University of Adelaide
journals.plos.org - Illumina Sequencing data can provide high coverage of a genome by relatively short (most often 100 bp to 150 bp) reads at a low cost. Even with low (advertised 1%) error rate, 100 × coverage Illumina data on average has an error in some read...