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MUSCLE / MUltiple Sequence Comparison by Log- Expectation
Provides a multiple protein sequence alignment. MUSCLE uses two distance measures for a pair of sequences: a kmer distance (for an unaligned pair) and the Kimura distance (for an aligned pair). This application has three stages: it (i) builds a progressive alignment, (ii) improves the tree and builds a new progressive alignment according to this tree, and (iii) performs iterative refinement using a variant of tree-dependent restricted partitioning.
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Provides a fast-multiple similar DNA/RNA sequence alignment method. HAlign is a multiple sequence alignment (MSA) application based on the centre star strategy. The goal of this application is ultra-large biological sequences dataset included protein sequences and nucleotide sequences. This package can be used on all platforms and employs center star multiple sequence alignment strategy.
PicXAA / ProbabilistIC maXimum Accuracy Alignment
Finds the multiple sequence alignment (MSA) with the maximum expected accuracy (MEA). PicXAA is a probabilistic non-progressive alignment algorithm which takes a greedy approach to probabilistically build up the MSA, by starting from confidently alignable regions (with high similarities) and proceeding toward less confident regions (with lower similarities). By building up the MSA from the confidently alignable regions, the software reduces the risk of propagating the alignment errors made at the early stage to the final alignment.
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A whole genome pairwise and multiple alignment editor. The program highlights differences between pairs of alignments and allows the user to easily navigate large alignments of similar sequences. Although Base-By-Base was intended as an editor and viewer for alignments of highly similar sequences, it is also provides many of the functions of other generic alignment editors. In addition to visualizing genomes and protein sequences, Base-By-Base allows the user to estimate simple phylogenetic trees, calculate the numbers of conserved and non-conserved sequence positions, and test simple quantitative hypothesis using novel modifications.
Disregards genomic location information and treats the segments simply as sequences. Pecan is a colinear alignment method that makes posterior decoding and the consistency methodology practical for very large multiple alignments, both by accelerating the alignment process with principled constraint heuristics and limiting the memory consumption to a practical amount. The Pecan program attacks the multiple sequence alignment problem, which even at the genome scale has quite a long pedigree.
Aligns a single raw nucleotide sequence against one or more NAST formatted sequences. NAST-iEr is an alignment algorithm involves global dynamic programming profile alignment to fixed (NAST-formatted) multiply aligned template sequences without any end-gap penalty. It generates a NAST alignment for a single query sequence, including performing the reference sequence database search, takes on the order of one second per sequence on an average desktop computer. NAST-iEr is a part of the Microbiome Utilities package.
Samples from the joint posterior distribution of phylogenies, alignments and evolutionary parameters by applying the Markov chain Monte Carlo (MCMC) method. StatAlign also offers tools for efficient on-the-fly summarization of the results. This high-dimensional joint distribution can be analysed in several ways: the possibilities range from the simple statistics of marginalized single dimensions to the covariation analysis of multiple dimensions. StatAlign also provides the user with scores relating to the quality of a secondary structure prediction, such as information entropy values for the combined space of secondary structures and sampled alignments, and a reliability score that predicts the expected number of correctly predicted base-pairs.
Allows user to study phenotypic differences in vertebrate species. Mulan is a comparative tool that generates multiple-sequence local alignments (MSLAs). It contains an alignment engine consisting of several data analysis and visualization schemes for high-throughput identification. This tool has several functions such as: (1) determining phylogenetic relationships among the input sequences and generating phylogenetic trees; (2) constructing graphical and textual alignments; (3) detecting evolutionary conserved regions (ECRs) in alignments; and (4) offering user several visual display options for the generated conservation profiles.
A Bayesian posterior sampler that employs Markov chain Monte Carlo to explore the joint space of alignment and phylogeny given molecular sequence data. Simultaneous estimation eliminates bias toward inaccurate alignment guide-trees, employs more sophisticated substitution models during alignment and automatically utilizes information in shared insertion/deletions to help infer phylogenies. BAli-Phy also produces high-quality alignment estimates for highly divergent sequences, because it uses advanced substitution models and a realistic model of indels occurring on an (uncertain) tree. BAli-Phy can produce alignment uncertainty (AU) plots that are colored to indicate uncertain areas of the alignment.
Provides an approach to clean nucleotide alignments based on initial GBlocks cleaning of the corresponding amino acid alignment. TranslatorX is a web application that generates back-translated alignments and compared their phylogenetic performance with respect to direct nucleotide alignments in recovering the phylogenetic relationships of a set of vertebrates. This approach maximizes the retention of variable positions that otherwise would be removed by GBlocks cleaning of the nucleotide alignment. This application is also available as a command-line application.
Generates a 3D representation of properties of user-submitted RNA or DNA alignments. The visualized properties are information of single alignment columns, mutual information of two alignment positions as well as the position-specific fraction of gaps. The nucleotide composition of both single columns and column pairs is visualized with the help of color-coded 3D bars labeled with letters. CorreLogo generates both VRML and JVX output that can be viewed with a VRML viewer or the JavaView applet, respectively.
MaM / Multiple Alignment Manipulator
Assists in analyzing and parsing multiple sequence alignment files. MaM is suitable for parsing alignment data, finding the common repeat locations, exonic regions, extracting these regions to generate subalignments for independent analysis and for displaying variations within these alignments. It also includes a flexible platform for the treatment of other sequence motifs and properties that may be recognized by other programs and require to be analyzed independently.
POA / Partial Order Alignment
A fast program for multiple sequence alignment (MSA) in bioinformatics. POA guarantees that the optimal alignment of each new sequence versus each sequence in the MSA will be considered. Moreover, this algorithm introduces an edit operator, homologous recombination, important for multidomain sequences. POA’s advantages are speed, scalability, sensitivity, and the superior ability to handle branching / indels in the alignment. This algorithm enables the construction of massive and complex alignments.
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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.
A package for aligning multiple biological sequences. Opal attains accuracy on par with the state-of-the-art without altering the alignment scoring function by increasing gap penalties near hydrophobic regions, or through position specific substitution scores based on alignment consistency. With this heuristic, the alignment between two sequences in a group is not altered when new sequences are added to the group. Over all benchmarks, the median run time for Opal was less than 10 seconds, which was on an input of 20 sequences of length about 250.
A method for phylogeny-aware alignment of partial-order sequence graphs. PAGAN infers ancestral sequences for the reference alignment and adds new sequences in their phylogenetic context, either to predefined positions or by finding the best placement for sequences of unknown origin. Unlike profile-based alternatives, PAGAN considers the phylogenetic relatedness of the sequences and is not affected by inclusion of more diverged sequences in the reference set. Our analyses show that PAGAN outperforms alternative methods for alignment extension and provides superior accuracy for both DNA and protein data, the improvement being especially large for fragmented sequences. Moreover, PAGAN-generated alignments of noisy next-generation sequencing sequences are accurate enough for the use of RNA-seq data in evolutionary analyses.
Preserves mononucleotide frequencies, gap structure and local conservation patterns exactly, while preserving dinucleotide frequencies approximately. Multiperm is a shuffling algorithm for arbitrary multiple sequence alignments. The number of distinct shuffles that can be produced by the algorithm is very large for the vast majority of multiple sequence alignments. Together these characteristics provide a much more realistic null model for RNA prediction studies than previously available.
AltAVist / Alternative Alignment Visualization Tool
Allows comparisons between two different multiple alignments of a given data set. AltAVist highlights regions where both alignments coincide. It permits users to distinguish between upper-case and lower-case letters in the input alignments. This tool is able to consider only upper-case letters for the alignment comparison. It can serve for the evaluation of alignment programs by comparing their results to reference alignments that are considered as a standard of truth.
EDNA / Energy Based Multiple Sequence Alignment
Conserves the thermodynamic stability of multiple sequence alignments (MSAs). EDNA (Energy Based Multiple Sequence Alignment) is an extension of the open source MSA program Opal. Finds the correct alignment where a dinucleotide substitution is possible thermodynamically without disrupting the free energy of neighboring interactions. EDNA avoids problems resulting from under-sampling in a set of transcription factor binding sites (TFBSs), which may be particularly valuable when building alignments for non-global regulators.
MoDMaps3D / Molecular Distance Maps 3D
Computes and displays sequence and species relatedness. MoDMaps3D is an alignment-free web-tool using approximated information distance (AID) to quantify the pairwise differences in oligomer composition for all input genomic sequences, and visualizes the inter-relationships thus obtained as an interactive map in three-dimensional Euclidean space. MoDMaps3D can be used in different ways: (i) to explore a prebuilt map, (ii) to build a map ab initio for a new set of sequences, or (iii) add new DNA sequences to an existing map.
PASTASpark / Practical Alignments using SATé and TrAnsitivity
Allows to improve the performance of the alignment phase of practical alignments using saté and transitivity (PASTA). PASTASpark allows to execute PASTA on a distributed memory cluster making use of Apache Spark (a big data engine). Apache Spark permits to improve the performance of the alignment phase of PASTA. It guarantees scalability and fault tolerance, and contributes to obtain multiple sequence alignments (MSAs) from very large datasets in reasonable time.
A web server for manipulating multiple genome sequence alignments and their consensus sequences for high-throughput genome sequence analyses. This server facilitates the visual inspection of multiple genome sequence alignments for a set of genomic intervals at a time. This allows the user to examine how these sites are evolutionarily conserved over time for their functional importance. The server also reports consensus sequences for the input genomic intervals, which can be applied to downstream analyses such as the identification of common motifs in the regions determined by ChIP-seq experiments.
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