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TraFiC / Transposon Finder in Cancer
Uses paired-end sequencing data for the detection of somatic insertions of transposable elements (TEs) and exogenous viruses of already known sequence. TraFiC is an in-house pipeline able to identify somatic TEs (solo-L1, Alu, SINE, and ERV) in four steps: (i) selection of candidate reads; (ii) transposable element masking; (iii) clustering and prediction of TE integration sites; and (iv) filtering of germline events. The identification of L1- transductions is performed in a later step by using an additional module of TraFiC.
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A software pipeline to analyze transposable elements (TE) insertions in next-generation sequencing (NGS) data data. T-lex allows users to accurate genotyping of individual TE insertions and get the estimation of their population frequencies both using individual strain and pooled NGS. To achieve this, T-lex uses information from (i) a module specifically designed to identify target site duplications and (ii) the genomic context of each insertion, to identify putatively miss-annotated TE insertions. T-lex2 is composed of five modules that can be run with individual strain or pooled NGS datasets.
MELT / Mobile Element Locator Tool
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Allows users to discover and study mobile element insertions (MEIs) in whole genome sequencing (WGS) projects. MELT includes a robust MEI discovery algorithm and a suite of MEI analysis tools. Several run modes were developed to provide flexibility in implementation, including the single-sample (MELT-Single) mode, which are useful for discovering and annotating MEIs in a relatively small number of genomes and the multiple-sample (MELT-Split) mode and the multiple-sample (MELTSGE) automated mode which are engineered for population-scale studies involving hundreds or thousands of genomes.
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A tool for discovery and genotyping of transposable element variants (TEVs) (also known as mobile element insertions) from next-generation sequencing reads aligned to a reference genome in BAM format. The goal is to call TEVs that are not present in the reference genome but present in the sample that has been sequenced. It should be noted that RetroSeq can be used to locate any class of viral insertion in any species where whole-genome sequencing data with a suitable reference genome is available.
Alu Repeat Subfamily Classification
Permits to look overrepresented pairs of non-consensus nucleotide values at distinct positions, by computing biprofiles, that is, frequencies of pairs of nucleotide values. Alu Repeat Subfamily Classification can be used to identify subfamilies of other repeat families in non-primate species if necessary. However, this tool is not able to detect insertion/deletion mutations, frequent CpG mutations and mutations to nucleotide values present in other subfamilies.
Combines read-pair and split-read information to detect novel Alus and their precise breakpoints directly from either whole-genome or whole-exome sequencing data while also identifying insertions directly in the vicinity of existing Alus. To set the parameters of our method, we use simulation of a faux reference, which allows us to compute the precision and recall of various parameter settings using real sequencing data. Applying our method to 100 bp paired Illumina data from seven individuals, including two trios, we detected on average 1519 novel Alus per sample. Based on the faux-reference simulation, we estimate that our method has 97% precision and 85% recall.
An integrated structural variation (SV) caller which leverages multiple orthogonal SV signals for high accuracy and resolution. MetaSV proceeds by merging SVs from multiple tools for all types of SVs. It also analyzes soft-clipped reads from alignment to detect insertions accurately since existing tools underestimate insertion SVs. Local assembly in combination with dynamic programming is used to improve breakpoint resolution. Paired-end and coverage information is used to predict SV genotypes.
A database-free approach to finding dispersed duplication (DD) events in high-throughput sequencing data. DD_DETECTION is able to detect DDs purely from paired-end read alignments. We show in a comparative study that this method is able to compete with database-oriented aproaches in recovering validated transposon insertion events. We also experimentally validate the predictions of DD_DETECTION on a human DNA sample, showing that it can find not only duplicated elements present in common databases, but also DDs of novel type.
PTEMD / Polymorphic TEs and their Movement Detection
A computational method for de novo discovery of genome-wide polymorphic transposable elements (TEs). PTEMD searches highly identical sequences using reads supported breakpoint evidences. It relies on reads situated at ‘breakpoints’, i.e. reads that span inserted TEs and their flanking sequences. Using PTEMD, we identified 14 polymorphic TE families (905 sequences) in rice blast fungus Magnaporthe oryzae, and 68 (10,618 sequences) in maize.
Visual ModuleOrganizer
Allows the detection of repeat modules in a set of sequences. Visual ModuleOrganizer is a Java graphical interface that enables an optimized version of the ModuleOrganizer tool. Visual ModuleOrganizer interface allows users to easily choose ModuleOrganizer parameters and to graphically display the results. Moreover, Visual ModuleOrganizer dynamically handles graphical results through four main parameters: gene annotations, overlapping modules with known annotations, location of the module in a minimal number of sequences, and the minimal length of the modules. As a case study, the analysis of FoldBack4 sequences clearly demonstrated that these tools can be extended to comparative and evolutionary analyses of any repeat sequence elements in a set of genomic sequences.
A mapping-based tool for identification of the site and orientation of insertion sequences (IS) in bacterial genomes, direct from paired-end short read data. ISMapper was validated using three types of short read data: (i) simulated reads from a variety of species, (ii) Illumina reads from 5 isolates for which finished genome sequences were available for comparison, and (iii) Illumina reads from 7 Acinetobacter baumannii isolates for which predicted IS locations were tested using PCR. ISMapper provides a rapid and robust method for identifying IS insertion sites direct from short read data, with a high degree of accuracy demonstrated across a wide range of bacteria.
Identifies transposable element insertion sites at single-nucleotide resolution based on the paired-end mapping and clipped-read signatures produced by NGS alignments. Jitterbug can be easily integrated into existing NGS analysis pipelines, using the standard BAM format produced by frequently applied alignment tools (e.g. bwa, bowtie2), with no need to realign reads to a set of consensus transposon sequences. Jitterbug is highly sensitive and able to recall transposon insertions with a very high specificity, as demonstrated by benchmarks in the human and Arabidopsis genomes, and validation using long PacBio reads. In addition, Jitterbug estimates the zygosity of transposon insertions with high accuracy and can also identify somatic insertions.
A pipeline tool for the identification of targeted sequences from multidimensional high throughput sequencing data. InsertionMapper consists of four independently working modules: data preprocessing, database modeling, dimension deconvolution and element mapping. InsertionMapper is proven efficacious for the identification of target-enriched sequences from multidimensional high throughput sequencing data. With adjustable parameters and experiment configurations, this tool can save great computational effort to biologists interested in identifying their sequences of interest within the huge output of modern DNA sequencers.
Permits to automate and discover structural variations (SVs). Tardis is a toolkit that integrates read pair, read depth, and split read (using soft clipped mappings) sequence signatures to discover several types of SV, while resolving ambiguities among different putative SVs. This application is suitable for cloud use as the memory footprint is low. It is also capable of characterizing deletions, small novel insertions, tandem duplications, inversions, and mobile element retrotransposition.
Allows rapid detection of genomic repeats and their further assignment as LINEs (long interspersed nuclear elements) and SINEs (short interspersed nuclear elements) based on conserve pattern. RetroPred is an automated method integrating results from Pairwise Aligner for Long Sequences (PALS), Parsimonious Inference of a Library of Elementary Repeats (PILER), Multiple EM for Motif Elicitation (MEME) and artificial neural network (ANN). PALS and PILER are used to identify transposable DNA family. Then MEME is run to discover conserved short patterns present in the identified repeats. From the discovered patterns, binary pattern files are generated. These patterns files are used as input for a trained ANN for classification into LINEs and SINEs. The results are parsed into graphical representation, indicating the location of LINEs and SINEs in the genome.
STEAK / Specific Transposable Element Aligner (HERV-K)
Detects integrations of any sort in high-throughput sequencing (HTS) data. STEAK was built for validating and discovering transposable element (TE) and retroviral integrations in a variety of HTS data. The software performs on both single-end (SE) and paired-end (PE) libraries and on a variety of HTS sequencing strategies. It can be applied to a broad range of research interests and clinical uses such as population genetic studies and detecting polymorphic integrations.
MAK / MITE analysis kit
Facilitates automated analysis of miniature inverted repeat transposable elements (MITEs). MAK tool kit proposes the following major functions: retrieve the member sequences for a given MITE sequence, report the genes or putative genes closest to members of a MITE family, search for putative autonomous (anchor) elements for MITEs, search for Related Empty Sites for members of a MITE (or other TE) family, search for deletion derivative elements or MITE-sized elements of a query TE sequence, calculate the sequence divergence of each member of a TE family, find TE elements (DNA sequences) using transposase protein sequences. MAK is able to routinely retrieve family member sequences and to report the positions of these elements relative to the closest neighboring genes. It is a powerful tool for revealing anchor elements that link MITE families to known transposable element families.
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