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Identifies non-human nucleic acids that reveal candidate microbes. PathSeq is a highly scalable software tool that provides computational subtraction of high throughput sequencing (HTS) data. This application demonstrates high sensitivity and specificity in its capacity to distinguish between human and non-human sequences using both simulated and experimental transcriptome data and entire genome sequencing data. It is implemented in a cloud computing environment, making it easily accessible to the scientific community.
RDP4 / Recombination Detection Program
Implements an extensive array of methods for detecting and visualizing recombination in, and stripping evidence of recombination from, virus genome sequence alignments. RDP4 can analyze up to 2500 sequences that can reach 10Mb. It is also applicable to the analysis of bacterial full-genome sequence datasets. It uses either fully automated mode from the command line interface or with a graphical user interface that enables detailed exploration of both individual recombination events and overall recombination patterns.
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A web application for exploring metagenomics classification results, with a special focus on infectious disease diagnosis. Pavian allows researchers to analyze, display and transform results from the Kraken and Centrifuge classifiers using interactive tables, heatmaps and flow diagrams. Pavian also provides an alignment viewer for validation of matches to a particular genome. Its functionalities help microbiome researchers as well as clinical microbiologists to gain a better understanding of their data.
IMSA / Integrated Metagenomic Sequence Analysis
Improves accuracy by using a conservative reference database, employing a new counting scheme, and by assembling shotgun reads. IMSA is a protocol for accurate taxonomy classification based on metatranscriptome data of any read length that can efficiently and robustly identify bacteria, fungi, and viruses in the same sample. It addresses the need for taxonomy classification from RNAseq data and also creates an opportunity to revisit old metatranscriptome data, where taxonomic content may be important but was not analyzed.
RINS / Rapid Identification of Non-human Sequences
An intersection-based pathogen detection workflow that utilizes a user-provided custom reference genome set for identification of non-human sequences in deep sequencing datasets. RINS is optimized for mate-paired high-throughput sequencing data with reads at least 36 bp and up to 500 bp, and can be run on sequencing data from any species. Non-paired end sequencing data can also be used, though contig generation and extension will be less robust. In <2 h, RINS correctly identified the known virus in the dataset SRR73726 and is compatible with any computer capable of running the prerequisite alignment and assembly programs. RINS accurately identifies sequencing reads from intact or mutated non-human genomes in a dataset and robustly generates contigs with these non-human sequences.
A computional coreceptor usage prediction model. gCUP is based on our recently developed method T-CUP, but was redeveloped, parallelized and optimized for the use on graphics processing units (GPUs). gCUP and T-CUP give identical predictions and thus the accuracy of the model is not compromised by using GPUs. By harvesting the power of GPUs and optimizing the use of their fast local memory, gCUP can drastically reduce the runtime and process the same 40 million reads in just 4 min using one modern GPU.
VIP / Virus Identification Pipeline
A one-touch computational pipeline for virus identification and discovery from metagenomic NGS data. VIP performs the following steps to achieve its goal: (i) map and filter out background-related reads, (ii) extensive classification of reads on the basis of nucleotide and remote amino acid homology, (iii) multiple k-mer based de novo assembly and phylogenetic analysis to provide evolutionary insight. We validated the feasibility and veracity of this pipeline with sequencing results of various types of clinical samples and public datasets. VIP has also contributed to timely virus diagnosis (~10 min) in acutely ill patients, demonstrating its potential in the performance of unbiased NGS-based clinical studies with demand of short turnaround time.
Uses for mining sequence data to identify sequences of viral origin. VirusSeeker is a set of fully automated and modular software package optimized for analysis of data generated by the Illumina next generation sequencing platform. It can also be applied to data generated by other platforms. It first identifies candidate viral sequences by comparing with virus-only databases and then remove false positive viral sequences by comparing the candidate viral sequences to NCBI NT (nucleotide) and NR (non-redundant protein) databases.
A free and open source set of Galaxy tools and workflows allowing both de novo reconstruction of novel viruses and detection of already identified viral species from sequencing datasets. Using the graphical Galaxy workflow editor, Metavisitor workflows can be adapted to suit specific needs, by adding analysis steps or replacing/modifying existing ones. For instance, Metavisitor may help in field surveillance of insect vectors and emerging viral species during epidemics, in viral metagenomic studies or in experimental research or diagnosis for human patients suffering from viral infections or coinfections. Metavisitor can be used on our Mississippi server, or can be installed on any Galaxy server instance and a pre-configured Metavisitor server image is provided. Metavisitor works with DNA, RNA or small RNA sequencing data over a range of read lengths and can use a combination of de novo and guided approaches to assemble genomes from sequencing reads. We show that the software has the potential for quick diagnosis as well as discovery of viruses from a vast array of organisms.
RAMBO-K / Read Assignment Method Based On K-mers
Allows rapid and sensitive removal of unwanted host sequences from Next Generation Sequencing (NGS) datasets. RAMBO-K shows a consistently high sensitivity and specificity across different datasets. It rapidly and reliably separates reads from different species without data preprocessing. The tool can be run to classify the real reads based on the previously computed Markov chains. The method is not able to reliably estimate the relative abundance of reads from the two organisms and the estimate varies widely between the two k-mer sizes.
Allows to share, communicate, and built collaboration around Next Generation Sequencing (NGS) analytical tools and data. Pathosphere.org allows to evaluate novel detection algorithms and other analytical tools. It allows users to communicate directly with the technical development team through forums and discussion boards. The tool permits to detect pathogens in complex sample backgrounds by offering features that allow to utilize, modify and create pipelines for a variety of NGS technologies.
T-RECs / Tool for RECombinations
Employs pairwise alignment of sliding windows and can perform (i) genotyping, (ii) clustering of new genomes, (iii) detect recent recombination events among different evolutionary lineages, (iv) manual inspection of detected recombination events by similarity plots and (v) annotation of genomic regions. T-RECs is based on the BLASTN heuristic local pairwise alignment method with sliding windows. It rapidly scans hundreds or even thousands of query genomes or even sequence fragments, allows genotyping based on a user-defined sequence database and detects candidate recombination events among members of different evolutionary groups e.g. organisms, genogroups, genotypes etc.
A logistic regression classifier model developed for the Illumina sequencing platforms that uses the quantiles of the quality scores, to distinguish true single nucleotide variants from sequencing errors based on the estimated SNV probability. To train the model, we created a dataset of an in silico mixture of five HIV-1 plasmids. QQ-SNV has the advantage of being extremely computationally efficient in handling “ultradeep” read sets, since SNV calling is reduced to a classification method based on logistic regression.
Predicts viral integrations. BatVI identifies a set of probable chimeric reads using the sensitive BLAST aligner. It can detect viral integrations having very low coverage. For detecting viral integrations, it uses fast clustering and multiple sequence assembly methods. BatVI can either identify the correct integration or report the fact that the integration is unreliable. Finally, it can predict more correct Hepatitis B Virus (HBV) integrations and produce less false positives in the shortest amount of time.
Combines existing well-known and novel RNA-seq tools for not only detection and quantification of viral RNA, but also variants in the viral transcripts. ViGEN includes 4 major modules: the first module allows to align and filter out human RNA sequences; the second module maps and count (remaining un-aligned) reads against reference genomes of all known and sequenced human viruses; the third module quantifies read counts at the individual viral genes level thus allowing for downstream differential expression analysis of viral genes between experimental and controls groups, and the fourth module calls variants in these viruses.
Maps the reads to reference genomes. VirFind is a method specifically developed for virus detection and discovery able to: (i) map and filter out host reads, (ii) deliver files of virus reads with taxonomic information and corresponding Blastn and Blastx reports, and (iii) perform conserved domain search for reads of unknown origin. The pipeline was used to process more than 30 samples resulting in the detection of all viruses known to infect the processed samples, the extension of the genomic sequences of others, and the discovery of several novel viruses.
A software tool for characterizing intra-host viruses through next generation sequencing (NGS) data. It implements our recently developed algorithm, Virus intEgration site detection through Reference SEquence customization (VERSE) as well as other new features. Specifically, VirusFinder 2 detects virus infection, co-infection with multiple viruses, mutations in the virus genomes, in addition to virus integration sites in host genomes. It also facilitates virus discovery by reporting novel contigs, long sequences assembled from short reads that map neither to the host genome nor to the genomes of known viruses. VirusFinder 2 can not only work for the human genome data, but also other organisms with available reference genome sequences (e.g. animals). VirusFinder 2 works with both paired-end and single-end data, unlike the previous 1.x versions that accepted only paired-end reads. The types of NGS data that VirusFinder 2 can deal with include whole genome sequencing (WGS), whole transcriptome sequencing (RNA-Seq), targeted sequencing data such as whole exome sequencing (WES) and ultra-deep amplicon sequencing.
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