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Update nextclade workflow
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corneliusroemer committed Aug 27, 2024
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8 changes: 4 additions & 4 deletions .pre-commit-config.yaml
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@@ -1,23 +1,23 @@
exclude: '\.(tsv|fasta|gb)$|^ingest/vendored/'
repos:
- repo: https://github.com/snakemake/snakefmt
rev: v0.10.1
rev: v0.10.2
hooks:
- id: snakefmt
language_version: python3.11
- repo: https://github.com/rhysd/actionlint
rev: v1.6.27
rev: v1.7.1
hooks:
- id: actionlint
entry: env SHELLCHECK_OPTS='--exclude=SC2027' actionlint
- repo: https://github.com/codespell-project/codespell
rev: v2.2.6
rev: v2.3.0
hooks:
- id: codespell
additional_dependencies:
- tomli
- repo: https://github.com/google/yamlfmt
rev: v0.12.1
rev: v0.13.0
hooks:
- id: yamlfmt
- repo: https://github.com/pappasam/toml-sort
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7 changes: 7 additions & 0 deletions nextclade/.ruff.toml
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@@ -0,0 +1,7 @@
line-length = 110
indent-width = 4

[lint]
ignore = [
"E712" # Messes with pandas
]
4 changes: 2 additions & 2 deletions nextclade/Snakefile
Original file line number Diff line number Diff line change
Expand Up @@ -3,9 +3,9 @@ if not config:
configfile: "config/config.yaml"


# build_names = ["lineage-b.1", "clade-iib", "all-clades", "clade-i"]
build_names = ["lineage-b.1", "clade-iib", "all-clades", "clade-i"]
# build_names = ["lineage-b.1", "clade-iib", "all-clades"]
build_names = ["clade-i"]
# build_names = ["all-clades"]

PREALIGN_REFERENCE = "resources/lineage-b.1/reference.fasta"
PREMASK_BED = "resources/lineage-b.1/mask.bed"
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12 changes: 0 additions & 12 deletions nextclade/resources/all-clades/CHANGELOG.md
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@@ -1,13 +1 @@
## Unreleased

Initial release of this dataset. This dataset is similar to the v2 dataset [`MPXV/ancestral`](https://github.com/nextstrain/nextclade_data/tree/2023-08-17--15-51-24--UTC/data/datasets/MPXV/references/ancestral/versions/2023-08-01T12%3A00%3A00Z/files) with some differences.

### New and changed gene names

Some genes have been renamed and one has been added. The new annotation is based on NCBI refseq annotations that were released in November 2022. The v2 dataset predates this refseq:

- The 4 genes in the inverted terminal repeat segment (ITR) on both ends of the genome (OPG001, OPG002, OPG003,OPG015) are now all included. The genes on the 3' end (~positions 190000-197000) now have an `_dup` appended to distinguish them.
- The gene previously named `NBT03_gp052` is now called `OPG073`
- The gene previously named `NBT03_gp174` is now called `OPG016`
- The gene previously named `NBT03_gp175` is now called `OPG015_dup`
- Gene `OPG166` has been added
22 changes: 11 additions & 11 deletions nextclade/resources/all-clades/README.md
Original file line number Diff line number Diff line change
@@ -1,24 +1,24 @@
# Nextclade dataset for "Mpox virus (All Clades)"

| Key | Value |
| ---------------------- | --------------------------------------------------------------------------------------------------------------------- |
| authors | [Cornelius Roemer](https://neherlab.org), [Richard Neher](https://neherlab.org), [Nextstrain](https://nextstrain.org) |
| data source | Genbank |
| workflow | [github.com/nextstrain/mpox/nextclade](https://github.com/nextstrain/mpox/nextclade) |
| nextclade dataset path | nextstrain/mpox/all-clades |
| annotation | [NC_063383.1](https://www.ncbi.nlm.nih.gov/nuccore/NC_063383) |
| clade definitions | [github.com/mpxv-lineages/lineage-designation](https://github.com/mpxv-lineages/lineage-designation) |
| related datasets | Mpox virus (Clade IIb): `nextstrain/mpox/clade-iib`<br> Mpox virus (Lineage B.1) `nextstrain/mpox/lineage-b.1` |
| Key | Value |
| ---------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| authors | [Cornelius Roemer](https://neherlab.org), [Richard Neher](https://neherlab.org), [Nextstrain](https://nextstrain.org) |
| data source | Genbank |
| workflow | [github.com/nextstrain/mpox/nextclade](https://github.com/nextstrain/mpox/nextclade) |
| nextclade dataset path | nextstrain/mpox/all-clades |
| annotation | [NC_063383.1](https://www.ncbi.nlm.nih.gov/nuccore/NC_063383) |
| clade definitions | [github.com/mpxv-lineages/lineage-designation](https://github.com/mpxv-lineages/lineage-designation) |
| related datasets | Mpox virus (Clade IIb): `nextstrain/mpox/clade-iib`<br>Mpox virus (Lineage B.1) `nextstrain/mpox/lineage-b.1`<br>Mpox virus (Clade I): `nextstrain/mpox/clade-i` |

## Scope of this dataset

This dataset is for Mpox viruses of all clades (I, IIa and IIb). For a focused analysis of sequences from clade IIb, you may want to use the more specific dataset: "Clade IIb" (`nextstrain/mpox/clade-iib`). For an even more focused analysis of 2022-2023 outbreak sequences (lineage B.1 and sublineages), you may want to use the even more specific dataset: "Lineage B.1" (`nextstrain/mpox/lineage-b.1`).
This dataset is for Mpox viruses of all clades (Ia, Ib, IIa and IIb). For a focused analysis of sequences from clade IIb, you may want to use the more specific dataset: "Clade IIb" (`nextstrain/mpox/clade-iib`). For an even more focused analysis of 2022-2023 outbreak sequences (lineage B.1 and sublineages), you may want to use the even more specific dataset: "Lineage B.1" (`nextstrain/mpox/lineage-b.1`). For clade I sequences, you may want to use the dataset "Clade I" (`nextstrain/mpox/clade-i`).

## Reference sequence and reference tree

The reference used in this dataset is the clade IIb NCBI refseq `NC_063383.1` (Isolate `MPXV-M5312_HM12_Rivers`).

Sequences for the reference tree come from NCBI/Genbank and are downsampled to around 500 sequences from the diversity of clades, lineages, countries and collection dates.
Sequences for the reference tree come from NCBI/Genbank and are downsampled to around 900 sequences from the diversity of clades, lineages, countries and collection dates.

## Further reading

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4 changes: 4 additions & 0 deletions nextclade/resources/all-clades/sequences.fasta

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63 changes: 35 additions & 28 deletions nextclade/scripts/assign-colors.py
Original file line number Diff line number Diff line change
@@ -1,21 +1,24 @@
import argparse
import pdb

import pandas as pd

# Forced colours MUST NOT appear in the ordering TSV
forced_colors = {
}
forced_colors = {}

if __name__ == '__main__':
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Assign colors based on ordering",
formatter_class=argparse.ArgumentDefaultsHelpFormatter
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)

parser.add_argument('--ordering', type=str, required=True, help="input ordering file")
parser.add_argument('--color-schemes', type=str, required=True, help="input color schemes file")
parser.add_argument('--metadata', type=str, help="if provided, restrict colors to only those found in metadata")
parser.add_argument('--output', type=str, required=True, help="output colors tsv")
parser.add_argument("--ordering", type=str, required=True, help="input ordering file")
parser.add_argument("--color-schemes", type=str, required=True, help="input color schemes file")
parser.add_argument(
"--metadata",
type=str,
help="if provided, restrict colors to only those found in metadata",
)
parser.add_argument("--output", type=str, required=True, help="output colors tsv")
args = parser.parse_args()

assignment = {}
Expand All @@ -34,14 +37,18 @@
# 1. remove assignments that don't exist in metadata
# 2. remove assignments that have 'focal' set to 'False' in metadata
if args.metadata:
metadata = pd.read_csv(args.metadata, delimiter='\t')
metadata = pd.read_csv(args.metadata, delimiter="\t")
for name, trait in assignment.items():
# Items not to exclude if not (yet) present in metadata to solve bootstrapping issue
if name in metadata and name not in ['clade_membership', 'outbreak', 'lineage']:
if name in metadata and name not in [
"clade_membership",
"outbreak",
"lineage",
]:
subset_present = [x for x in assignment[name] if x in metadata[name].unique()]
assignment[name] = subset_present
if name in metadata and 'focal' in metadata:
focal_list = metadata.loc[metadata['focal'] == True, name].unique()
if name in metadata and "focal" in metadata:
focal_list = metadata.loc[metadata["focal"] == True, name].unique()
subset_focal = [x for x in assignment[name] if x in focal_list]
assignment[name] = subset_focal

Expand All @@ -53,28 +60,28 @@
array = line.lstrip().rstrip().split("\t")
schemes[counter] = array

with open(args.output, 'w') as f:
with open(args.output, "w") as f:
for trait_name, trait_array in assignment.items():
if len(trait_array)==0:
if len(trait_array) == 0:
print(f"No traits found for {trait_name}")
continue
if len(schemes)<len(trait_array):
print(f"WARNING: insufficient colours available for trait {trait_name} - reusing colours!")
remain = len(trait_array)
color_array = []
while(remain>0):
if (remain>len(schemes)):
color_array = [*color_array, *schemes[len(schemes)]]
remain -= len(schemes)
else:
color_array = [*color_array, *schemes[remain]]
remain = 0
if len(schemes) < len(trait_array):
print(f"WARNING: insufficient colours available for trait {trait_name} - reusing colours!")
remain = len(trait_array)
color_array = []
while remain > 0:
if remain > len(schemes):
color_array = [*color_array, *schemes[len(schemes)]]
remain -= len(schemes)
else:
color_array = [*color_array, *schemes[remain]]
remain = 0
else:
color_array = schemes[len(trait_array)]
color_array = schemes[len(trait_array)]
extra_trait_values = list(forced_colors.get(trait_name, {}).keys())
extra_color_values = list(forced_colors.get(trait_name, {}).values())

zipped = list(zip(trait_array+extra_trait_values, color_array+extra_color_values))
zipped = list(zip(trait_array + extra_trait_values, color_array + extra_color_values))
for trait_value, color in zipped:
f.write(trait_name + "\t" + trait_value + "\t" + color + "\n")
f.write("\n")
8 changes: 5 additions & 3 deletions nextclade/scripts/clades_renaming.py
Original file line number Diff line number Diff line change
Expand Up @@ -6,9 +6,7 @@
description="remove time info",
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument(
"--input-node-data", type=str, required=True, help="input data"
)
parser.add_argument("--input-node-data", type=str, required=True, help="input data")
parser.add_argument(
"--output-node-data",
type=str,
Expand Down Expand Up @@ -40,6 +38,10 @@
clade_name = "IIb"
outbreak_name = "hMPXV-1"
lineage_name = old_clade_name
elif old_clade_name[0] in "ABCDEFGHIJKLMNOPQRSTUVWXYZ":
clade_name = "IIb"
outbreak_name = "hMPXV-1"
lineage_name = old_clade_name
else:
raise ValueError(f"Unknown clade name: {old_clade_name}")

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10 changes: 2 additions & 8 deletions nextclade/scripts/collapse-zero-branches.py
Original file line number Diff line number Diff line change
Expand Up @@ -6,11 +6,7 @@


def get_branch_length_distribution(tree) -> Counter[float, int]:
return Counter(
node.branch_length
for node in tree.find_clades()
if node.branch_length is not None
)
return Counter(node.branch_length for node in tree.find_clades() if node.branch_length is not None)


def collapse_near_zero_branches(tree, threshold=0.001, verbose=False):
Expand All @@ -35,9 +31,7 @@ def collapse_near_zero_branches(tree, threshold=0.001, verbose=False):
difference = branch_length_counts_before - branch_length_counts_after

if verbose:
print(
f"Collapsed {difference.total()} internal branches with lengths below {threshold}"
)
print(f"Collapsed {difference.total()} internal branches with lengths below {threshold}")
print("Collapsed branches:")
for length, count in difference.items():
print(f"Branch length {length}: {count} branches")
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19 changes: 12 additions & 7 deletions nextclade/scripts/deduplicate.py
Original file line number Diff line number Diff line change
Expand Up @@ -9,10 +9,11 @@
"""

import typer
from Bio import SeqIO
import itertools

import llist
import typer
from Bio import SeqIO


def informative_sites(sequence: str) -> int:
Expand All @@ -21,6 +22,7 @@ def informative_sites(sequence: str) -> int:
"""
return sum([1 for c in sequence if c in "ACGT"])


def identical(seq1: str, seq2: str, info_sites: list) -> bool:
"""
Check if two sequences are identical (up to Ns)
Expand All @@ -33,6 +35,7 @@ def identical(seq1: str, seq2: str, info_sites: list) -> bool:
return False
return True


def composition_per_site(sequences) -> list:
"""
Compute the composition of each site in a list of sequences
Expand All @@ -47,6 +50,7 @@ def composition_per_site(sequences) -> list:
composition[i][c] += 1
return composition


def mismatch_prob_per_site(composition: list) -> list:
"""
Compute the mismatch probability of each site in a list of sequences
Expand All @@ -55,7 +59,7 @@ def mismatch_prob_per_site(composition: list) -> list:
result = []
seqs = sum(composition[0].values())
for site in composition:
values = [val/seqs for char, val in site.items() if char in "ACGT"]
values = [val / seqs for char, val in site.items() if char in "ACGT"]
prob = 0
for i, value in enumerate(values):
for j, other_value in enumerate(values):
Expand All @@ -64,17 +68,17 @@ def mismatch_prob_per_site(composition: list) -> list:
result.append(prob)
return result


def informative_indexes_sorted_by_entropy(composition: list) -> list:
"""
List of indexes of informative sites sorted by entropy
Uninformative sites are not included
"""
site_information = { i: info for i, info in enumerate(mismatch_prob_per_site(composition)) if info > 0 }
site_information = {i: info for i, info in enumerate(mismatch_prob_per_site(composition)) if info > 0}
site_information = sorted(site_information.items(), key=lambda x: x[1], reverse=True)
return [x[0] for x in site_information]



def deduplicate(input: str, output: str):
"""
Deduplicate sequences in a file
Expand All @@ -85,7 +89,8 @@ def deduplicate(input: str, output: str):
"""
with open(input, "r") as f:
sequences = [
{ "id": record.id,
{
"id": record.id,
"seq": str(record.seq),
"number_informative_sites": informative_sites(str(record.seq)),
}
Expand All @@ -106,7 +111,7 @@ def deduplicate(input: str, output: str):
while ying is not None:
yang = ying.next
while yang is not None:
if identical(str(ying.value["seq"]),str(yang.value["seq"]), info_sites):
if identical(str(ying.value["seq"]), str(yang.value["seq"]), info_sites):
print(f"Removing {yang.value['id']} as identical to {ying.value['id']}")
to_remove = yang
dup_list.append(yang.value["id"])
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