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config.yaml
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config.yaml
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# Configuration file for pipeline
# List matutils pre-built mutation-annotated tree. We do the analysis for each tree and put
# in a subdirectory called `results_{mat}` where `{mat}` is the name of that tree.
# The most recent public trees are at
# http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/
mat_trees:
gisaid_2024-04-24: https://hgwdev.gi.ucsc.edu/~angie/be4910e/gisaidAndPublic.2024-04-24.masked.pb.gz
public_2024-04-19: http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/2024/04/19/public-2024-04-19.all.masked.pb.gz
public_2023-10-01: http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/2023/10/01/public-2023-10-01.all.masked.nextclade.pangolin.pb.gz
public_2023-06-21: http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/2023/06/21/public-2023-06-21.all.masked.nextclade.pangolin.pb.gz
public_2023-05-11: http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/2023/05/11/public-2023-05-11.all.masked.nextclade.pangolin.pb.gz
public_2023-03-27: http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/2023/03/27/public-2023-03-27.all.masked.nextclade.pangolin.pb.gz
public_2022-12-18: http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/2022/12/18/public-2022-12-18.all.masked.nextclade.pangolin.pb.gz
gisaid_2023-03-29: https://hgwdev.gi.ucsc.edu/~angie/2847b92/gisaidAndPublic.2023-03-29.masked.pb.gz
public_2022-01-31: http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/2022/01/31/public-2022-01-31.all.masked.nextclade.pangolin.pb.gz
# specify one of the mutation-annotated trees in `mat_trees` as the "current" one that is
# linked to by default as the best current estimates.
current_mat: gisaid_2024-04-24
# Reference GTF and FASTA, and location of spike coding sequence
ref_fasta: http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/bigZips/wuhCor1.fa.gz
ref_gtf: http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/bigZips/genes/ncbiGenes.gtf.gz
# gene annotations to add to the reference GTF, which is missing ORF9b, see:
# https://github.com/jbloomlab/SARS2-mut-fitness/issues/21
add_to_ref_gtf:
ORF9b: [28284, 28577]
# Only keep nextstrain clades with at least this many samples in mutation-annotated tree
min_clade_samples: 10000
# Subset samples based on whether they start with these regex matches
sample_subsets:
all: . # regex to match anything
USA: USA
England: England
# Clade founder genotypes. For backwards-compatibility, we use the ones from Richard Neher
# when available, and those from Cornelius Roemer when the Neher file does not have a
# founder for a clade, which is the case for newer clades as he is not updating that file.
clade_founders:
neher_json: https://raw.githubusercontent.com/neherlab/SC2_variant_rates/7e738194a8c6592082f1caa9a6ca70cb68289790/data/clade_gts.json
roemer_json: https://raw.githubusercontent.com/corneliusroemer/pango-sequences/main/data/pango-consensus-sequences_summary.json
# map Pango clades in `roemer_json` to NextStrain clades, from here:
# https://github.com/nextstrain/ncov/blob/master/defaults/clade_display_names.yml
roemer_nextstrain_to_pango:
23A: XBB.1.5
23B: XBB.1.16
23C: CH.1.1
23D: XBB.1.9
23E: XBB.2.3
23F: EG.5.1
23G: XBB.1.5.70
23H: HK.3
23I: BA.2.86
24A: JN.1
24B: JN.1.11.1
# Exclude these clades, for instance if no clade founder defined for them
clades_to_exclude:
- 21A
# For counting mutations, exclude any branches with more than this many nucleotide
# mutations or more than this many reversions to reference or clade founder. These
# filters are applied only on the coding nucleotide changes, not any non-coding ones.
max_nt_mutations: 4
max_reversions_to_ref: 1
max_reversions_to_clade_founder: 1
# Exclude nucleotide mutations from reference to clade founder and their reversions.
# These sites have higher than normal errors due to calling of missing bases to reference.
exclude_ref_to_founder_muts: true
# Only include sites in this range (inclusive). Currently set to exclude sites in the UTRs
# before/after coding sequences as these may not be well covered in UShER tree:
site_include_range:
start: 266 # start of ORF1ab
end: 29674 # end of ORF10
# exclude the following sites for all clades (set to null for no exclusions)
sites_to_exclude:
# Sites in Table S1 of https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1009175
- 153
- 1149
- 2198
- 3145
- 3564
- 3778
- 4050
- 6255
- 8022
- 8790
- 13402
- 13947
- 22802
- 24389
- 24390
- 24933
# sites specified for exclusion because they have extremely high mutation
# frequency in some clade
- 5629 # T5629G is much higher (~5% of all) in clade 20A than any other mutation.
- 6851 # C6851A and its reversion are top two mutations in 20C at ~5% and ~3% of all mutations
- 7328 # ~6% of all mutations in clade 21I, also highly mutated (~4% of all) in several other clades
- 28095 # ~11% of all mutations in clade 20I
- 29362 # ~30% of all mutations in clade 21C
# Name of VCF with sites masked across entire tree
site_mask_vcf: https://raw.githubusercontent.com/W-L/ProblematicSites_SARS-CoV2/master/subset_vcf/problematic_sites_sarsCov2.mask.vcf
# Name of YAML with UShER masked sites. These are sites masked per clade
# in the pre-built UShER tree.
usher_masked_sites: data/usher_masked_sites.yaml
# for analysis of 4-fold synonymous mutation spectra/rates, only keep clade subsets with
# at least this many non-excluded mutation counts
synonymous_spectra_min_counts: 5000
# Orf1ab to Nsp numbering (amino-acid start in Orf1ab) from
# https://github.com/theosanderson/Codon2Nucleotide/blob/main/src/App.js
orf1ab_to_nsps:
nsp1: [1, 180]
nsp2: [181, 818]
nsp3: [819, 2763]
nsp4: [2764, 3263]
nsp5 (Mpro): [3264, 3569]
nsp6: [3570, 3859]
nsp7: [3860, 3942]
nsp8: [3943, 4140]
nsp9: [4141, 4253]
nsp10: [4254, 4392]
nsp12 (RdRp): [4393, 5324]
nsp13: [5325, 5925]
nsp14: [5926, 6452]
nsp15: [6453, 6798]
nsp16: [6799, 7096]
# How to handle nucleotide sites that overlap among sites: exclude them from
# amino-acid fitness estimates or retain those sites in estimates. If retained, estimates
# can be confounded by not knowing which gene the selection is acting on.
gene_overlaps:
exclude:
- [ORF1a, ORF1ab] # 11 sites of overlap near ribosomal frameshifting location
- [ORF7a, ORF7b] # 1 site of overlap corresponding to ORF7a stop codon
retain:
- [N, ORF9b] # ORF9b is a 291 out-of-frame overlapping reading frame in N
# Pseudocount for calculating amino-acid fitnesses
fitness_pseudocount: 0.5
# initial cutoff for minimum expected count to show fitness values
min_expected_count: 10
# only plot correlation among clades when at least this many expected counts
clade_corr_min_count: 500000
# initial clade founder to use as "wildtype" when plotting aa fitnesses
aa_fitness_init_ref_clade: 19A
# amino-acid fitness heatmap color spans **at least** much (expanded if needed by data)
aa_fitness_heatmap_minimal_domain: [-6, 2]
# Define common names of Nexstrain clades
clade_synonyms:
19A: B
20A: B.1
20B: B.1.1
20C: B.1.367
20E: B.1.177
20F: D.2
20G: B.1.2
20I: Alpha
20J: Gamma
21C: Epsilon
21F: Iota
21I: Delta
21J: Delta
21K: Omicron BA.1
21L: Omicron BA.2
22A: Omicron BA.4
22B: Omicron BA.5
22C: Omicron BA.2.12.1
22D: Omicron BA.2.75
22E: Omicron BQ.1
22F: XBB
23A: XBB.1.5
23B: BB.1.16
23C: CH.1.1
23D: XBB.1.9
23E: XBB.2.3
23F: EG.5.1
23G: XBB.1.5.70
23H: HK.3
23I: BA.2.86
24A: JN.1
24B: JN.1.11.1
# Deep mutational scanning datasets to correlate fitness estimates with:
dms_datasets:
dadonaite_ba1_spike:
study: https://doi.org/10.1016/j.cell.2023.02.001
description: spike (Dadonaite et al, 2023)
gene: S
url: https://raw.githubusercontent.com/dms-vep/SARS-CoV-2_Omicron_BA.1_spike_DMS_mAbs/main/results/muteffects_functional/muteffects_observed.csv
filter_cols:
times_seen: 3
starr_rbd:
study: https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1010951
description: RBD (Starr et al, 2022)
gene: S
url: https://media.githubusercontent.com/media/jbloomlab/SARS-CoV-2-RBD_DMS_Omicron/f76ba2b2bec18ede9fa9da18c9ccc52389b1ba3a/results/final_variant_scores/final_variant_scores.csv
iketani_mpro:
study: https://www.sciencedirect.com/science/article/pii/S1931312822004024
description: Mpro (Iketani et al, 2022)
gene: nsp5 (Mpro)
url: https://raw.githubusercontent.com/alejandrochavezlab/3CL_protease_DMS/dc802ee3ea9d43005ca97a28af078767fd66777c/outputs/results/normalized_to_wt_and_stop/activity_scores.csv
wt_seq: data/Mpro.fa
flynn_mpro_2022:
study: https://elifesciences.org/articles/77433
description: Mpro (Flynn et al, 2022)
gene: nsp5 (Mpro)
url: https://cdn.elifesciences.org/articles/77433/elife-77433-fig2-data1-v2.xlsx
wt_seq: data/Mpro.fa
flynn_mpro_2023:
study: https://doi.org/10.1101/2023.03.02.530652
description: Mpro (Flynn et al, 2023)
gene: nsp5 (Mpro)
url: https://www.biorxiv.org/content/biorxiv/early/2023/03/02/2023.03.02.530652/DC1/embed/media-1.xlsx
# Spike fitness estimates from Richard Neher, based on approach in his paper:
# https://academic.oup.com/ve/advance-article/doi/10.1093/ve/veac113/6887176
# These are designed as an independent cross check of the fitness estimates here.
neher_fitness: data/Neher_aa_fitness.csv
# For analysis of fixed mutations in each clade, do this relative
# to this clade founder as "reference"
clade_fixed_muts_ref: 19A # this is Wuhan-Hu-1
# For analysis of mutation fitness versus terminal / non-terminal counts,
# specify pseudocount and initial minimum actual count
terminal_pseudocount: 0.5
terminal_min_actual_count: 5
# For dN/dS comparative analysis
dnds: https://raw.githubusercontent.com/spond/SARS-CoV-2-variation/master/windowed-sites-fel-all.csv
# For comparison to other studies
comparator_studies:
rodriguez_rivas_dca:
data: https://raw.githubusercontent.com/GiancarloCroce/DCA_SARS-CoV-2/main/data/data_dca_proteome.csv
name: Rodriguez-Rivas et al (2022)
maher_drivers:
data: https://www.science.org/doi/suppl/10.1126/scitranslmed.abk3445
name: Maher et al (2022)
thadani_learning:
data: https://www.biorxiv.org/content/biorxiv/early/2023/04/12/2022.07.21.501023/DC4/embed/media-4.zip
name: Thadani et al (2023)
# For GitHub Pages docs of plots
docs_url: https://jbloomlab.github.io/SARS2-mut-fitness # base URL for GitHub pages site
docs_plot_annotations: data/docs_plot_annotations.yaml # lists plots and their annotations
# Metadata for aa_fitness JSON
citation: https://academic.oup.com/ve/article/9/2/vead055/7265011
authors: [Jesse Bloom, Richard Neher]
source: https://github.com/jbloomlab/SARS2-mut-fitness/tree/main
description: Estimated fitness for amino acid mutations in each SARS-CoV-2 gene from natural occurrences.