The Allele Frequencies Website [Search HLA Allele Frequencies]

HLA » Allele Frequency Search

Displaying all results from your selection.

Line	Allele	Population	% of individuals that have the allele	Allele Frequency	Sample Size	Location
1	B*58:01	Argentina Rosario Toba	1.2	0.0060	86	32_57_S_60_39_W
2	B*58:01	Australia Cape York Peninsula Aborigine		0.0100	103	10_41_S_142_32_E
3	B*58:01	Australia New South Wales Caucasian		0.0490	134	33_0_S_146_0_E
4	B*58:01	Australia Yuendumu Aborigine		0.0000	191	22_15_S_131_47_E
5	B*58:01	Austria	1.5	0.0080	200	48_13_N_16_21_E
6	B*58:01	Azores Central Islands		0.0090	59	38_0_N_28_0_W
7	B*58:01	Azores Oriental Islands		0.0260	43	36_58_N_25_6_W
8	B*58:01	Azores Terceira Island		0.0120	130	38_44_N_27_19_W
9	B*58:01	Brazil Belo Horizonte Caucasian	4.2	0.0210	95	19_55_S_43_56_W
10	B*58:01	Brazil Mixed		0.0220	108	23_10_S_47_48_W
11	B*58:01	Brazil Vale do Ribeira Quilombos	0.0	0.0000	144	24_36_S_48_15_W
12	B*58:01	Bulgaria		0.0180	55	42_0_N_23_0_E
13	B*58:01	Burkina Faso Fulani		0.0610	49	12_50_N_1_50_W
14	B*58:01	Burkina Faso Mossi		0.0570	53	12_50_N_1_50_W
15	B*58:01	Burkina Faso Rimaibe		0.0430	47	12_50_N_1_50_W
16	B*58:01	Cameroon Baka Pygmy		0.1500	10	8_30_N_14_0_E
17	B*58:01	Cameroon Bakola Pygmy	8.0		50	4_3_N_9_42_E
18	B*58:01	Cameroon Bamileke		0.0520	77	5_28_N_10_25_E
19	B*58:01	Cameroon Beti		0.0370	174	2_55_N_11_9_E
20	B*58:01	Cameroon Sawa		0.1150	13	4_50_N_10_0_E
21	B*58:01	Cameroon Yaounde		0.0540	92	3_52_N_11_31_E
22	B*58:01	Cape Verde Northwestern Islands		0.0320	62	16_0_N_24_0_W
23	B*58:01	Cape Verde Southeastern Islands		0.0400	62	16_0_N_24_0_W
24	B*58:01	Central African Republic Mbenzele Pygmy	5.5		36	3_32_N_16_4_E
25	B*58:01	Chile Mapuche		0.0154	66	37_48_S_73_23_W
26	B*58:01	Chile Santiago Mixed	1.0		70	33_26_S_70_39_W
27	B*58:01	China Beijing		0.0230	67	39_58_N_116_24_E
28	B*58:01	China Beijing Shijiazhuang Tianjian Han		0.0600	618	39_54_N_116_24_E
29	B*58:01	China Canton Han		0.0890	264	23_6_N_113_15_E
30	B*58:01	China Guangdong Province Meizhou Han		0.1700	100	24_27_N_116_7_E
31	B*58:01	China Guangxi Region Maonan		0.0420	108	23_48_N_108_59_E
32	B*58:01	China Guangzhou		0.0850	102	23_6_N_113_15_E
33	B*58:01	China Guangzhou Han		0.0470	106	23_6_N_113_15_E
34	B*58:01	China Guizhou Province Bouyei		0.0830	109	26_50_N_106_50_E
35	B*58:01	China Guizhou Province Miao pop 2		0.0480	85	26_50_N_106_50_E
36	B*58:01	China Guizhou Province Shui		0.0150	153	26_50_N_106_50_E
37	B*58:01	China Han HIV negative		0.0630	72	36_34_N_103_49_E
38	B*58:01	China Henan HIV negative		0.0630	16	34_0_N_113_40_E
39	B*58:01	China Hubei Han	12.3	0.0616	3,732	30_45_N_114_15_E
40	B*58:01	China Inner Mongolia Region		0.0880	102	36_0_N_102_0_E
41	B*58:01	China Jiangsu Han		0.0710	3,238	32_54_N_119_48_E
42	B*58:01	China Jiangsu Province Han		0.0714	334	32_54_N_119_48_E
43	B*58:01	China Marrow Donor Registry		0.0620	600	39_54_N_116_23_E
44	B*58:01	China North Han		0.0290	105	39_54_N_116_24_E
45	B*58:01	China Qinghai Province Hui		0.0230	110	36_0_N_102_0_E
46	B*58:01	China Shanxi HIV negative		0.0230	22	36_5_N_111_50_E
47	B*58:01	China Sichuan HIV negative		0.0880	34	30_50_N_102_49_E
48	B*58:01	China South Han		0.0890	284	23_1_N_113_3_E
49	B*58:01	China Southwest Dai		0.0770	124	22_0_N_100_48_E
50	B*58:01	China Tibet Region Tibetan		0.0160	158	29_39_N_91_7_E
51	B*58:01	China Yunnan Bulang		0.0040	116	21_57_N_100_27_E
52	B*58:01	China Yunnan Hani		0.0270	150	21_59_N_100_49_E
53	B*58:01	China Yunnan Province Han		0.0740	101	24_2_N_105_3_E
54	B*58:01	China Yunnan Province Jinuo		0.0050	109	24_30_N_101_30_E
55	B*58:01	China Yunnan Province Lisu		0.0070	111	24_30_N_101_30_E
56	B*58:01	China Yunnan Province Nu		0.0190	107	24_30_N_101_30_E
57	B*58:01	China Yunnan Province Wa		0.0170	119	24_30_N_101_30_E
58	B*58:01	Colombia Bogotá Cord Blood	3.3	0.0167	1,463	4_39_N_73_52_W
59	B*58:01	Croatia		0.0130	150	45_0_N_15_0_E
60	B*58:01	Croatia pop 4		0.0105	4,000	45_48_N_15_57_E
61	B*58:01	Cuba Caucasian	5.7	0.0290	70	23_8_N_82_22_W
62	B*58:01	Cuba Mixed Race	9.5	0.0480	42	23_8_N_82_22_W
63	B*58:01	Czech Republic		0.0140	106	50_0_N_14_0_E
64	B*58:01	Czech Republic NMDR		0.0069	5,099	49_48_N_15_30_E
65	B*58:01	England North West	1.0	0.0050	298	53_0_N_3_0_W
66	B*58:01	France Corsica Island		0.0450	100	42_9_N_9_5_E
67	B*58:01	France French Bone Marrow Donor Registry		0.0102	42,623	48_51_N_2_21_E
68	B*58:01	France Southeast	3.1	0.0160	130	46_0_N_5_0_E
69	B*58:01	Gaza	9.5	0.0476	42	31_22_N_34_18_E
70	B*58:01	Georgia Tibilisi		0.0140	109	41_41_N_44_57_E
71	B*58:01	Germany DKMS - Austria minority		0.0118	1,698	48_31_N_9_3_E
72	B*58:01	Germany DKMS - Bosnia and Herzegovina minority		0.0097	1,028	48_31_N_9_3_E
73	B*58:01	Germany DKMS - China minority		0.0593	1,282	48_31_N_9_3_E
74	B*58:01	Germany DKMS - Croatia minority		0.0117	2,057	48_31_N_9_3_E
75	B*58:01	Germany DKMS - France minority		0.0125	1,406	48_31_N_9_3_E
76	B*58:01	Germany DKMS - German donors		0.0079	3,456,066	48_31_N_9_3_E
77	B*58:01	Germany DKMS - Greece minority		0.0145	1,894	48_31_N_9_3_E
78	B*58:01	Germany DKMS - Italy minority		0.0198	1,159	48_31_N_9_3_E
79	B*58:01	Germany DKMS - Netherlands minority		0.0073	1,374	48_31_N_9_3_E
80	B*58:01	Germany DKMS - Portugal minority		0.0162	1,176	48_31_N_9_3_E
81	B*58:01	Germany DKMS - Romania minority		0.0097	1,234	48_31_N_9_3_E
82	B*58:01	Germany DKMS - Spain minority		0.0131	1,107	48_31_N_9_3_E
83	B*58:01	Germany DKMS - Turkey minority		0.0180	4,856	48_31_N_9_3_E
84	B*58:01	Germany DKMS - United Kingdom minority		0.0048	1,043	48_31_N_9_3_E
85	B*58:01	Germany pop 6		0.0081	8,862	51_6_N_10_23_E
86	B*58:01	Germany pop 8		0.0090	39,689	48_24_N_9_58_E
87	B*58:01	Ghana Ga-Adangbe	7.6	0.0420	131	5_45_N_0_12_E
88	B*58:01	Greece pop 8	4.8	0.0241	83	37_58_N_23_43_E
89	B*58:01	Guatemala Mayan		0.0070	132	14_8_N_91_5_W
90	B*58:01	Guinea Bissau		0.0780	65	12_0_N_15_0_W
91	B*58:01	Hong Kong Chinese	14.2	0.0730	569	22_16_N_114_9_E
92	B*58:01	Hong Kong Chinese BMDR		0.0887	7,595	22_15_N_114_10_E
93	B*58:01	Hong Kong Chinese cord blood registry		0.0840	3,892	22_15_N_114_10_E
94	B*58:01	India Andhra Pradesh Golla		0.0720	111	17_5_N_78_5_E
95	B*58:01	India Central UCBB	7.9	0.0395	4,204	27_1_N_81_19_E
96	B*58:01	India Delhi pop 2	15.4	0.0880	90	28_36_N_77_13_E
97	B*58:01	India East UCBB	7.0	0.0348	2,403	22_25_N_88_18_E
98	B*58:01	India Khandesh Region Pawra		0.1500	50	20_54_N_74_46_E
99	B*58:01	India Mumbai Maratha		0.0740	91	18_58_N_72_49_E
100	B*58:01	India New Delhi		0.0680	71	28_37_N_77_13_E
101	B*58:01	India North pop 2		0.0580	72	25_0_N_74_0_E
102	B*58:01	India North UCBB	9.6	0.0479	5,849	28_36_N_77_11_E
103	B*58:01	India Northeast UCBB	6.4	0.0321	296	26_16_N_91_48_E
104	B*58:01	India South UCBB	6.9	0.0347	11,446	13_6_N_80_8_E
105	B*58:01	India Tamil Nadu		0.0366	2,492	11_32_N_78_52_E
106	B*58:01	India West Bhil		0.0900	50	20_54_N_74_46_E
107	B*58:01	India West Coast Parsi		0.0300	50	18_0_N_74_0_E
108	B*58:01	India West UCBB	7.7	0.0385	5,829	19_11_N_73_3_E
109	B*58:01	Indonesia Java pop 2		0.0420	36	6_8_S_106_10_E
110	B*58:01	Indonesia Java Western	11.4		236	7_30_S_111_15_E
111	B*58:01	Indonesia Sundanese and Javanese		0.0600	201	6_8_S_106_10_E
112	B*58:01	Iran Baloch		0.0400	100	29_29_N_60_52_E
113	B*58:01	Iran Gorgan		0.0080	64	36_50_N_54_43_E
114	B*58:01	Iran Kurd pop 2		0.0500	60	36_17_N_46_17_E
115	B*58:01	Iran Saqqez-Baneh Kurds		0.0500	60	36_14_N_46_16_E
116	B*58:01	Iran Tabriz Azeris		0.0258	97	38_4_N_46_17_E
117	B*58:01	Iran Yazd		0.0089	56	31_53_N_54_21_E
118	B*58:01	Ireland Northern	0.6	0.0030	1,000	54_40_N_6_45_W
119	B*58:01	Ireland South	0.8	0.0040	250	53_20_N_6_15_W
120	B*58:01	Israel Arab Druze		0.0150	101	31_8_N_35_2_E
121	B*58:01	Israel Arab pop 2		0.0230	12,301	32_8_N_34_52_E
122	B*58:01	Israel Argentina Jews		0.0187	4,307	32_8_N_34_52_E
123	B*58:01	Israel Ashkenazi and Non Ashkenazi Jews		0.0320	146	31_8_N_35_2_E
124	B*58:01	Israel Ashkenazi Jews pop 3		0.0248	4,625	32_8_N_34_52_E
125	B*58:01	Israel Bukhara Jews		0.0222	2,317	32_8_N_34_52_E
126	B*58:01	Israel Druze		0.0170	5,914	32_41_N_35_17_E
127	B*58:01	Israel Ethiopia Jews		0.0398	5,928	32_8_N_34_52_E
128	B*58:01	Israel Georgia Jews		0.0037	4,471	32_10_N_34_53_E
129	B*58:01	Israel Iran Jews		0.0205	8,153	32_8_N_34_52_E
130	B*58:01	Israel Iraq Jews		0.0106	13,270	32_10_N_34_52_E
131	B*58:01	Israel Kavkazi Jews		0.0121	2,840	32_10_N_34_52_E
132	B*58:01	Israel Libya Jews		0.0100	3,739	32_10_N_34_52_E
133	B*58:01	Israel Morocco Jews		0.0108	36,718	32_10_N_34_52_E
134	B*58:01	Israel Poland Jews		0.0231	13,871	32_10_N_34_52_E
135	B*58:01	Israel Tunisia Jews		0.0081	9,070	32_10_N_34_52_E
136	B*58:01	Israel USA Jews		0.0219	6,058	32_10_N_34_52_E
137	B*58:01	Israel USSR Jews		0.0151	45,681	32_9_N_34_50_E
138	B*58:01	Israel YemenJews		0.0555	15,542	32_9_N_34_50_E
139	B*58:01	Italy North pop 3	6.7	0.0330	97	43_0_N_12_0_E
140	B*58:01	Italy pop 5		0.0160	975	45_28_N_9_11_E
141	B*58:01	Italy Sardinia pop3		0.0640	100	39_14_N_9_3_E
142	B*58:01	Ivory Coast Adiopodoume Akan		0.0230	44	5_20_N_4_0_W
143	B*58:01	Japan Central		0.0040	371	35_41_N_139_46_E
144	B*58:01	Japan pop 16		0.0058	18,604	35_41_N_139_46_E
145	B*58:01	Japan pop 3		0.0050	1,018	35_41_N_139_46_E
146	B*58:01	Jordan Amman		0.0140	146	31_35_N_36_20_E
147	B*58:01	Kenya		0.0800	144	1_28_S_36_8_E
148	B*58:01	Kenya Luo		0.0700	265	0_0_S_34_6_E
149	B*58:01	Kenya Nandi		0.1000	240	0_0_S_35_0_E
150	B*58:01	Kenya, Nyanza Province, Luo tribe	14.0	0.0750	100	0_5_S_34_46_E
151	B*58:01	Kosovo	2.4	0.0121	124	42_34_N_21_0_E
152	B*58:01	Macedonia pop 4		0.0090	216	42_0_N_21_0_E
153	B*58:01	Madeira		0.0160	185	32_44_N_16_58_W
154	B*58:01	Malaysia Champa	10.3	0.0520	29	2_30_N_112_30_E
155	B*58:01	Malaysia Jelebu Temuan		0.1040	25	2_56_N_102_5_E
156	B*58:01	Malaysia Kelantan	7.1	0.0360	28	2_30_N_112_30_E
157	B*58:01	Malaysia Mandailing	3.7	0.0190	27	2_30_N_112_30_E
158	B*58:01	Malaysia Patani	20.0	0.1000	25	2_30_N_112_30_E
159	B*58:01	Malaysia Peninsular Chinese	22.2	0.1211	194	3_9_N_101_57_E
160	B*58:01	Malaysia Peninsular Indian	5.9	0.0295	271	3_9_N_101_57_E
161	B*58:01	Malaysia Peninsular Malay	11.3	0.0584	951	3_9_N_101_57_E
162	B*58:01	Malaysia Perak Grik Jehai		0.0600	25	5_25_N_101_8_E
163	B*58:01	Malaysia Sarawak Bau Bidayuh		0.1400	25	1_25_N_110_9_E
164	B*58:01	Mali Bandiagara		0.0220	138	14_4_N_3_6_W
165	B*58:01	Mexico Chihuahua Chihuahua City Pop 2	2.3	0.0114	88	28_48_N_106_26_W
166	B*58:01	Mexico Guadalajara Mestizo pop 2		0.0100	103	20_40_N_103_21_W
167	B*58:01	Mexico Mestizo	0.0	0.0000	41	19_24_N_99_9_W
168	B*58:01	Mexico Mexico City Mestizo pop 2		0.0064	234	19_26_N_99_8_W
169	B*58:01	Mexico Mexico City Mestizo population		0.0070	143	19_25_N_99_7_W
170	B*58:01	Mexico Mexico City Tlalpan	0.3	0.0015	330	19_25_N_99_8_W
171	B*58:01	Mexico Oaxaca Mixtec		0.0000	103	17_5_N_96_45_W
172	B*58:01	Mexico Oaxaca Zapotec		0.0220	90	17_5_N_96_45_W
173	B*58:01	Mexico Veracruz Xalapa	3.6	0.0179	84	19_32_N_96_55_W
174	B*58:01	Morocco Atlantic Coast Chaouya		0.0340	98	30_22_N_7_22_W
175	B*58:01	Morocco Nador Metalsa pop 2		0.0140	73	35_10_N_2_56_W
176	B*58:01	Morocco Settat Chaouya	6.8	0.0340	98	33_0_N_7_36_W
177	B*58:01	Netherlands Leiden		0.0060	1,305	52_9_N_4_31_E
178	B*58:01	New Zealand Maori with Admixed History	1.0	0.0050	105	42_0_S_174_0_E
179	B*58:01	Nicaragua Managua	3.6	0.0181	339	12_7_N_86_10_W
180	B*58:01	Oman	13.6	0.0680	118	22_0_N_56_0_E
181	B*58:01	Panama		0.0364	462	8_59_N_79_37_W
182	B*58:01	Poland		0.0100	200	51_7_N_17_2_E
183	B*58:01	Poland DKMS		0.0065	20,653	52_8_N_19_23_E
184	B*58:01	Portugal Azores Terceira Island	2.6	0.0132	130	38_43_N_27_13_W
185	B*58:01	Portugal Center		0.0200	50	39_0_N_8_0_W
186	B*58:01	Portugal North		0.0220	46	41_0_N_8_0_W
187	B*58:01	Portugal South		0.0200	49	37_0_N_8_0_W
188	B*58:01	Romania	2.6	0.0130	348	46_0_N_25_0_E
189	B*58:01	Russia Bering Island Aleuts		0.0048	104	55_0_N_166_15_E
190	B*58:01	Russia Karelia		0.0094	1,075	63_9_N_32_59_E
191	B*58:01	Russia Tuva pop 2		0.0670	169	51_30_N_95_5_E
192	B*58:01	Sao Tome Island Angolar		0.0470	32	0_20_N_6_44_E
193	B*58:01	Sao Tome Island Forro		0.0300	66	0_20_N_6_44_E
194	B*58:01	Saudi Arabia Guraiat and Hail	9.3	0.0460	213	27_31_N_41_41_E
195	B*58:01	Scotland Orkney	0.0	0.0000	99	58_59_N_3_11_W
196	B*58:01	Senegal Niokholo Mandenka		0.0690	165	12_35_N_12_9_W
197	B*58:01	Serbia pop 2	1.0	0.0050	102	44_13_N_20_47_E
198	B*58:01	Singapore Chinese	20.1	0.1040	149	1_24_N_103_45_E
199	B*58:01	Singapore Chinese Han		0.0580	94	1_17_N_103_51_E
200	B*58:01	Singapore Javaneses		0.0310	51	1_24_N_103_45_E
201	B*58:01	Singapore Riau Malay		0.0500	132	1_24_N_103_45_E
202	B*58:01	Singapore SGVP Chinese CHS		0.1400	96	1_21_N_103_50_E
203	B*58:01	Singapore SGVP Malay MAS		0.0480	89	1_21_N_103_50_E
204	B*58:01	Singapore SGVP. Indian INS		0.0310	86	1_21_N_103_50_E
205	B*58:01	Singapore Thai		0.0860	100	1_24_N_103_45_E
206	B*58:01	South Africa Caucasians		0.0260	102	30_0_S_25_0_E
207	B*58:01	South Africa Natal Tamil		0.0200	51	30_0_S_31_0_E
208	B*58:01	South Africa Natal Zulu	8.0	0.0400	100	29_0_S_31_0_E
209	B*58:01	South Africa Worcester	13.0	0.0720	159	33_39_S_19_27_E
210	B*58:01	South Korea pop 10		0.0608	4,128	37_33_N_126_58_E
211	B*58:01	South Korea pop 3		0.0650	485	37_33_N_126_59_E
212	B*58:01	Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria,	2.2	0.0110	4,335	41_22_N_2_11_E
213	B*58:01	Spain Andalusia		0.0120	99	37_22_N_5_59_W
214	B*58:01	Spain Catalonia Girona		0.0060	88	41_59_N_2_49_E
215	B*58:01	Spain Gipuzkoa Basque		0.0000	100	43_10_N_2_10_W
216	B*58:01	Spain Majorca and Minorca		0.0060	90	39_37_N_2_59_E
217	B*58:01	Sri Lanka Colombo	13.4	0.0720	714	6_56_N_79_50_E
218	B*58:01	Sudan East Rashaida	3.7		27	14_0_N_35_0_E
219	B*58:01	Sudan Mixed	9.0	0.0450	200	5_0_N_35_0_E
220	B*58:01	Switzerland Aargau-Solothurn		0.0081	1,838	46_48_N_8_13_E
221	B*58:01	Switzerland Basel		0.0421	1,888	47_33_N_7_34_E
222	B*58:01	Switzerland Bern		0.0103	3,545	46_57_N_7_27_E
223	B*58:01	Switzerland Geneva pop 2		0.0326	1,267	46_12_N_6_8_E
224	B*58:01	Switzerland Graubunden		0.0122	759	46_42_N_9_57_E
225	B*58:01	Switzerland Lausanne		0.0143	993	46_31_N_6_39_E
226	B*58:01	Switzerland Lugano		0.0240	1,169	46_0_N_8_55_E
227	B*58:01	Switzerland Luzern		0.0226	1,553	47_3_N_8_18_E
228	B*58:01	Switzerland Sion		0.0000	832	46_15_N_7_23_E
229	B*58:01	Switzerland St Gallen		0.0157	2,113	47_26_N_9_21_E
230	B*58:01	Switzerland Zurich		0.0207	4,875	47_22_N_8_32_E
231	B*58:01	Taiwan Hakka	21.8	0.1090	55	24_0_N_121_0_E
232	B*58:01	Taiwan Han Chinese		0.1060	504	23_46_N_121_0_E
233	B*58:01	Taiwan Minnan pop 1	16.7	0.0880	102	24_0_N_121_0_E
234	B*58:01	Taiwan Paiwan	2.0	0.0100	51	23_0_N_121_0_E
235	B*58:01	Taiwan Pazeh	7.3	0.0360	55	25_0_N_121_30_E
236	B*58:01	Taiwan pop 2		0.1000	364	23_46_N_121_0_E
237	B*58:01	Taiwan pop 3		0.1010	212	23_46_N_121_0_E
238	B*58:01	Taiwan Siraya	11.8	0.0590	51	24_0_N_121_0_E
239	B*58:01	Taiwan Thao	10.0	0.0500	30	24_0_N_121_0_E
240	B*58:01	Taiwan Tzu Chi Morrow Donor Registry		0.1183	46,682	25_2_N_121_38_E
241	B*58:01	Taiwan Tzu Chi Morrow Donor Registry Aborigine		0.0236	233	25_2_N_121_38_E
242	B*58:01	Taiwan Tzu Chi Cord Blood Bank		0.0980	710	23_46_N_121_0_E
243	B*58:01	Tanzania Maasai	6.0	0.0314	336	3_11_S_37_4_E
244	B*58:01	Thailand		0.0770	142	16_7_N_102_0_E
245	B*58:01	Thailand Northeast		0.0840	66	15_13_N_104_51_E
246	B*58:01	Thailand Northeast pop 2		0.0790	400	16_27_N_103_10_E
247	B*58:01	Thailand pop 3		0.0610	49	13_45_N_100_29_E
248	B*58:01	Tunisia	8.0	0.0400	100	35_0_N_9_0_E
249	B*58:01	Tunisia Gabes		0.0157	95	33_53_N_10_6_E
250	B*58:01	Tunisia Ghannouch		0.0370	82	33_3_N_10_20_E
251	B*58:01	Tunisia pop 3		0.0340	104	36_48_N_10_11_E
252	B*58:01	Uganda Kampala		0.0400	161	0_3_N_32_6_E
253	B*58:01	Uganda Kampala pop 2		0.0600	175	0_20_N_32_30_E
254	B*58:01	United Arab Emirates Abu Dhabi		0.0481	52	24_28_N_54_22_E
255	B*58:01	USA African American		0.0640	252	30_0_N_95_0_W
256	B*58:01	USA African American Bethesda	5.3	0.0260	187	38_0_N_78_0_W
257	B*58:01	USA African American pop 3		0.0320	564	38_53_N_77_2_W
258	B*58:01	USA African American pop 4		0.0351	2,411	44_58_N_93_15_W
259	B*58:01	USA African American pop 8		0.0360	605	39_24_N_77_25_W
260	B*58:01	USA Alaska Yupik		0.0000	252	60_48_N_161_26_W
261	B*58:01	USA Asian		0.0740	358	30_0_N_95_0_W
262	B*58:01	USA Asian pop 2		0.0577	1,772	44_58_N_93_15_W
263	B*58:01	USA Caucasian Bethesda	0.0	0.0000	307	38_0_N_78_0_W
264	B*58:01	USA Caucasian pop 2		0.0110	265	30_0_N_95_0_W
265	B*58:01	USA Caucasian pop 4		0.0102	1,070	38_53_N_77_2_W
266	B*58:01	USA Eastern European		0.0080	558	38_53_N_77_2_W
267	B*58:01	USA European American pop 2		0.0090	1,245	39_24_N_77_25_W
268	B*58:01	USA Hispanic		0.0110	234	30_0_N_95_0_W
269	B*58:01	USA Hispanic pop 2		0.0145	1,999	44_58_N_93_15_W
270	B*58:01	USA Italy Ancestry		0.0160	273	38_0_N_77_0_W
271	B*58:01	USA Mexican American Mestizo		0.0090	553	38_53_N_77_2_W
272	B*58:01	USA NMDP African		0.0425	28,557	38_45_N_76_6_W
273	B*58:01	USA NMDP African American pop 2		0.0378	416,581	38_45_N_76_6_W
274	B*58:01	USA NMDP Alaska Native or Aleut		0.0060	1,376	38_45_N_76_6_W
275	B*58:01	USA NMDP American Indian South or Central America		0.0100	5,926	38_45_N_76_6_W
276	B*58:01	USA NMDP Caribean Black		0.0405	33,328	38_45_N_76_6_W
277	B*58:01	USA NMDP Caribean Hispanic		0.0233	115,374	38_45_N_76_6_W
278	B*58:01	USA NMDP Caribean Indian		0.0260	14,339	38_45_N_76_6_W
279	B*58:01	USA NMDP Chinese		0.0874	99,672	38_45_N_76_6_W
280	B*58:01	USA NMDP European Caucasian		0.0073	1,242,890	38_45_N_76_6_W
281	B*58:01	USA NMDP Filipino		0.0404	50,614	38_45_N_76_6_W
282	B*58:01	USA NMDP Hawaiian or other Pacific Islander		0.0145	11,499	38_45_N_76_6_W
283	B*58:01	USA NMDP Hispanic South or Central American		0.0142	146,714	38_45_N_76_6_W
284	B*58:01	USA NMDP Japanese		0.0076	24,582	38_45_N_76_6_W
285	B*58:01	USA NMDP Korean		0.0603	77,584	38_45_N_76_6_W
286	B*58:01	USA NMDP Mexican or Chicano		0.0090	261,235	38_45_N_76_6_W
287	B*58:01	USA NMDP Middle Eastern or North Coast of Africa		0.0173	70,890	38_45_N_76_6_W
288	B*58:01	USA NMDP North American Amerindian		0.0070	35,791	38_45_N_76_6_W
289	B*58:01	USA NMDP South Asian Indian		0.0420	185,391	38_45_N_76_6_W
290	B*58:01	USA NMDP Southeast Asian		0.0478	27,978	38_45_N_76_6_W
291	B*58:01	USA NMDP Vietnamese		0.0692	43,540	38_45_N_76_6_W
292	B*58:01	USA North American Native		0.0080	187	30_0_N_95_0_W
293	B*58:01	USA Philadelphia Caucasian	3.7	0.0190	141	39_56_N_75_10_W
294	B*58:01	USA San Antonio Caucasian		0.0030	222	29_23_N_98_33_W
295	B*58:01	USA San Diego	2.6	0.0140	496	32_50_N_117_15_W
296	B*58:01	USA San Francisco Caucasian		0.0140	220	37_46_N_122_25_W
297	B*58:01	USA South Texas Hispanic		0.0040	194	29_0_N_98_0_W
298	B*58:01	USA Spain Ancestry		0.0200	279	38_0_N_77_0_W
299	B*58:01	Vietnam Hanoi Kinh pop 2		0.0650	170	21_2_N_105_51_E
300	B*58:01	Wales	1.0	0.0050	1,798	51_29_N_3_11_W
301	B*58:01	Zambia Lusaka		0.0000	44	15_25_S_28_17_E
302	B*58:01	Zimbabwe Harare Shona		0.0440	230	17_51_S_31_1_E

©2024 Allele Frequencies Website.

Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools
Gonzalez-Galarza FF, McCabe A, Santos EJ, Jones J, Takeshita LY, Ortega-Rivera ND, Del Cid-Pavon GM, Ramsbottom K, Ghattaoraya GS, Alfirevic A, Middleton D and Jones AR Nucleic Acid Research 2020, 48:D783-8.
Liverpool, U.K.

support@allelefrequencies.net