FAMSA: Fast and Accurate Multiple Sequence Alignments. It provides a progressive algorithm for large-scale multiple sequence alignments of proteins.

Latest feature include:

• Fast guide tree heuristic called Medoid Tree (-medoidtree switch) for ultra-scale alignments:
  • the entire Pfam-A v33.1 in its largest NCBI variant (over 18 thousand families, 60 GB of raw FASTA files) was analyzed in 8 hours,
  • the family PF00005 of 3 million ABC transporters was aligned in 5 minutes and 24 GB of RAM.
• Remarkable time and memory optimizations - SLINK has been replaced with Prim’s minimum spanning tree algorithm when constructing default (single linkage) guide trees. NOTE: This may change quality results slightly compared to FAMSA 1 due to different ties resolution.
• Neighbour joining guide trees (-gt nj option). NOTE: Neighbour joining trees are calculated with a use of original O(N3) algorithm, thus their applicability on large sets is limited (unless they are used as subtrees with Medoid Tree heuristic).
• Option for compressing output aligment to gzip (-gz switch).
• Compatibility with ARM64 8 architecture (including Apple M1).
• Duplicate removal - redundant sequences are by default removed prior the alignment and restored afterwards (feature introduced in revision 2.1.0). This can change output alignments when a family contains duplicates. The old behaviour can be obtained by using -keep-duplicates switch.
• Profile-profile alignments (available by specifying two input FASTA files; introduced in revision 2.2.0).

References:

• Deorowicz, S., Debudaj-Grabysz, A. & Gudyś, A. FAMSA: Fast and accurate multiple sequence alignment of huge protein families. Sci Rep 6, 33964 (2016).

• FAMSA Github Site

• Module Name: famsa (see the modules page for more information)
• Multithreaded
• Environment variables set
  • FAMSA_TESTDATA: Location of example files

Allocate an interactive session and run the program.
Sample session (user input in bold):

[user@biowulf]$ sinteractive -c4 --mem=8G
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job

[user@cn3144 ~]$ module load famsa

[user@cn3144 ~]$ cp -r $FAMSA_TESTDATA .

[user@cn3144 ~]$ cd TEST_DATA

[user@cn3144 ~]$ famsa -t 4 adeno_fiber/adeno_fiber sl.aln
FAMSA (Fast and Accurate Multiple Sequence Alignment)
  version 2.2.2- (2022-10-09)
  S. Deorowicz, A. Debudaj-Grabysz, A. Gudys

Done!

[user@cn3144 ~]$ famsa -t 4 -medoidtree -gt upgma hemopexin/hemopexin upgma.medoid.aln
FAMSA (Fast and Accurate Multiple Sequence Alignment)
  version 2.2.2- (2022-10-09)
  S. Deorowicz, A. Debudaj-Grabysz, A. Gudys

Done!

[user@cn3144 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226

[user@biowulf ~]$

Create a batch input file (e.g. famsa.sh). For example:

#!/bin/bash
set -e
module load famsa
famsa -t $SLURM_CPUS_PER_TASK input.fasta ouput.aln

Submit this job using the Slurm sbatch command.

sbatch [--cpus-per-task=#] [--mem=#] famsa.sh

Create a swarmfile (e.g. famsa.swarm). For example:

famsa -t $SLURM_CPUS_PER_TASK input1.fasta ouput1.aln
famsa -t $SLURM_CPUS_PER_TASK input2.fasta ouput2.aln
famsa -t $SLURM_CPUS_PER_TASK input3.fasta ouput3.aln
famsa -t $SLURM_CPUS_PER_TASK input4.fasta ouput4.aln

Submit this job using the swarm command.

swarm -f famsa.swarm [-g #] [-t #] --module famsa