Synteny block identification aims to identify homologous chromosomal regions and relations between genomes. The identification of conserved syntenic regions enables discovery of predicted locations for orthologous and homeologous genes, even when no such gene is present. This capability means that synteny-based methods are far more effective than sequence similarity-based methods in identifying true-negatives, a necessity for studying gene loss and gene transposition.
Provides a genetic and radiation hybrid (RH) mapping tool. CarthaGene can deal with multiple populations, including mixtures of genetic and RH data. It performs multipoint maximum likelihood estimations with accelerated expectation–maximization algorithms for some pedigrees. It produces an ordered set of alternative maps which allows an estimation of the reliability of ordering of each marker. The set of all these maps can be explored manually and compared graphically.
Assists users in performing microbial genome annotation, data management and comparative analysis. MicroScope furnishes an environment permitting researchers to perform specifically comparative analysis of prokaryotic genomes, and manual curation of gene function in a comparative genomics and metabolic context. Moreover, this tool was used for annotating microbial genomes, transcriptomic and re-sequencing data.
A toolkit that implements an adjusted MCScan algorithm for detection of synteny and collinearity and incorporates 14 computer programs for visualizing and analyzing identified synteny and collinearity. MCScanX scans multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and aligns these regions using genes as anchors. MCScanX can be used to effectively analyze chromosome structural changes, and reveal the history of gene family expansions that might contribute to the adaptation of lineages and taxa. An integrated view of various modes of gene duplication can supplement the traditional gene tree analysis in specific families.
A multiple alignment tool for whole genomes. Mugsy uses Nucmer for pairwise alignment, a custom graph based segmentation procedure for identifying collinear regions, and the segment-based progressive multiple alignment strategy from Seqan::TCoffee. Mugsy does not require a reference sequence, can align mixtures of assembled draft and completed genome data, and is robust in identifying a rich complement of genetic variation including duplications, rearrangements, and large-scale gain and loss of sequence.
Helps in genome annotation. RATT is a software that allows users to transfer any entries from a reference sequence to similar samples. It can be applied to successive versions of a genome assembly, genomes of closely related species or strains. In addition, the software is also able to detect dissimilarities between two sequences and to generate inputs making genomes’ features to be visualized with Artemis. The software is a part of PAGIT toolkit.
A software package for detecting, displaying, and querying syntenic relationships between sequenced chromosomes and/or fingerprint contig physical maps. SyMAP uses MUMmer to compute the raw hits between the two genomes, which are then clustered and filtered using the optional gene annotation. The filtered hits are input to the synteny algorithm, which was designed to discover duplicated regions and form larger-scale synteny blocks, where intervening micro-rearrangements are allowed. SyMAP provides extensive interactive Java displays at all levels of resolution along with simultaneous displays of multiple aligned pairs. The synteny blocks from multiple chromosomes may be displayed in a high-level dot plot or three-dimensional view, and the user may then drill down to see the details of a region, including the alignments of the hits to the gene annotation.
Scans multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and aligns these regions using genes as anchors. MCscan takes the predicted pairwise segments from dynamic programming (DAGchainer in particular) and then try to build consensus segments from a set of related, overlapping segments. It is intended as an easy-to-use and quick way to identify conserved gene arrays both within the same genome and across different genomes.