lineage_mutations(pango_lin, mutation, freq)
- outbreak_data.lineage_mutations(pango_lin=None, lineage_crumbs=False, mutations=None, freq=0.8, server='api.outbreak.info', auth=None)
Retrieves data from all mutations in a specified lineage above a frequency threshold. - Use ‘OR’ in a string to return overlapping mutations in multiple lineages: ‘BA.2 OR BA.1’
- Arguments:
- pango_lin:
A string; loads data for all mutations in a specified PANGO lineage
- lineage_crumbs:
If true returns data for descendant lineages of pango_lin. Include the wildcard ‘*’ in string to return info on all related lineages.
- mutations:
A string; loads mutation data for the specified sequence under the specified PANGO lineage
- freq:
A number between 0 and 1 specifying the frequency threshold above which to return mutations (default = 0.8)
- return:
A pandas dataframe
Example usage:
Get a list of all mutations and relevant data associated with the variant ‘B.1.1.7’:
df = outbreak_data.lineage_mutations('b.1.1.7') print(df)
Output:
mutation mutation_count lineage_count lineage gene \
0 n:d3l 1133368 1154337 b.1.1.7 N
1 n:r203k 1131899 1154337 b.1.1.7 N
2 s:d614g 1150796 1154337 b.1.1.7 S
3 orf1a:t1001i 1149579 1154337 b.1.1.7 ORF1a
4 orf8:s84l 1148665 1154337 b.1.1.7 ORF8
5 s:a570d 1147678 1154337 b.1.1.7 S
6 s:p681h 1147591 1154337 b.1.1.7 S
7 orf1b:p314l 1147331 1154337 b.1.1.7 ORF1b
8 s:d1118h 1147009 1154337 b.1.1.7 S
9 orf1a:a1708d 1146288 1154337 b.1.1.7 ORF1a
10 orf8:y73c 1144041 1154337 b.1.1.7 ORF8
11 s:s982a 1142512 1154337 b.1.1.7 S
12 orf8:q27* 1142465 1154337 b.1.1.7 ORF8
13 s:t716i 1142087 1154337 b.1.1.7 S
14 n:s235f 1141424 1154337 b.1.1.7 N
15 orf8:r52i 1138388 1154337 b.1.1.7 ORF8
16 s:n501y 1129018 1154337 b.1.1.7 S
17 orf1a:i2230t 1127643 1154337 b.1.1.7 ORF1a
18 orf1a:del3675/3677 1115708 1154337 b.1.1.7 ORF1a
19 s:del69/70 1114288 1154337 b.1.1.7 S
20 s:del144/144 1093432 1154337 b.1.1.7 S
21 n:g204r 1050444 1154337 b.1.1.7 N
ref_aa alt_aa codon_num codon_end type \
0 D L 3 None substitution
1 R K 203 None substitution
2 D G 614 None substitution
3 T I 1001 None substitution
4 S L 84 None substitution
5 A D 570 None substitution
6 P H 681 None substitution
7 P L 314 None substitution
8 D H 1118 None substitution
9 A D 1708 None substitution
10 Y C 73 None substitution
11 S A 982 None substitution
12 Q * 27 None substitution
13 T I 716 None substitution
14 S F 235 None substitution
15 R I 52 None substitution
16 N Y 501 None substitution
17 I T 2230 None substitution
18 ORF1A:DEL3675/3677 DEL3675/3677 3675 3677.0 deletion
19 S:DEL69/70 DEL69/70 69 70.0 deletion
20 S:DEL144/144 DEL144/144 144 144.0 deletion
21 G R 204 None substitution
prevalence change_length_nt
0 0.981835 None
1 0.980562 None
2 0.996932 None
3 0.995878 None
4 0.995086 None
5 0.994231 None
6 0.994156 None
7 0.993931 None
8 0.993652 None
9 0.993027 None
10 0.991081 None
11 0.989756 None
12 0.989715 None
13 0.989388 None
14 0.988813 None
15 0.986183 None
16 0.978066 None
17 0.976875 None
18 0.966536 9.0
19 0.965306 6.0
20 0.947238 3.0
21 0.909998 None
Mutiple queries for lineages and mutations can be separated by “,”:
#Find mutation information for B.1.1.7, P.1, and XBB.1.5 df = outbreak_data_lineage_mutations('b.1.1.7, p.1, xbb.1.5') print(df)
Output
mutation mutation_count lineage_count lineage gene ref_aa \
0 n:d3l 1133368 1154337 b.1.1.7 N D
1 n:r203k 1131899 1154337 b.1.1.7 N R
2 s:d614g 1150796 1154337 b.1.1.7 S D
3 orf1a:t1001i 1149579 1154337 b.1.1.7 ORF1a T
4 orf8:s84l 1148665 1154337 b.1.1.7 ORF8 S
.. ... ... ... ... ... ...
63 s:g446s 156244 167128 xbb.1.5 S G
64 s:del144/144 154766 167128 xbb.1.5 S S:DEL144/144
65 s:h146q 153308 167128 xbb.1.5 S H
66 s:r408s 152365 167128 xbb.1.5 S R
67 s:k417n 147604 167128 xbb.1.5 S K
alt_aa codon_num codon_end type prevalence change_length_nt
0 L 3 None substitution 0.981835 None
1 K 203 None substitution 0.980562 None
2 G 614 None substitution 0.996932 None
3 I 1001 None substitution 0.995878 None
4 L 84 None substitution 0.995086 None
.. ... ... ... ... ... ...
63 S 446 None substitution 0.934876 None
64 DEL144/144 144 144.0 deletion 0.926033 3.0
65 Q 146 None substitution 0.917309 None
66 S 408 None substitution 0.911667 None
67 N 417 None substitution 0.883179 None
[113 rows x 12 columns]
Use ‘OR’ in a string to return overlapping mutations in multiple lineages:
df = outbreak_data.lineage_mutations('ba.2 OR xbb.1.5') print(df)
Output
mutation mutation_count lineage_count lineage gene \
0 n:r203k 237984 243206 P.1 OR xbb.1.5 N
1 s:d614g 242522 243206 P.1 OR xbb.1.5 S
2 orf1b:p314l 242226 243206 P.1 OR xbb.1.5 ORF1b
3 s:h655y 241765 243206 P.1 OR xbb.1.5 S
4 orf8:s84l 240116 243206 P.1 OR xbb.1.5 ORF8
5 n:g204r 238101 243206 P.1 OR xbb.1.5 N
6 s:n501y 235654 243206 P.1 OR xbb.1.5 S
7 orf1a:del3675/3677 226006 243206 P.1 OR xbb.1.5 ORF1a
ref_aa alt_aa codon_num codon_end type \
0 R K 203 None substitution
1 D G 614 None substitution
2 P L 314 None substitution
3 H Y 655 None substitution
4 S L 84 None substitution
5 G R 204 None substitution
6 N Y 501 None substitution
7 ORF1A:DEL3675/3677 DEL3675/3677 3675 3677.0 deletion
prevalence change_length_nt
0 0.978528 None
1 0.997188 None
2 0.995970 None
3 0.994075 None
4 0.987295 None
5 0.979010 None
6 0.968948 None
7 0.929278 9.0