diverse-seq implements computationally efficient alignment-free algorithms that enable efficient prototyping for phylogenetic workflows. It can accelerate parameter selection searches for sequence alignment and phylogeny estimation by identifying a subset of sequences that are representative of the diversity in a collection. We show that selecting representative sequences with an entropy measure of k-mer frequencies correspond well to sampling via conventional genetic distances. The computational performance is linear with respect to the number of sequences and can be run in parallel. Applied to a collection of 10.5k whole microbial genomes on a laptop took ~8 minutes to prepare the data and 4 minutes to select 100 representatives. diverse-seq can further boost the performance of phylogenetic estimation by providing a seed phylogeny that can be further refined by a more sophisticated algorithm. For ~1k whole microbial genomes on a laptop, it takes ~1.8 minutes to estimate a bifurcating tree from mash distances.
You can read more about the methods implemented in diverse_seq in the preprint here.
Convert sequence data into a more efficient format for the diversity assessment. This must be done before running either the nmost or max commands.
CLI options for dvs prep
Usage: dvs prep [OPTIONS]
Writes processed sequences to a <HDF5 file>.dvseqs.
Options:
-s, --seqdir PATH directory containing sequence files [required]
-sf, --suffix TEXT sequence file suffix [default: fa]
-o, --outpath PATH write processed seqs to this filename [required]
-np, --numprocs INTEGER number of processes [default: 1]
-F, --force_overwrite Overwrite existing file if it exists
-m, --moltype [dna|rna] Molecular type of sequences [default: dna]
-L, --limit INTEGER number of sequences to process
-hp, --hide_progress hide progress bars
--help Show this message and exit.
Selects the n sequences that maximise the total JSD. We recommend using nmost for large datasets.
Note A fuller explanation is coming soon!
Options for command line dvs nmost
Usage: dvs nmost [OPTIONS]
Identify n seqs that maximise average delta JSD
Options:
-s, --seqfile PATH path to .dvseqs file [required]
-o, --outpath PATH the input string will be cast to Path instance
-n, --number INTEGER number of seqs in divergent set [required]
-k INTEGER k-mer size [default: 6]
-i, --include TEXT seqnames to include in divergent set
-np, --numprocs INTEGER number of processes [default: 1]
-L, --limit INTEGER number of sequences to process
-v, --verbose is an integer indicating number of cl occurrences
[default: 0]
-hp, --hide_progress hide progress bars
--help Show this message and exit.
Options for cogent3 app dvs_nmost
The dvs nmost is also available as the cogent3 app dvs_nmost. The result of using cogent3.app_help("dvs_nmost") is shown below.
Overview
--------
select the n-most diverse seqs from a sequence collection
Options for making the app
--------------------------
dvs_nmost_app = get_app(
'dvs_nmost',
n=10,
moltype='dna',
include=None,
k=6,
seed=None,
)
Parameters
----------
n
the number of divergent sequences
moltype
molecular type of the sequences
k
k-mer size
include
sequence names to include in the final result
seed
random number seed
Notes
-----
If called with an alignment, the ungapped sequences are used.
The order of the sequences is randomised. If include is not None, the
named sequences are added to the final result.
Input type
----------
ArrayAlignment, SequenceCollection, Alignment
Output type
-----------
ArrayAlignment, SequenceCollection, Alignment
The result of the max command is typically a set that are modestly more diverse than that from nmost.
Note A fuller explanation is coming soon!
Options for command line dvs max
Usage: dvs max [OPTIONS]
Identify the seqs that maximise average delta JSD
Options:
-s, --seqfile PATH path to .dvseqs file [required]
-o, --outpath PATH the input string will be cast to Path instance
-z, --min_size INTEGER minimum size of divergent set [default: 7]
-zp, --max_size INTEGER maximum size of divergent set
-k INTEGER k-mer size [default: 6]
-st, --stat [stdev|cov] statistic to maximise [default: stdev]
-i, --include TEXT seqnames to include in divergent set
-np, --numprocs INTEGER number of processes [default: 1]
-L, --limit INTEGER number of sequences to process
-T, --test_run reduce number of paths and size of query seqs
-v, --verbose is an integer indicating number of cl occurrences
[default: 0]
-hp, --hide_progress hide progress bars
--help Show this message and exit.
Options for cogent3 app dvs_max
The dvs max is also available as the cogent3 app dvs_max.
Overview
--------
select the maximally divergent seqs from a sequence collection
Options for making the app
--------------------------
dvs_max_app = get_app(
'dvs_max',
min_size=5,
max_size=30,
stat='stdev',
moltype='dna',
include=None,
k=6,
seed=None,
)
Parameters
----------
min_size
minimum size of the divergent set
max_size
the maximum size of the divergent set
stat
either stdev or cov, which represent the statistics
std(delta_jsd) and cov(delta_jsd) respectively
moltype
molecular type of the sequences
include
sequence names to include in the final result
k
k-mer size
seed
random number seed
Notes
-----
If called with an alignment, the ungapped sequences are used.
The order of the sequences is randomised. If include is not None, the
named sequences are added to the final result.
Input type
----------
ArrayAlignment, SequenceCollection, Alignment
Output type
-----------
ArrayAlignment, SequenceCollection, Alignment
The result of the ctree command is a newick formatted tree string without distances.
Note A fuller explanation is coming soon!
Options for command line dvs ctree
Usage: dvs ctree [OPTIONS]
Quickly compute a cluster tree based on kmers for a collection of sequences.
Options:
-s, --seqfile PATH path to .dvseqs file [required]
-o, --outpath PATH the input string will be cast to Path instance
-m, --moltype [dna|rna] Molecular type of sequences [default: dna]
-k INTEGER k-mer size [default: 6]
--sketch-size INTEGER sketch size for mash distance
-d, --distance [mash|euclidean]
distance measure for tree construction
[default: mash]
-c, --canonical-kmers consider kmers identical to their reverse
complement
-L, --limit INTEGER number of sequences to process
-np, --numprocs INTEGER number of processes [default: 1]
-hp, --hide_progress hide progress bars
--help Show this message and exit.
Options for cogent3 app dvs_ctree
The dvs ctree is also available as the cogent3 app dvs_ctree or dvs_par_ctree. The latter is not composable, but can run the analysis for a single collection in parallel.
Overview
--------
Create a cluster tree from kmer distances.
Options for making the app
--------------------------
dvs_ctree_app = get_app(
'dvs_ctree',
k=12,
sketch_size=3000,
moltype='dna',
distance_mode='mash',
mash_canonical_kmers=None,
show_progress=False,
)
Initialise parameters for generating a kmer cluster tree.
Parameters
----------
k
kmer size
sketch_size
size of sketches, only applies to mash distance
moltype
seq collection molecular type
distance_mode
mash distance or euclidean distance between kmer freqs
mash_canonical_kmers
whether to use mash canonical kmers for mash distance
show_progress
whether to show progress bars
Notes
-----
This app is composable.
If mash_canonical_kmers is enabled when using the mash distance,
kmers are considered identical to their reverse complement.
References
----------
.. [1] Ondov, B. D., Treangen, T. J., Melsted, P., Mallonee, A. B.,
Bergman, N. H., Koren, S., & Phillippy, A. M. (2016).
Mash: fast genome and metagenome distance estimation using MinHash.
Genome biology, 17, 1-14.
Input type
----------
ArrayAlignment, SequenceCollection, Alignment
Output type
-----------
PhyloNode
Overview
--------
Create a cluster tree from kmer distances in parallel.
Options for making the app
--------------------------
dvs_par_ctree_app = get_app(
'dvs_par_ctree',
k=12,
sketch_size=3000,
moltype='dna',
distance_mode='mash',
mash_canonical_kmers=None,
show_progress=False,
max_workers=None,
parallel=True,
)
Initialise parameters for generating a kmer cluster tree.
Parameters
----------
k
kmer size
sketch_size
size of sketches, only applies to mash distance
moltype
seq collection molecular type
distance_mode
mash distance or euclidean distance between kmer freqs
mash_canonical_kmers
whether to use mash canonical kmers for mash distance
show_progress
whether to show progress bars
numprocs
number of workers, defaults to running serial
Notes
-----
This app is not composable but can run in parallel. It is
best suited to a single large sequence collection.
If mash_canonical_kmers is enabled when using the mash distance,
kmers are considered identical to their reverse complement.
References
----------
.. [1] Ondov, B. D., Treangen, T. J., Melsted, P., Mallonee, A. B.,
Bergman, N. H., Koren, S., & Phillippy, A. M. (2016).
Mash: fast genome and metagenome distance estimation using MinHash.
Genome biology, 17, 1-14.
Input type
----------
ArrayAlignment, SequenceCollection, Alignment
Output type
-----------
PhyloNode