EMMA(1e)

💖 EMMA(1e) — the glow-up edition 💖

ok so bestie, you found your way to EMMA(1e), a page from the EMBOSS Manual for Debian. This is emma, and she's out here doing Multiple sequence alignment as a ClustalW wrapper. Pull up a chair, grab a boba, we're going through the whole thing together, every last flag. no skips, no shortcuts, periodt. ✨

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📜 NAME

emma — Multiple sequence alignment (ClustalW wrapper). that's the whole vibe. 🧬

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🎀 SYNOPSIS

emma -sequence seqall [-onlydend toggle] -dend toggle -dendfile infile
     [-slow toggle] -pwmatrix list -pwdnamatrix list
     -usermatrix variable -pairwisedatafile infile -matrix list
     -usermamatrix variable -dnamatrix list -umamatrix variable
     -mamatrixfile infile -pwgapopen float -pwgapextend float
     -ktup integer -gapw integer -topdiags integer -window integer
     -nopercent boolean [-gapopen float] [-gapextend float]
     [-endgaps boolean] [-gapdist integer] -norgap boolean
     -hgapres string -nohgap boolean [-maxdiv integer] -outseq seqoutset
     -dendoutfile outfile

emma -help

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🦋 DESCRIPTION

emma is a command line program from EMBOSS ("the European Molecular Biology Open Software Suite"). She belongs to the "Alignment:Multiple" command group(s). that's her little clique and she's thriving in it 💅

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✨ OPTIONS ✨

🌸 Input section

• -sequence seqall — the sequences you're feeding in. the moment of truth, bestie.
• -onlydend toggle — default value: N
• -dend toggle — default value: N
• -dendfile infile — the dendrogram file you're handing over.
• -slow toggle — okay so here's the tea: a distance gets calculated between every pair of sequences, and those distances build the dendrogram that guides the final multiple alignment. The scores come from separate pairwise alignments. You can calculate those using 2 methods: dynamic programming (slow but accurate) or the method of Wilbur and Lipman (extremely fast but approximate). The slow-accurate one is totally fine for short sequences but will be VERY SLOW for many (e.g. >100) long (e.g. >1000 residue) sequences. Default value: Y

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🧚 Pairwise align options

• -pwmatrix list — the scoring table that describes how similar each amino acid is to each other one. There are three 'in-built' series of weight matrices on offer, and each series has several matrices that behave differently at different evolutionary distances. For the exact details, read the documentation, iykyk. Roughly though: several matrices are stored in memory, spanning the full range of amino acid distance (from almost identical sequences all the way out to highly divergent ones). For very similar sequences, it's best to use a strict weight matrix, one that only gives a high score to identities and the most favoured conservative substitutions. For more divergent sequences, it's appropriate to use 'softer' matrices, which give a high score to lots of other frequent substitutions.
  1. BLOSUM (Henikoff). These matrices appear to be the best available for carrying out data base similarity (homology searches). The matrices used are: Blosum80, 62, 45 and 30.
  2. PAM (Dayhoff). These have been extremely widely used since the late '70s. The PAM 120, 160, 250 and 350 matrices get used here.
  3. GONNET. These matrices were derived using almost the same procedure as the Dayhoff one (above) but are much more up to date and are based on a far larger data set. They appear to be more sensitive than the Dayhoff series. The GONNET 40, 80, 120, 160, 250 and 350 matrices get used here.

An identity matrix is also supplied, which gives a score of 1.0 to two identical amino acids and a score of zero otherwise. This matrix is not very useful, ngl. Default value: b

• -pwdnamatrix list — the scoring table that describes the scores assigned to matches and mismatches (including IUB ambiguity codes). Default value: i
• -usermatrix variable — your own matrix goes here.
• -pairwisedatafile infile — the pairwise data file, bestie.

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👑 Matrix options

• -matrix list — this gives a menu where you're offered a choice of weight matrices. The default for proteins is the PAM series derived by Gonnet and colleagues. Note: a series is used! The actual matrix that gets used depends on how similar the sequences to be aligned at this alignment step are. Different matrices work differently at each evolutionary distance. There are three 'in-built' series of weight matrices offered, each consisting of several matrices which work differently at different evolutionary distances. To see the exact details, read the documentation. Crudely put: several matrices are stored in memory, spanning the full range of amino acid distance (from almost identical sequences to highly divergent ones). For very similar sequences, it's best to use a strict weight matrix which only gives a high score to identities and the most favoured conservative substitutions. For more divergent sequences, it's appropriate to use 'softer' matrices which give a high score to many other frequent substitutions.
  1. BLOSUM (Henikoff). These matrices appear to be the best available for carrying out data base similarity (homology searches). The matrices used are: Blosum80, 62, 45 and 30.
  2. PAM (Dayhoff). These have been extremely widely used since the late '70s. The PAM 120, 160, 250 and 350 matrices get used.
  3. GONNET. These matrices were derived using almost the same procedure as the Dayhoff one (above) but are much more up to date and are based on a far larger data set. They appear to be more sensitive than the Dayhoff series. The GONNET 40, 80, 120, 160, 250 and 350 matrices get used.

An identity matrix is also supplied, which gives a score of 1.0 to two identical amino acids and a score of zero otherwise. This matrix is not very useful. Alternatively, you can read in your own — just one matrix, not a series. Default value: b

• -usermamatrix variable — for when you're bringing your own to the party.
• -dnamatrix list — this gives a menu where a single matrix (not a series) can be selected. Default value: i
• -umamatrix variable — your matrix, your rules.
• -mamatrixfile infile — point it at the matrix file.

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🫶 Additional section

🐢 Slow align options

• -pwgapopen float — the penalty for opening a gap in the pairwise alignments. Default value: 10.0
• -pwgapextend float — the penalty for extending a gap by 1 residue in the pairwise alignments. Default value: 0.1

⚡ Fast align options

• -ktup integer — this is the size of exactly matching fragment that's used. INCREASE it for speed (max = 2 for proteins; 4 for DNA), DECREASE it for sensitivity. For longer sequences (e.g. >1000 residues) you may need to increase the default. Default value: @($(acdprotein)?1:2)
• -gapw integer — this is a penalty for each gap in the fast alignments. It has little affect on the speed or sensitivity except for extreme values. Default value: @($(acdprotein)?3:5)
• -topdiags integer — the number of k-tuple matches on each diagonal (in an imaginary dot-matrix plot) gets calculated, and only the best ones (the ones with the most matches) get used in the alignment. This parameter specifies how many. Decrease for speed; increase for sensitivity. Default value: @($(acdprotein)?5:4)
• -window integer — this is the number of diagonals around each of the 'best' diagonals that will be used. Decrease for speed; increase for sensitivity. Default value: @($(acdprotein)?5:4)
• -nopercent boolean — default value: N

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🎀 Gap options

• -gapopen float — the penalty for opening a gap in the alignment. Increasing the gap opening penalty will make gaps less frequent. Default value: 10.0
• -gapextend float — the penalty for extending a gap by 1 residue. Increasing the gap extension penalty will make gaps shorter. Terminal gaps are not penalised. Default value: 5.0
• -endgaps boolean — End gap separation: this treats end gaps just like internal gaps for the purposes of avoiding gaps that are too close (set by 'gap separation distance'). If you turn this off, end gaps will be ignored for this purpose. This is useful when you wish to align fragments where the end gaps are not biologically meaningful. Default value: Y
• -gapdist integer — Gap separation distance: this tries to decrease the chances of gaps being too close to each other. Gaps that are less than this distance apart are penalised more than other gaps. This does not prevent close gaps; it makes them less frequent, promoting a block-like appearance of the alignment. Default value: 8
• -norgap boolean — Residue specific penalties: amino acid specific gap penalties that reduce or increase the gap opening penalties at each position in the alignment or sequence. For example, positions that are rich in glycine are more likely to have an adjacent gap than positions that are rich in valine. Default value: N
• -hgapres string — this is a set of the residues 'considered' to be hydrophilic. It gets used when introducing Hydrophilic gap penalties. Default value: GPSNDQEKR
• -nohgap boolean — Hydrophilic gap penalties: used to increase the chances of a gap within a run (5 or more residues) of hydrophilic amino acids; these are likely to be loop or random coil regions where gaps are more common. The residues that are 'considered' to be hydrophilic are set by '-hgapres'. Default value: N
• -maxdiv integer — this switch delays the alignment of the most distantly related sequences until after the most closely related sequences have been aligned. The setting shows the percent identity level required to delay the addition of a sequence; sequences that are less identical than this level to any other sequences will be aligned later. Default value: 30

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💜 Output section

• -outseq seqoutset — where the output sequences go.
• -dendoutfile outfile — where the dendrogram output goes.

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💀 BUGS

Found a bug? Spill it to the Debian Bug Tracking system (http://bugs.debian.org/emboss), or go straight to the EMBOSS developers (http://sourceforge.net/tracker/?group_id=93650&atid=605031). they want to hear it, fr fr.

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🔍 SEE ALSO

emma is fully documented via the tfm(1) system. go look, bestie.

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⭐ AUTHOR

Debian Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>

• Wrote the script used to autogenerate this manual page. iconic behaviour honestly.

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🌈 COPYRIGHT

This manual page was autogenerated from an Ajax Control Definition of the EMBOSS package. It can be redistributed under the same terms as EMBOSS itself.

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and that's the whole page, no crumbs left 🍓 this beauty is from EMBOSS 6.4.0, dated 05/11/2012, and it's the EMMA(1e) manual page. slay, go align something 💖✨