Accurarate amplicon alignment to gene consensus
Project description
Amplicons to Global Gene (A2G2)
This program implements the progressive algorithm to align a large set of amplicons to a reference gene consensus, or a large set of sequences to an amplicon consensus, based on a reference consensus. This program makes use of traditional multiple aligners such as MAFFT (default), and muscle, and can be extended to other aligners.
Problem
Some taxonomic assignment software require a set of align sequences, both in the query as in the reference. Projects such as those using environmental DNA (eDNA) or trying to assess wide diversity using metagenomics often have a hard time creating such alignments, because of memory and computational restrictions. Another observation is that massive alignments often introduce more gaps in the sequences, and force alignment of segments that should not align in that region. Here is where A2G2 will use a global to local alignment to avoid such issues, and retained the ungapped alignment of the amplicons.
Basic usage
A2G2 will give you help by:
A2G -h
this should give you something like this:
A2G version: 2020.0.1
Copyright 2020 Jose Sergio Hleap
usage: A2G [-h] [--cpus CPUS] [--nowrite] [--out_prefix OUT_PREFIX]
[--remove_duplicates]
global_consensus local_consensus fasta
positional arguments:
global_consensus Sequence consensus of the global region, e.g. full COI
local_consensus Sequence consensus of the local region, e.g. Leray
fragment
fasta fasta file with the focal sequences
optional arguments:
-h, --help show this help message and exit
--cpus CPUS number of cpus to use
--nowrite return string instead of writing
--out_prefix OUT_PREFIX
Prefix of outputs
--remove_duplicates Keep or remove duplicated sequences
Then to run it, you can simply type:
A2G global_target local_target query_file --cpus 10 --out_prefix prefix --remove_duplicates
With this command, you will use the global_target
as the overall region, the local_target
as the amplicon reference
sequence to anchor the query sequences, and query_file
contains your query sequences. Those are the required
arguments. The optional arguments allow you to control the execution. --cpus
allow you to provide the number of cpus
to use. In the example, up to 10 cpus will be used. --out_prefix
change the prefix of the outputs generated. Finally,
the --remove_duplicates
option will retain only unique sequences.
If the no_write
option is used, A2G2 will output the alignment
to standard out, and other info to standard error. If you would like to pipe
only the alignment, you can redirect the standard error to a null device:
A2G global_target local_target query_file --cpus 10 --out_prefix prefix --no_write 2> /dev/null
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