An important fraction of microbial diversity is harbored in strain individuality, so identification of conspecific bacterial strains is imperative for improved understanding of microbial community functions. Limitations in bioinformatics and sequencing technologies have to date precluded strain identification owing to difficulties in phasing short reads to faithfully recover the original strain-level genotypes, which have highly similar sequences.
Offers a platform dedicated to microbiome studies. QIIME is an open-source package intending to encompass all steps of the analysis, from raw data to the interpretation of the results. This software furnishes utilities allowing the combination of heterogeneous experimental datasets, completed by a tracking feature. Additionally, it can be extended by the addition of multiple plug-in for specific tasks such as the manipulation of alignments, quality check or demultiplexing.
Provides various next-generation sequencing (NGS) data analysis applications which are developed or optimized by Illumina, or from a growing ecosystem of third-party app providers. BAseSpace is a cloud platform that can be integrated with the industry’s leading sequencing platforms, without cumbersome or time consuming data transfer steps.
An open-source algorithm that identifies conspecific strains from metagenomic sequence data and reconstructs the phylogeny of these strains in microbial communities. ConStrains uses single-nucleotide polymorphism (SNP) patterns in a set of universal genes to infer within-species structures that represent strains. Applying ConStrains to simulated and host-derived datasets provides insights into microbial community dynamics.
Allows the users to upload raw reads, obtained from different next generation sequencing (NGS) platforms, and get a fast estimation of the pathogenic potential of the bacteria they are studying. This web-server can analyze and identify genomic features associated with both pathogenicity and non-pathogenicity. PathogenFinder could be helpful in situations of possible bacterial outbreaks and follows the direction modern clinical microbiology and global epidemiology are taking driven by the revolution brought by high throughput DNA sequencing technologies.
Uses metagenomic data to achieve strain-level microbial profiling resolution. PanPhlAn recognized outbreak strains, produced the largest strain level population genomic study of human-associated bacteria and, in combination with metatranscriptomics, profiled the transcriptional activity of strains in complex communities. PanPhlAn’s ability for strain-tracking and functional analysis of unknown pathogens makes it an efficient tool for culture-free infectious outbreak epidemiology and microbial population studies.
A Java based application which offers efficient and intuitive reference-independent visualization of metagenomic datasets from single samples for subsequent human-in-the-loop inspection and binning. The method is based on nonlinear dimension reduction of genomic signatures and exploits the superior pattern recognition capabilities of the human eye-brain system for cluster identification and delineation. We demonstrate the general applicability of VizBin for the analysis of metagenomic sequence data by presenting results from two cellulolytic microbial communities and one human-borne microbial consortium. The superior performance of our application compared to other analogous metagenomic visualization and binning methods is also presented.
Delineates strain lineage and antibiotic resistance. PhyResSE is a web-based tool designed to enable nonspecialized users to extract phylogenetic and resistance information from next-generation sequencing (NGS) data. The software enables the automated interpretation of Mycobacterium tuberculosis complex (MTBC) whole-genome sequencing (WGS) data for the identification of resistance-mediating variants and phylogenetic lineage classification. It opens the way for a wider application of WGS in the mycobacteriological laboratory for day-to-day use.