Athena Vale
MUSCLE, or MUltiple Sequence Comparison by Log-Expectation, is a computer software program for multiple sequence alignment of protein and nucleotide sequences. It was introduced by Robert C. Edgar in two papers published in 2004. MUSCLE is a fast and accurate method for creating multiple alignments of protein sequences and is freely available for use. MUSCLE has been compared to other multiple sequence alignment methods such as CLUSTALW, T-Coffee, and MAFFT, and has been shown to achieve high accuracy and speed. The MUSCLE algorithm proceeds in three stages: draft progressive, improved progressive, and refinement. This introduction provides an overview of MUSCLE and its applications in sequence alignment.
| Characteristics | Values |
|---|---|
| Name | MUSCLE (MUltiple Sequence Comparison by Log-Expectation) |
| Use | Multiple sequence alignment of protein and nucleotide sequences |
| Algorithm | Three stages: draft progressive, improved progressive, and refinement |
| Speed | MUSCLE-fast variant is the fastest algorithm on all test sets |
| Accuracy | MUSCLE achieves the highest or joint-highest rank in accuracy |
| Availability | Freely available at http://www.drive5.com/muscle |
| Applications | Phylogenetic tree estimation, structure prediction, critical residue identification |
| First Paper | Published in Nucleic Acids Research |
| Second Paper | Published in BMC Bioinformatics |
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What You'll Learn
MUSCLE algorithm's three stages: draft progressive, improved progressive, and refinement
MUltiple Sequence Comparison by Log-Expectation (MUSCLE) is a computer software for multiple sequence alignment of protein and nucleotide sequences. The MUSCLE algorithm proceeds in three stages: draft progressive, improved progressive, and refinement.
Draft Progressive Stage
The goal of the first stage is to produce a multiple alignment, emphasizing speed over accuracy. The kmer distance is computed for each pair of input sequences, giving a distance matrix. Matrix D1 is clustered by UPGMA, producing a binary tree. A progressive alignment is then constructed by following the branching order of the tree. At each leaf, a profile is constructed from an input sequence. Nodes in the tree are visited in prefix order (children before their parent). At each internal node, a pairwise alignment is constructed of the two child profiles, giving a new profile that is assigned to that node.
Improved Progressive Stage
The main source of error in the draft progressive stage is the approximate kmer distance measure, which results in a suboptimal tree. MUSCLE, therefore, re-estimates the tree using the Kimura distance, which is more accurate but requires an alignment. The Kimura distance for each pair of input sequences is computed from MSA1, giving distance matrix D2. Matrix D2 is then clustered by UPGMA, producing binary tree TREE2. A progressive alignment is produced following TREE2, producing multiple alignment MSA2. This is optimized by computing alignments only for subtrees whose branching orders changed relative to TREE1.
Refinement Stage
An edge is chosen from TREE2, with edges being visited in decreasing distance from the root. The chosen edge is deleted, dividing the tree into two subtrees. The profile of the multiple alignment is then computed for each subtree. A new multiple sequence alignment is produced by re-aligning the subtree profiles. If the SP score is improved, the new alignment is kept, otherwise, it is discarded. The process of deleting an edge and aligning is repeated until convergence, or until a user-defined limit is reached.
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MUSCLE's speed and accuracy
MUSCLE, or MUltiple Sequence Comparison by Log-Expectation, is a computer software program for creating multiple alignments of protein and nucleotide sequences. The MUSCLE algorithm proceeds in three stages: the draft progressive, improved progressive, and refinement stages.
In the first stage, the algorithm produces a multiple alignment, emphasizing speed over accuracy. This step involves computing the k-mer distance for every pair of input sequences to create a distance matrix. The distance matrix is then clustered using UPGMA to produce a binary tree. From this tree, a progressive alignment is constructed, beginning with the creation of profiles for each leaf of the tree. This process continues until there is a multiple sequence alignment of all input sequences at the root of the tree.
The speed and accuracy of MUSCLE have been compared with other methods such as T-Coffee, MAFFT, and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART, and a new benchmark, PREFAB. MUSCLE achieves the highest or joint-highest rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT. It is also the fastest of the tested methods for large numbers of sequences. For example, MUSCLE can align 5000 sequences of average length 350 in just 7 minutes on a current desktop computer.
The MUSCLE program, source code, and PREFAB test data are freely available online. Multiple alignments of protein sequences are important in many applications, including phylogenetic tree estimation, structure prediction, and critical residue identification.
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MUSCLE-fast
MUSCLE, or MUltiple Sequence Comparison by Log-Expectation, is a computer software program for multiple sequence alignment of protein and nucleotide sequences. It was introduced by Robert C. Edgar in a 2004 paper published in Nucleic Acids Research, with further technical details published in a second paper in BMC Bioinformatics.
The MUSCLE algorithm operates in three stages: draft progressive, improved progressive, and refinement. In the first stage, the algorithm generates a multiple alignment, prioritizing speed over accuracy. This is achieved by computing the k-mer distance for each pair of input sequences to create a distance matrix. The distance matrix is then clustered using UPGMA to produce a binary tree, from which a progressive alignment is constructed. This process involves creating profiles for each leaf of the tree and constructing a pairwise alignment of the two child profiles for every node, resulting in a new profile assigned to that node. This continues until a multiple sequence alignment of all input sequences is achieved at the root of the tree.
The second stage focuses on refining the tree by calculating the Kimura distance for each pair of input sequences using the multiple sequence alignment from the first stage, creating a second distance matrix. This distance matrix is also clustered using UPGMA to produce a more optimal tree.
MUSCLE has been compared to other alignment methods such as T-Coffee, MAFFT, and CLUSTALW, and has achieved the highest or joint-highest rank in accuracy. It is particularly effective for large numbers of sequences, demonstrating its speed and efficiency. The MUSCLE program, source code, and test data are freely available online.
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MUSCLE compared to other MSA programs
MUSCLE (Multiple Sequence Comparison by Log-Expectation) is a software used for multiple sequence alignment (MSA) of nucleotide and protein sequences. It is one of the fastest MSA tools, and is comparable to other MSA programs such as T-COFFEE and MAFFT in terms of speed and accuracy. MUSCLE has been shown to be more accurate than Clustal Omega in most cases, making it a preferred alternative.
In terms of performance, MUSCLE has been found to be highly dependent on insertion rates, with SATe outperforming it in this aspect. When it comes to sequence length, MUSCLE achieved the highest SPS among other MSA tools, while ProbCons achieved the highest average scores. MUSCLE also achieved the highest sum of pairs among other tools when studying the effect of indel size on alignment quality, with ProbCons being the top performer.
The MUSCLE algorithm operates in three stages: draft progressive, improved progressive, and refinement. In the first stage, speed is prioritized over accuracy, and a k-mer distance is computed for each pair of input sequences to create a distance matrix. This matrix is then clustered using UPGMA to produce a binary tree, from which a progressive alignment is constructed. The final stage involves choosing an edge from the second tree and dividing it into two subtrees, before realigning the subtree profiles to produce a new multiple sequence alignment.
Overall, MUSCLE is a reliable and efficient MSA tool, offering high accuracy and throughput. It is a popular choice for MSA tasks, especially when speed is a priority, and its performance is comparable to other leading MSA programs.
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MUSCLE5
This approach enables unbiased assessments of sequence homology and phylogeny, providing novel confidence estimates in alignments, trees, and other inferences. MUSCLE5 has been shown to confidently resolve topologies with low bootstrap values according to standard methods, and conversely, identify incorrect topologies with high bootstraps.
When citing MUSCLE5, it is important to acknowledge the original source, which is the Nature Communications article by Robert C. Edgar, titled "Muscle5: High-accuracy alignment ensembles enable unbiased assessments of sequence homology and phylogeny." The article provides a detailed explanation of the MUSCLE5 algorithm and its applications, along with relevant examples and comparisons to standard methods.
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Frequently asked questions
MUSCLE is a computer software for multiple sequence alignment of protein and nucleotide sequences.
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).
MUSCLE is used to create multiple alignments of protein sequences, which are important in many applications, including phylogenetic tree estimation, structure prediction, and critical residue identification.
The MUSCLE algorithm was published by Robert C. Edgar in two papers in 2004. The citation is available on the Bioconductor website.
