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Transposon insertion sequencing data analysis software tools

We use the term Tn-seq to refer to a range of transposon insertion sequencing techniques that use a random transposon mutant library and high-throughput sequencing to study fitness of mutant strains and/or to identify genes that are essential or advantageous for growth under a specific set of conditions. Thanks to the novel advances in deep sequencing technologies, this technique has become useful for understanding gene function and the genetics behind microbial physiology. (Gawronski et al., 2009; Sarmiento et al., 2013; van Opijnen et al., 2009; van Opijnen and Camilli, 2013; Gallagher et al., 2011; Fu et al., 2013). Source text: Solaimanpour et al., 2015.

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Contains a set of tools to analyse the output from TraDIS analyses. Bio-Tradis provides functionality to (i) detect TraDIS tags in a BAM file, (ii) add the tags to the reads, (iii) filter reads in a FastQ file containing a user defined tag, (iv) remove tags, (v) map to a reference genome and (vi) create an insertion site plot file available as standalone scripts or as perl modules. Bio-Tradis is implemented as an extensible Perl library which can either be used as is, or as a basis for the development of more advanced analysis tools.
GeIST / Genomic Integration Site Tracker
A command-line pipeline designed to map integration sites. GeIST bridges the gap between raw sequence data and identifying genomic DNA integration sites in multiple samples or parsing independent events in a single sample. GeIST is suited to identify multiple types of integrations. GeIST accepts a BAM or FASTQ file of paired-end LM-PCR sequences and a file indicating the association between samples and barcodes. The software returns a BAM file of the sequences at each integration junction, a Browser Extensible Data (BED) file for easy visualization of the integration patterns, and a summary of how often each barcode was detected.
MAGenTA / Microbial Assessment by Genome-wide Tn-Seq Analysis
Represents a suite of analysis tools concerning the calculation of the development rate for disrupted gene in the genome. MAGenTA is a complete Tn-Seq analysis pipeline implemented in Galaxy, but also available as separate scripts. It makes sensitive genome wide fitness, analysis available for most transposon and Tn-Seq associated approaches. It also contains fitness calculations (growth rate), bottleneck corrections and calculations, or again statistical comparisons of conditions.
An accessible transposon-insertion sequencing (TIS) analysis pipeline for identifying essential regions that are required for growth under optimal conditions as well as conditionally essential loci that participate in survival only under specific conditions. ARTIST uses simulation-based normalization to model and compensate for experimental noise, and thereby enhances the statistical power in conditional TIS analyses. ARTIST also employs a novel adaptation of the hidden Markov model to generate statistically robust, high-resolution, annotation-independent maps of fitness-linked loci across the entire genome.
INSPIIRED / INtegration Site PIpeline for pairedend REaDs
Allows to work about viral integration sites and the longitudinal outcomes of gene therapy patients. INSPIIRED serves for quantitative analysis of integration site distributions. This is a biochemical method for integration site isolation, which achieves the critical criteria of suppressing PCR contamination between samples while sampling randomly from the pool of integrated DNAs. This tool accommodates analysis of integration in both single-copy and repeated sequences.
VISITs / Vector Integration Sites Identification from PhiT-seq
Allows analysis of Phenotypic interrogation followed by Tag sequencing (PhiT-seq) data. VISITs is a pipeline divided into several modules: pre-processing, quality control (QC), data diagnosis, statistical analysis and visualization. Its usage was illustrated on two positives selection screens (identification of survival genes after selection). The software enables handling of biological variance as well as more complicated experiment design by using existing frameworks developed for other next-generation sequencing (NGS) data analysis.
HaSAPPy / Haploid Screening Analysis Package in Python
Assists users in computational candidate identification. HaSAPPy analyses next generation sequencing (NGS) datasets to reconstruct viral insertions in control and selected cell pools. It also estimates the enrichment of disruptive mutations and the ratio of disruptive over neutral mutations for each gene. This method allows the analysis of multiple experiments against a single control, whereby each dataset can contain multiple replicates.
Tn-seq explorer
A convenient and easy-to-use package of tools for exploration of the Tn-seq data. In a typical application, the user will have obtained a collection of sequence reads adjacent to transposon insertions in a reference genome. The reads are first aligned to the reference genome using one of the tools available for this task. Tn-seq Explorer reads the alignment and the gene annotation, and provides the user with a set of tools to investigate the data and identify possibly essential or advantageous genes as those that contain significantly low counts of transposon insertions.
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