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.
Identifies conditionally essential genes. TnSeq is a zero-inflated Poisson (ZIP) model to deal with the excess of zeros for the analysis of transposon insertion sequencing (Tn-seq) data at the level of locations. The software uses high-throughput sequencing (HTS) data from transposon mutant libraries. TnseqDiff, a parametric method to identify conditionally essential genes based on insertion-level data is implemented in the package.
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.
Allows users to find clumps and estimate false discovery rates (FDRs). geneRxCluster identifies differential clustering of genomic sites. This tool supplies several functions to explore genomic insertion sites based on two different gene therapy vectors. A scan stastistic permits users to discover spatial differences in clustering and calculation of FDRs.
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.
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.
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.
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.
A tool for analyzing Himar1 TnSeq data. TRANSIT provides a graphical interface to three different statistical methods for analyzing TnSeq data. These methods cover a variety of approaches capable of identifying essential genes in individual datasets as well as comparative analysis between conditions.
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.
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.
A software tool for researchers in the genomics field utilizing transposon insertion sequencing analysis. ESSENTIALS accurately predicts (conditionally) essential genes and offers the flexibility of using different sample normalization methods, genomic location bias correction, data preprocessing steps, appropriate statistical tests and various visualizations to examine the results, while requiring only a minimum of input and hands-on work from the researcher.
A method for analyzing sequence data from transposon mutant libraries using a Hidden Markov Model (HMM), along with formulas to adapt the parameters of the model to different datasets for robustness. Tn-HMM allows for the clustering of insertion sites into distinct regions of essentiality across the entire genome in a statistically rigorous manner, while also allowing for the detection of growth-defect and growth-advantage regions.
Assists users in analyzing DNA clones. TnClone is a high-throughput platform that utilizes a GUI to offer a platform for general biologists. By clicking and scrolling, users can analyze sequences from scratch without processing the intermediate files from raw data individually. This application includes four major modules: sorting, trimming, assembly, and downstream analysis.
Custom scripts for analyzing (parsing, mapping, and tallying) Tn-seq reads and determining differentially abundant transposon insertion mutants. The scripts contained herein can be used to automatically analyze high-throughput sequencing reads derived from transposon-genome junctions. First, each individual dataset is analyzed with TnSeq.sh or TnSeq2.sh, and then a control and test condition and their specified data files are compared with TnSeqAnalysis.sh.
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.
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