MantisBT - MEGA
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IDProjectCategoryView StatusDate SubmittedLast Update
0001429MEGA[All Projects] Feedbackpublic2019-09-20 09:152019-09-20 14:13
Reporterguest 
Assigned Togstecher 
PrioritynormalSeverityminorReproducibilityhave not tried
StatusresolvedResolutionnot fixable 
PlatformOSOS Version
Product VersionMEGA 11 (Graphical Interface version) 
Target VersionFixed in Version 
First NameJulius
Last NameCampecino
Emailcampecin@msu.edu
Confirm Emailcampecin@msu.edu
Summary0001429: error if number of sequence is too large
DescriptionHi,

I am trying to codon align 13000 sequences using muscle but it always gives me an error. It works fine when I tested mega with about 3000 sequences. I could probably just use the muscle software but it won't allow me to do codon alignment not like in mega.

I was wondering if there is any fix to this.

Julius
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Issue History
Date ModifiedUsernameFieldChange
2019-09-20 09:15guestNew Issue
2019-09-20 13:57gstecherNote Deleted: 0001218
2019-09-20 13:57gstecherNote Deleted: 0001222
2019-09-20 13:57gstecherNote Deleted: 0001251
2019-09-20 13:58gstecherNote Deleted: 0001250
2019-09-20 13:58gstecherNote Deleted: 0001249
2019-09-20 13:58gstecherNote Deleted: 0001223
2019-09-20 14:13gstecherNote Added: 0004305
2019-09-20 14:13gstecherStatusnew => resolved
2019-09-20 14:13gstecherResolutionopen => not fixable
2019-09-20 14:13gstecherAssigned To => gstecher

Notes
(0004305)
gstecher   
2019-09-20 14:13   
Hi Julius,

I am writing in response to your question regarding the MEGA software. For aligning that many sequences I think your best option is to use an alignment program that is designed to handle larger numbers of sequences such as MAFFT. Unfortunately, MEGA does not handle that much data very well for sequence alignment. You might also be able to do something like:

    translate codons to amino acids
    align amino acids
    map the aligned amino acids back to original codon data using something like http://wbiomed.curtin.edu.au/bioinf/CodonAlign.php [^] or a custom script

--
Best regards,
Glen Stecher
Institute for Genomics and Evolutionary Medicine
igem.temple.edu