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Merge pull request #74 from GavinHuttley/main
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DOC: include ctree in the README
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@GavinHuttley
GavinHuttley authored Nov 7, 2024
2 parents 07e3f2d + 4b73fa9 commit 64ec9d7
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227 changes: 218 additions & 9 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -37,8 +37,7 @@ Options:
-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, defaults to DNA
[default: dna]
-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.
Expand Down Expand Up @@ -75,7 +74,7 @@ Usage: dvs nmost [OPTIONS]
Identify n seqs that maximise average delta JSD
Options:
-s, --seqfile PATH path to .dvtgseqs file [required]
-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]
Expand Down Expand Up @@ -150,11 +149,11 @@ named sequences are added to the final result.
Input type
----------
SequenceCollection, ArrayAlignment, Alignment
ArrayAlignment, SequenceCollection, Alignment
Output type
-----------
SequenceCollection, ArrayAlignment, Alignment
ArrayAlignment, SequenceCollection, Alignment
```
<!-- [[[end]]] -->
Expand Down Expand Up @@ -188,7 +187,7 @@ Usage: dvs max [OPTIONS]
Identify the seqs that maximise average delta JSD
Options:
-s, --seqfile PATH path to .dvtgseqs file [required]
-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
Expand Down Expand Up @@ -273,12 +272,222 @@ named sequences are added to the final result.
Input type
----------
SequenceCollection, ArrayAlignment, Alignment
ArrayAlignment, SequenceCollection, Alignment
Output type
-----------
SequenceCollection, ArrayAlignment, Alignment
ArrayAlignment, SequenceCollection, Alignment
```
<!-- [[[end]]] -->
</details>
</details>

### `dvs ctree`: build a phylogeny using k-mers

The result of the `ctree` command is a newick formatted tree string without distances.

> **Note**
> A fuller explanation is coming soon!
<details>
<summary>Options for command line dvs ctree</summary>

<!-- [[[cog
import cog
from diverse_seq.cli import main
from click.testing import CliRunner
runner = CliRunner()
result = runner.invoke(main, ["ctree", "--help"])
help = result.output.replace("Usage: main", "Usage: dvs")
cog.out(
"```\n{}\n```".format(help)
)
]]] -->
```
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.
```
<!-- [[[end]]] -->

</details>

<details>
<summary>Options for cogent3 app dvs_ctree</summary>

The `dvs ctree` is also available as the [cogent3 app](https://cogent3.org/doc/app/index.html) `dvs_ctree` or `dvs_par_ctree`. The latter is not composable, but can run the analysis for a single collection in parallel.

<!-- [[[cog
import cog
import contextlib
import io
from cogent3 import app_help
buffer = io.StringIO()
with contextlib.redirect_stdout(buffer):
app_help("dvs_ctree")
cog.out(
"```\n{}\n```".format(buffer.getvalue())
)
]]] -->
```
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
```
<!-- [[[end]]] -->


<!-- [[[cog
import cog
import contextlib
import io
from cogent3 import app_help
buffer = io.StringIO()
with contextlib.redirect_stdout(buffer):
app_help("dvs_par_ctree")
cog.out(
"```\n{}\n```".format(buffer.getvalue())
)
]]] -->
```
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
```
<!-- [[[end]]] -->

</details>
4 changes: 3 additions & 1 deletion src/diverse_seq/cluster.py
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Original file line number Diff line number Diff line change
Expand Up @@ -130,6 +130,8 @@ def __init__(
Notes
-----
This app is composable.
If mash_canonical_kmers is enabled when using the mash distance,
kmers are considered identical to their reverse complement.
Expand Down Expand Up @@ -275,7 +277,7 @@ def __init__(
Notes
-----
This is app is not composable but can run in parallel. It is
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,
Expand Down

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