BOL

sourceforge.net - PBJelly - the genome upgrading tool. PBHoney - the structural variation discovery tool Both are contained within the PBSuite code found in downloads.----- PBJelly -----Read The...

github.com - This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in: Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomesMads...

ritchielab.psu.edu - With PhenoGram researchers can create chomosomal ideograms annotated with lines in color at specific base-pair locations, or colored base-pair to base-pair regions, with or without other annotation. PhenoGram allows for annotation of chromosomal...

github.com - SequenceServer lets you rapidly set up a BLAST+ server with an intuitive user interface for use locally or over the web. More at http://sequenceserver.com.

github.com - DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies Our work is published in Scientific Reports: Ye, C. et al. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous...

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.sequenceontology.org - We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers...

github.com - SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large...

the sequenced reads can be mapped to the organism’s genes to assess how differently the genes are expressed under the experimental circumstances as opposed to the control scenario. This is known as differential expression (DE) analysis

Bioinformatics Resources !