MAVID: constrained ancestral alignment of multiple sequences.

By Nicolas L. Bray, Lior S. Pachter. Genome Research, 2003

327 citations recorded by the source corpus.

We describe a new global multiple-alignment program capable of aligning a large number of genomic regions. Our progressive-alignment approach incorporates the following ideas: maximum-likelihood inference of ancestral sequences, automatic guide-tree construction, protein-based anchoring of ab-initio gene predictions, and constraints derived from a global homology map of the sequences. We have implemented these ideas in the MAVID program, which is able to accurately align multiple genomic regions up to megabases long. MAVID is able to effectively align divergent sequences, as well as incomplete unfinished sequences. We demonstrate the capabilities of the program on the benchmark CFTR region, which consists of 1.8 Mb of human sequence and 20 orthologous regions in marsupials, birds, fish, and mammals. Finally, we describe two large MAVID alignments, an alignment of all the available HIV genomes and a multiple alignment of the entire human, mouse, and rat genomes.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b2523fe2f06dd303ca88c18dc75d5c0e70339326

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In Molecular Biology

Citations in the corpus

Fast Statistical Alignment (2009, unknown): “Analogously to other genome alignment programs such as MAVID [18], MLAGAN [19], CHAOS/DIALIGN [20] and Pecan [21], FSA uses long matches to anchor regions of the alignment and performs inference with dynamic programming in between anchors.”
Bioinformatics for Whole-Genome Shotgun Sequencing of Microbial Communities (2005, background): “When a closely related, fully sequenced genome is available, comparative assembly can easily be performed by extracting the homologous sequence and assembling it with either a comparative assembler [24] or an alignment program that can handle draft sequence [25,26].”
Recent developments in the MAFFT multiple sequence alignment program (2008, background): “Instead, MLAGAN [42] and MAVID [43] are useful.”
A tale of two clades: monkeypox viruses. (2005, methodology): “Genome alignments were generated with Mavid (Bray & Pachter, 2004) with default parameters and then edited by hand to remove errors.”
PhyloGibbs: A Gibbs Sampling Motif Finder That Incorporates Phylogeny (2005, methodology): “alignment algorithms [29–31] can be used for this task, and”
Population Genomics: Whole-Genome Analysis of Polymorphism and Divergence in Drosophila simulans (2007, methodology): “The MAVID [126] aligner was run on each orthologous segment in the map.”
microRNA Target Predictions across Seven Drosophila Species and Comparison to Mammalian Targets (2005, background): “The second set (termed set 2) came from true genome-wide multiple alignments (C. Dewey, MERCATOR, http://hanuman.math.berkeley.edu/ ; cdewey/ mercator/) [21].”
The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes (2014, background): “BSR [28], Magic [29], Mavid [30], Mauve [31-33], MGA [34], M-GCAT [35], Mugsy [36], TBA [37], multi-LAGAN [38], PECAN [39]), multiple genome alignment remains a challenging task due to the prevalence of horizontal gene transfer [26,40], recombination, homoplasy, gene conversion, mobile genetic eleme”
Improved pairwise alignment of genomic dna (2007, methodology): “In the MAVID multiple aligner, Bray and Pachter (2004) infer probabilistic sequences similar to ours, but reduce them to sequences of most-probable bases prior to alignment.”
Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. (2005, background): “nomes to be aligned (Brudno et al. 2003; Blanchette et al. 2004; Bray and Pachter 2004), cross-species conservation is emerging as”
Algebraic Statistics for Computational Biology: Preface (2005, methodology): “Summary: A multiple alignment program designed for large genomic sequences [Bray and Pachter, 2004].”
Tropical Halfspaces (2003, unknown): “C O ] 24 A ug 2 00”
Enredo and Pecan: genome-wide mammalian consistency-based multiple alignment with paralogs. (2008, background): “The second problem has been handled by different types of constraint heuristics, mostly relying on finding confident regions of high similarity that can be detected using more aggressive methods (Bray et al. 2003; Kurtz et al. 2004).”