Note that the reference sequence and ID must be present in the MSA.
For this option, the user will be asked to provide the ID of the references sequence. Remove positions that contain gaps in a user-specified reference sequence.Or put conversely, keep positions for which a residue is the most frequent character. Remove positions for which a gap is the most frequent character.Note that for this strategy positions included in the consensus sequence can have a gap as the most frequence character in the alignment, however more than half of the sequences in the alignment will have a residue at all included positions. Or put conversely, keep positions for which the gap frequency is < 50%. (Recommended) Remove positions for which the gap frequency is > 50%.Filtering insertions can be viewed as "Which positions do I want to include in my consensus sequence?" The consensus.py script allows for users to choose which method they prefer. Include flag to prevent saving images of MSA data analysis.įiltering an MSA for insertions is done differently by different groups. Must be a value between 0 and 1 (default: 0.5). Only valid for Option 1 for removing insertions. Gap frequecy threshold to define a consensus positions. If not given will use name of input FASTA file as template to name output files. Flagĭesired method for removing insertions. The following table gives an overview of the flag options as well. These packages can be installed using pip from the command line by running: Scripts were written using Python3.6 on a MacOSX (Unix) system.īoth scripts require the following non-standard packages:
Requirementsīoth scripts require Python3.6 or newer. Here we have made available a script (length_filter.py) to assist in preprocessing a sequence set by filtering sequences by sequence length prior to sequence alignment, and a script (consensus.py) to determine residue frequencies at all positions in an MSA, filter residue insertions from the MSA, and determine a consensus sequence. Applying preprocessing steps to a sequence set can improve sequence alignment and the resulting consensus sequence. All that is needed to design a protein consensus sequence is an MSA for the target protein family and basic coding scripts to determine residue frequencies at all positions in the MSA. A protein consensus sequences is composed of the most frequent residue at all positions in a multiple sequence alignment (MSA) of homologous protein sequences. Protein consensus sequence design has been shown to be a successful strategy for engineering highly stable proteins that retain their biological activities. Protein-consensus-sequence Table of contents
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