dbSNP Short Genetic Variations
Welcome to the Reference SNP (rs) Report
All alleles are reported in the Forward orientation. Click on the Variant Details tab for details on Genomic Placement, Gene, and Amino Acid changes. HGVS names are in the HGVS tab.
Reference SNP (rs) Report
This page reports data for a single dbSNP Reference SNP variation (RefSNP or rs) from the new redesigned dbSNP build.
Top of the page reports a concise summary for the rs, with more specific details included in the corresponding tabs below.
All alleles are reported in the Forward orientation. Use the Genomic View to inspect the nucleotides flanking the variant, and its neighbors.
For more information see Help documentation.
rs12777823
Current Build 157
Released September 3, 2024
- Organism
- Homo sapiens
- Position
-
chr10:94645745 (GRCh38.p14) Help
The anchor position for this RefSNP. Includes all nucleotides potentially affected by this change, thus it can differ from HGVS, which is right-shifted. See here for details.
- Alleles
- G>A / G>T
- Variation Type
- SNV Single Nucleotide Variation
- Frequency
-
A=0.185205 (49022/264690, TOPMED)A=0.163394 (22899/140146, ALFA)A=0.20911 (16457/78700, PAGE_STUDY) (+ 23 more)
- Clinical Significance
- Reported in ClinVar
- Gene : Consequence
-
None
- Publications
- 22 citations
- Genomic View
- See rs on genome
ALFA Allele Frequency
The ALFA project provide aggregate allele frequency from dbGaP. More information is available on the project page including descriptions, data access, and terms of use.
| Population | Group | Sample Size | Ref Allele | Alt Allele | Ref HMOZ | Alt HMOZ | HTRZ | HWEP |
|---|---|---|---|---|---|---|---|---|
| Total | Global | 140146 | G=0.836606 | A=0.163394 | 0.70261 | 0.029398 | 0.267992 | 15 |
| European | Sub | 113804 | G=0.847817 | A=0.152183 | 0.720115 | 0.024481 | 0.255404 | 4 |
| African | Sub | 7164 | G=0.7559 | A=0.2441 | 0.57091 | 0.059185 | 0.369905 | 0 |
| African Others | Sub | 212 | G=0.731 | A=0.269 | 0.537736 | 0.075472 | 0.386792 | 0 |
| African American | Sub | 6952 | G=0.7566 | A=0.2434 | 0.571922 | 0.058688 | 0.36939 | 0 |
| Asian | Sub | 3248 | G=0.6733 | A=0.3267 | 0.449507 | 0.102833 | 0.44766 | 0 |
| East Asian | Sub | 1994 | G=0.6710 | A=0.3290 | 0.44333 | 0.101304 | 0.455366 | 1 |
| Other Asian | Sub | 1254 | G=0.6770 | A=0.3230 | 0.45933 | 0.105263 | 0.435407 | 0 |
| Latin American 1 | Sub | 314 | G=0.834 | A=0.166 | 0.700637 | 0.031847 | 0.267516 | 0 |
| Latin American 2 | Sub | 2824 | G=0.8778 | A=0.1222 | 0.771955 | 0.016289 | 0.211756 | 0 |
| South Asian | Sub | 134 | G=0.627 | A=0.373 | 0.432836 | 0.179104 | 0.38806 | 1 |
| Other | Sub | 12658 | G=0.81648 | A=0.18352 | 0.672144 | 0.039185 | 0.288671 | 5 |
Frequency tab displays a table of the reference and alternate allele frequencies reported by various studies and populations. Table lines, where Population="Global" refer to the entire study population, whereas lines, where Group="Sub", refer to a study-specific population subgroupings (i.e. AFR, CAU, etc.), if available. Frequency for the alternate allele (Alt Allele) is a ratio of samples observed-to-total, where the numerator (observed samples) is the number of chromosomes in the study with the minor allele present (found in "Sample size", where Group="Sub"), and the denominator (total samples) is the total number of all chromosomes in the study for the variant (found in "Sample size", where Group="Study-wide" and Population="Global").
Download| Study | Population | Group | Sample Size | Ref Allele | Alt Allele |
|---|---|---|---|---|---|
| TopMed | Global | Study-wide | 264690 | G=0.814795 | A=0.185205 |
| Allele Frequency Aggregator | Total | Global | 140146 | G=0.836606 | A=0.163394 |
| Allele Frequency Aggregator | European | Sub | 113804 | G=0.847817 | A=0.152183 |
| Allele Frequency Aggregator | Other | Sub | 12658 | G=0.81648 | A=0.18352 |
| Allele Frequency Aggregator | African | Sub | 7164 | G=0.7559 | A=0.2441 |
| Allele Frequency Aggregator | Asian | Sub | 3248 | G=0.6733 | A=0.3267 |
| Allele Frequency Aggregator | Latin American 2 | Sub | 2824 | G=0.8778 | A=0.1222 |
| Allele Frequency Aggregator | Latin American 1 | Sub | 314 | G=0.834 | A=0.166 |
| Allele Frequency Aggregator | South Asian | Sub | 134 | G=0.627 | A=0.373 |
| The PAGE Study | Global | Study-wide | 78700 | G=0.79089 | A=0.20911 |
| The PAGE Study | AfricanAmerican | Sub | 32516 | G=0.75292 | A=0.24708 |
| The PAGE Study | Mexican | Sub | 10808 | G=0.87491 | A=0.12509 |
| The PAGE Study | Asian | Sub | 8318 | G=0.6974 | A=0.3026 |
| The PAGE Study | PuertoRican | Sub | 7918 | G=0.8471 | A=0.1529 |
| The PAGE Study | NativeHawaiian | Sub | 4534 | G=0.7925 | A=0.2075 |
| The PAGE Study | Cuban | Sub | 4230 | G=0.8473 | A=0.1527 |
| The PAGE Study | Dominican | Sub | 3828 | G=0.8028 | A=0.1972 |
| The PAGE Study | CentralAmerican | Sub | 2450 | G=0.8988 | A=0.1012 |
| The PAGE Study | SouthAmerican | Sub | 1982 | G=0.8764 | A=0.1236 |
| The PAGE Study | NativeAmerican | Sub | 1260 | G=0.8389 | A=0.1611 |
| The PAGE Study | SouthAsian | Sub | 856 | G=0.644 | A=0.356 |
| 38KJPN | JAPANESE | Study-wide | 77442 | G=0.69887 | A=0.30113 |
| Korean Genome Project 4K | KOREAN | Study-wide | 7234 | G=0.7221 | A=0.2779 |
| 1000Genomes_30X | Global | Study-wide | 6404 | G=0.7587 | A=0.2413 |
| 1000Genomes_30X | African | Sub | 1786 | G=0.7576 | A=0.2424 |
| 1000Genomes_30X | Europe | Sub | 1266 | G=0.8507 | A=0.1493 |
| 1000Genomes_30X | South Asian | Sub | 1202 | G=0.6398 | A=0.3602 |
| 1000Genomes_30X | East Asian | Sub | 1170 | G=0.6752 | A=0.3248 |
| 1000Genomes_30X | American | Sub | 980 | G=0.888 | A=0.112 |
| 1000Genomes | Global | Study-wide | 5008 | G=0.7546 | A=0.2454 |
| 1000Genomes | African | Sub | 1322 | G=0.7489 | A=0.2511 |
| 1000Genomes | East Asian | Sub | 1008 | G=0.6855 | A=0.3145 |
| 1000Genomes | Europe | Sub | 1006 | G=0.8489 | A=0.1511 |
| 1000Genomes | South Asian | Sub | 978 | G=0.638 | A=0.362 |
| 1000Genomes | American | Sub | 694 | G=0.893 | A=0.107 |
| Genetic variation in the Estonian population | Estonian | Study-wide | 4480 | G=0.8647 | A=0.1353 |
| The Avon Longitudinal Study of Parents and Children | PARENT AND CHILD COHORT | Study-wide | 3854 | G=0.8456 | A=0.1544 |
| UK 10K study - Twins | TWIN COHORT | Study-wide | 3708 | G=0.8433 | A=0.1567 |
| KOREAN population from KRGDB | KOREAN | Study-wide | 2930 | G=0.7239 | A=0.2761 |
| HapMap | Global | Study-wide | 1892 | G=0.7643 | A=0.2357 |
| HapMap | American | Sub | 770 | G=0.787 | A=0.213 |
| HapMap | African | Sub | 692 | G=0.741 | A=0.259 |
| HapMap | Asian | Sub | 254 | G=0.669 | A=0.331 |
| HapMap | Europe | Sub | 176 | G=0.892 | A=0.108 |
| Korean Genome Project | KOREAN | Study-wide | 1832 | G=0.7145 | A=0.2855 |
| Genome-wide autozygosity in Daghestan | Global | Study-wide | 1136 | G=0.8283 | A=0.1717 |
| Genome-wide autozygosity in Daghestan | Daghestan | Sub | 628 | G=0.861 | A=0.139 |
| Genome-wide autozygosity in Daghestan | Near_East | Sub | 144 | G=0.868 | A=0.132 |
| Genome-wide autozygosity in Daghestan | Central Asia | Sub | 122 | G=0.844 | A=0.156 |
| Genome-wide autozygosity in Daghestan | Europe | Sub | 108 | G=0.824 | A=0.176 |
| Genome-wide autozygosity in Daghestan | South Asian | Sub | 98 | G=0.50 | A=0.50 |
| Genome-wide autozygosity in Daghestan | Caucasus | Sub | 36 | G=0.94 | A=0.06 |
| Genome of the Netherlands Release 5 | Genome of the Netherlands | Study-wide | 998 | G=0.853 | A=0.147 |
| CNV burdens in cranial meningiomas | Global | Study-wide | 788 | G=0.714 | A=0.286 |
| CNV burdens in cranial meningiomas | CRM | Sub | 788 | G=0.714 | A=0.286 |
| Chileans | Chilean | Study-wide | 626 | G=0.893 | A=0.107 |
| Northern Sweden | ACPOP | Study-wide | 600 | G=0.853 | A=0.147 |
| Medical Genome Project healthy controls from Spanish population | Spanish controls | Study-wide | 534 | G=0.863 | A=0.137 |
| Qatari | Global | Study-wide | 216 | G=0.875 | A=0.125 |
| A Vietnamese Genetic Variation Database | Global | Study-wide | 216 | G=0.690 | A=0.310 |
| SGDP_PRJ | Global | Study-wide | 182 | G=0.385 | A=0.615 |
| Ancient Sardinia genome-wide 1240k capture data generation and analysis | Global | Study-wide | 62 | G=0.81 | A=0.19 |
| The Danish reference pan genome | Danish | Study-wide | 40 | G=0.82 | A=0.17 |
| Siberian | Global | Study-wide | 14 | G=0.50 | A=0.50 |
Variant Details tab shows known variant placements on genomic sequences: chromosomes (NC_), RefSeqGene, pseudogenes or genomic regions (NG_), and in a separate table: on transcripts (NM_) and protein sequences (NP_). The corresponding transcript and protein locations are listed in adjacent lines, along with molecular consequences from Sequence Ontology. When no protein placement is available, only the transcript is listed. Column "Codon[Amino acid]" shows the actual base change in the format of "Reference > Alternate" allele, including the nucleotide codon change in transcripts, and the amino acid change in proteins, respectively, allowing for known ribosomal slippage sites. To view nucleotides adjacent to the variant use the Genomic View at the bottom of the page - zoom into the sequence until the nucleotides around the variant become visible.
| Sequence name | Change |
|---|---|
| GRCh38.p14 chr 10 | NC_000010.11:g.94645745G>A |
| GRCh38.p14 chr 10 | NC_000010.11:g.94645745G>T |
| GRCh37.p13 chr 10 | NC_000010.10:g.96405502G>A |
| GRCh37.p13 chr 10 | NC_000010.10:g.96405502G>T |
Clinical Significance tab shows a list of clinical significance entries from ClinVar associated with the variation, per allele. Click on the RCV accession (i.e. RCV000001615.2) or Allele ID (i.e. 12274) to access full ClinVar report.
| ClinVar Accession | Disease Names | Clinical Significance |
|---|---|---|
| RCV000211190.3 | warfarin response - Dosage | Drug-Response |
Aliases tab displays HGVS names representing the variant placements and allele changes on genomic, transcript and protein sequences, per allele. HGVS name is an expression for reporting sequence accession and version, sequence type, position, and allele change. The column "Note" can have two values: "diff" means that there is a difference between the reference allele (variation interval) at the placement reported in HGVS name and the reference alleles reported in other HGVS names, and "rev" means that the sequence of this variation interval at the placement reported in HGVS name is in reverse orientation to the sequence(s) of this variation in other HGVS names not labeled as "rev".
| Placement | G= | A | T |
|---|---|---|---|
| GRCh38.p14 chr 10 | NC_000010.11:g.94645745= | NC_000010.11:g.94645745G>A | NC_000010.11:g.94645745G>T |
| GRCh37.p13 chr 10 | NC_000010.10:g.96405502= | NC_000010.10:g.96405502G>A | NC_000010.10:g.96405502G>T |
Submissions tab displays variations originally submitted to dbSNP, now supporting this RefSNP cluster (rs). We display Submitter handle, Submission identifier, Date and Build number, when the submission appeared for the first time. Direct submissions to dbSNP have Submission ID in the form of an ss-prefixed number (ss#). Other supporting variations are listed in the table without ss#.
| No | Submitter | Submission ID | Date (Build) |
|---|---|---|---|
| 1 | SSAHASNP | ss20698542 | Apr 05, 2004 (121) |
| 2 | PERLEGEN | ss23586501 | Sep 20, 2004 (123) |
| 3 | ABI | ss39757121 | Mar 15, 2006 (126) |
| 4 | AFFY | ss66325057 | Dec 02, 2006 (127) |
| 5 | AFFY | ss76017151 | Dec 08, 2007 (130) |
| 6 | KRIBB_YJKIM | ss83017592 | Dec 15, 2007 (130) |
| 7 | HUMANGENOME_JCVI | ss97675547 | Feb 05, 2009 (130) |
| 8 | 1000GENOMES | ss109667708 | Jan 24, 2009 (130) |
| 9 | ILLUMINA-UK | ss119274995 | Feb 15, 2009 (130) |
| 10 | ILLUMINA | ss161036297 | Dec 01, 2009 (131) |
| 11 | AFFY | ss170463971 | Jul 04, 2010 (132) |
| 12 | BUSHMAN | ss201884219 | Jul 04, 2010 (132) |
| 13 | 1000GENOMES | ss224883819 | Jul 14, 2010 (132) |
| 14 | 1000GENOMES | ss235292338 | Jul 15, 2010 (132) |
| 15 | 1000GENOMES | ss241975630 | Jul 15, 2010 (132) |
| 16 | GMI | ss280731973 | May 04, 2012 (137) |
| 17 | PJP | ss290909093 | May 09, 2011 (134) |
| 18 | ILLUMINA | ss479460554 | Sep 08, 2015 (146) |
| 19 | EXOME_CHIP | ss491438575 | May 04, 2012 (137) |
| 20 | TISHKOFF | ss562142472 | Apr 25, 2013 (138) |
| 21 | SSMP | ss657182520 | Apr 25, 2013 (138) |
| 22 | ILLUMINA | ss780681616 | Sep 08, 2015 (146) |
| 23 | ILLUMINA | ss783354943 | Sep 08, 2015 (146) |
| 24 | EVA-GONL | ss987803354 | Aug 21, 2014 (142) |
| 25 | JMKIDD_LAB | ss1077214623 | Aug 21, 2014 (142) |
| 26 | 1000GENOMES | ss1338619334 | Aug 21, 2014 (142) |
| 27 | HAMMER_LAB | ss1397589404 | Sep 08, 2015 (146) |
| 28 | DDI | ss1426410921 | Apr 01, 2015 (144) |
| 29 | EVA_GENOME_DK | ss1575296434 | Apr 01, 2015 (144) |
| 30 | EVA_DECODE | ss1597476677 | Apr 01, 2015 (144) |
| 31 | EVA_UK10K_ALSPAC | ss1625193872 | Apr 01, 2015 (144) |
| 32 | EVA_UK10K_TWINSUK | ss1668187905 | Apr 01, 2015 (144) |
| 33 | EVA_MGP | ss1711265718 | Apr 01, 2015 (144) |
| 34 | EVA_SVP | ss1713202577 | Apr 01, 2015 (144) |
| 35 | ILLUMINA | ss1751988195 | Sep 08, 2015 (146) |
| 36 | ILLUMINA | ss1917849802 | Feb 12, 2016 (147) |
| 37 | WEILL_CORNELL_DGM | ss1931169381 | Feb 12, 2016 (147) |
| 38 | ILLUMINA | ss1946289727 | Feb 12, 2016 (147) |
| 39 | ILLUMINA | ss1959284858 | Feb 12, 2016 (147) |
| 40 | GENOMED | ss1967199754 | Jul 19, 2016 (147) |
| 41 | JJLAB | ss2026313235 | Sep 14, 2016 (149) |
| 42 | USC_VALOUEV | ss2154589764 | Nov 08, 2017 (151) |
| 43 | HUMAN_LONGEVITY | ss2177141201 | Dec 20, 2016 (150) |
| 44 | SYSTEMSBIOZJU | ss2627625482 | Nov 08, 2017 (151) |
| 45 | ILLUMINA | ss2632748258 | Nov 08, 2017 (151) |
| 46 | ILLUMINA | ss2632748259 | Nov 08, 2017 (151) |
| 47 | GRF | ss2698842440 | Nov 08, 2017 (151) |
| 48 | ILLUMINA | ss2710717494 | Nov 08, 2017 (151) |
| 49 | GNOMAD | ss2892116922 | Nov 08, 2017 (151) |
| 50 | AFFY | ss2984919951 | Nov 08, 2017 (151) |
| 51 | AFFY | ss2985568262 | Nov 08, 2017 (151) |
| 52 | SWEGEN | ss3006964297 | Nov 08, 2017 (151) |
| 53 | ILLUMINA | ss3021264790 | Nov 08, 2017 (151) |
| 54 | BIOINF_KMB_FNS_UNIBA | ss3026946743 | Nov 08, 2017 (151) |
| 55 | CSHL | ss3349260889 | Nov 08, 2017 (151) |
| 56 | ILLUMINA | ss3626509738 | Oct 12, 2018 (152) |
| 57 | ILLUMINA | ss3634417737 | Oct 12, 2018 (152) |
| 58 | ILLUMINA | ss3636101741 | Oct 12, 2018 (152) |
| 59 | ILLUMINA | ss3640125078 | Oct 12, 2018 (152) |
| 60 | ILLUMINA | ss3644542474 | Oct 12, 2018 (152) |
| 61 | URBANLAB | ss3649441365 | Oct 12, 2018 (152) |
| 62 | ILLUMINA | ss3651623213 | Oct 12, 2018 (152) |
| 63 | ILLUMINA | ss3653690682 | Oct 12, 2018 (152) |
| 64 | EGCUT_WGS | ss3674376527 | Jul 13, 2019 (153) |
| 65 | EVA_DECODE | ss3690460107 | Jul 13, 2019 (153) |
| 66 | ILLUMINA | ss3725179408 | Jul 13, 2019 (153) |
| 67 | ACPOP | ss3737584699 | Jul 13, 2019 (153) |
| 68 | ILLUMINA | ss3744369891 | Jul 13, 2019 (153) |
| 69 | ILLUMINA | ss3744718709 | Jul 13, 2019 (153) |
| 70 | EVA | ss3748467120 | Jul 13, 2019 (153) |
| 71 | PAGE_CC | ss3771575682 | Jul 13, 2019 (153) |
| 72 | ILLUMINA | ss3772219066 | Jul 13, 2019 (153) |
| 73 | KHV_HUMAN_GENOMES | ss3813833205 | Jul 13, 2019 (153) |
| 74 | EVA | ss3832276570 | Apr 26, 2020 (154) |
| 75 | EVA | ss3839679393 | Apr 26, 2020 (154) |
| 76 | EVA | ss3845153057 | Apr 26, 2020 (154) |
| 77 | SGDP_PRJ | ss3874825507 | Apr 26, 2020 (154) |
| 78 | KRGDB | ss3922953342 | Apr 26, 2020 (154) |
| 79 | KOGIC | ss3968456535 | Apr 26, 2020 (154) |
| 80 | EVA | ss3984639013 | Apr 26, 2021 (155) |
| 81 | EVA | ss3985493272 | Apr 26, 2021 (155) |
| 82 | TOPMED | ss4862591405 | Apr 26, 2021 (155) |
| 83 | TOMMO_GENOMICS | ss6114192319 | Nov 01, 2024 (157) |
| 84 | EVA | ss6253822408 | Nov 01, 2024 (157) |
| 85 | EVA | ss6307408030 | Nov 01, 2024 (157) |
| 86 | EVA | ss6321979690 | Nov 01, 2024 (157) |
| 87 | EVA | ss6322395558 | Nov 01, 2024 (157) |
| 88 | EVA | ss6326442447 | Nov 01, 2024 (157) |
| 89 | EVA | ss6332060309 | Nov 01, 2024 (157) |
| 90 | YEGNASUBRAMANIAN_LAB | ss6343186645 | Nov 01, 2024 (157) |
| 91 | EVA | ss6349787508 | Nov 01, 2024 (157) |
| 92 | KOGIC | ss6382286549 | Nov 01, 2024 (157) |
| 93 | GNOMAD | ss6859847257 | Nov 01, 2024 (157) |
| 94 | GNOMAD | ss6859847258 | Nov 01, 2024 (157) |
| 95 | TOMMO_GENOMICS | ss8198964834 | Nov 01, 2024 (157) |
| 96 | EVA | ss8237481878 | Nov 01, 2024 (157) |
| 97 | 1000G_HIGH_COVERAGE | ss8285084495 | Nov 01, 2024 (157) |
| 98 | EVA | ss8315494458 | Nov 01, 2024 (157) |
| 99 | EVA | ss8395317594 | Nov 01, 2024 (157) |
| 100 | HUGCELL_USP | ss8480545135 | Nov 01, 2024 (157) |
| 101 | EVA | ss8510128841 | Nov 01, 2024 (157) |
| 102 | 1000G_HIGH_COVERAGE | ss8579559459 | Nov 01, 2024 (157) |
| 103 | SANFORD_IMAGENETICS | ss8624255679 | Nov 01, 2024 (157) |
| 104 | SANFORD_IMAGENETICS | ss8649883944 | Nov 01, 2024 (157) |
| 105 | TOMMO_GENOMICS | ss8745181279 | Nov 01, 2024 (157) |
| 106 | YY_MCH | ss8811791499 | Nov 01, 2024 (157) |
| 107 | EVA | ss8824806353 | Nov 01, 2024 (157) |
| 108 | EVA | ss8847378099 | Nov 01, 2024 (157) |
| 109 | EVA | ss8847605578 | Nov 01, 2024 (157) |
| 110 | EVA | ss8849696820 | Nov 01, 2024 (157) |
| 111 | EVA | ss8880081982 | Nov 01, 2024 (157) |
| 112 | EVA | ss8941170343 | Nov 01, 2024 (157) |
| 113 | EVA | ss8979335290 | Nov 01, 2024 (157) |
| 114 | EVA | ss8981728016 | Nov 01, 2024 (157) |
| 115 | EVA | ss8981728017 | Nov 01, 2024 (157) |
| 116 | EVA | ss8982151796 | Nov 01, 2024 (157) |
| 117 | 1000Genomes | NC_000010.10 - 96405502 | Oct 12, 2018 (152) |
| 118 | 1000Genomes_30X | NC_000010.11 - 94645745 | Nov 01, 2024 (157) |
| 119 | The Avon Longitudinal Study of Parents and Children | NC_000010.10 - 96405502 | Oct 12, 2018 (152) |
| 120 | Chileans | NC_000010.10 - 96405502 | Apr 26, 2020 (154) |
| 121 | Genome-wide autozygosity in Daghestan | NC_000010.9 - 96395492 | Apr 26, 2020 (154) |
| 122 | Genetic variation in the Estonian population | NC_000010.10 - 96405502 | Oct 12, 2018 (152) |
| 123 | The Danish reference pan genome | NC_000010.10 - 96405502 | Apr 26, 2020 (154) |
| 124 |
gnomAD v4 - Genomes
Submission ignored due to conflicting rows: |
- | Nov 01, 2024 (157) |
| 125 |
gnomAD v4 - Genomes
Submission ignored due to conflicting rows: |
- | Nov 01, 2024 (157) |
| 126 | Genome of the Netherlands Release 5 | NC_000010.10 - 96405502 | Apr 26, 2020 (154) |
| 127 | HapMap | NC_000010.11 - 94645745 | Apr 26, 2020 (154) |
| 128 | KOREAN population from KRGDB | NC_000010.10 - 96405502 | Apr 26, 2020 (154) |
| 129 | Korean Genome Project | NC_000010.11 - 94645745 | Apr 26, 2020 (154) |
| 130 | Korean Genome Project 4K | NC_000010.11 - 94645745 | Nov 01, 2024 (157) |
| 131 | Medical Genome Project healthy controls from Spanish population | NC_000010.10 - 96405502 | Apr 26, 2020 (154) |
| 132 | Northern Sweden | NC_000010.10 - 96405502 | Jul 13, 2019 (153) |
| 133 | The PAGE Study | NC_000010.11 - 94645745 | Jul 13, 2019 (153) |
| 134 | Ancient Sardinia genome-wide 1240k capture data generation and analysis | NC_000010.10 - 96405502 | Apr 26, 2021 (155) |
| 135 | CNV burdens in cranial meningiomas | NC_000010.10 - 96405502 | Apr 26, 2021 (155) |
| 136 | Qatari | NC_000010.10 - 96405502 | Apr 26, 2020 (154) |
| 137 | SGDP_PRJ | NC_000010.10 - 96405502 | Apr 26, 2020 (154) |
| 138 | Siberian | NC_000010.10 - 96405502 | Apr 26, 2020 (154) |
| 139 | 38KJPN | NC_000010.11 - 94645745 | Nov 01, 2024 (157) |
| 140 | TopMed | NC_000010.11 - 94645745 | Apr 26, 2021 (155) |
| 141 | UK 10K study - Twins | NC_000010.10 - 96405502 | Oct 12, 2018 (152) |
| 142 | A Vietnamese Genetic Variation Database | NC_000010.10 - 96405502 | Jul 13, 2019 (153) |
| 143 | ALFA | NC_000010.11 - 94645745 | Nov 01, 2024 (157) |
| 144 | ClinVar | RCV000211190.3 | Oct 16, 2022 (156) |
History tab displays RefSNPs (Associated ID) from previous builds (Build) that now support the current RefSNP, and the dates, when the history was updated for each Associated ID (History Updated).
| Associated ID | History Updated (Build) |
|---|---|
| rs56463295 | May 24, 2008 (130) |
| rs59201782 | Feb 26, 2009 (130) |
| Submission IDs | Observation SPDI | Canonical SPDI | Source RSIDs |
|---|---|---|---|
| 60834, ss66325057, ss76017151, ss109667708, ss119274995, ss170463971, ss201884219, ss280731973, ss290909093, ss1397589404, ss1597476677, ss1713202577 | NC_000010.9:96395491:G:A | NC_000010.11:94645744:G:A | (self) |
| 51050646, 28343235, 58357, 20114775, 2282514, 12638232, 30130736, 381478, 10869564, 719199, 188478, 13211311, 26842487, 7106118, 28343235, 6293878, ss224883819, ss235292338, ss241975630, ss479460554, ss491438575, ss562142472, ss657182520, ss780681616, ss783354943, ss987803354, ss1077214623, ss1338619334, ss1426410921, ss1575296434, ss1625193872, ss1668187905, ss1711265718, ss1751988195, ss1917849802, ss1931169381, ss1946289727, ss1959284858, ss1967199754, ss2026313235, ss2154589764, ss2627625482, ss2632748258, ss2632748259, ss2698842440, ss2710717494, ss2892116922, ss2984919951, ss2985568262, ss3006964297, ss3021264790, ss3349260889, ss3626509738, ss3634417737, ss3636101741, ss3640125078, ss3644542474, ss3651623213, ss3653690682, ss3674376527, ss3737584699, ss3744369891, ss3744718709, ss3748467120, ss3772219066, ss3832276570, ss3839679393, ss3874825507, ss3922953342, ss3984639013, ss3985493272, ss6253822408, ss6307408030, ss6322395558, ss6326442447, ss6332060309, ss6343186645, ss6349787508, ss8198964834, ss8237481878, ss8315494458, ss8395317594, ss8510128841, ss8624255679, ss8649883944, ss8824806353, ss8847378099, ss8847605578, ss8941170343, ss8979335290, ss8981728016, ss8981728017, ss8982151796 | NC_000010.10:96405501:G:A | NC_000010.11:94645744:G:A | (self) |
| RCV000211190.3, 67085394, 468056, 24834536, 32138447, 797151, 131568139, 78137060, 8397723188, ss2177141201, ss3026946743, ss3649441365, ss3690460107, ss3725179408, ss3771575682, ss3813833205, ss3845153057, ss3968456535, ss4862591405, ss6114192319, ss6321979690, ss6382286549, ss6859847257, ss8285084495, ss8480545135, ss8579559459, ss8745181279, ss8811791499, ss8849696820, ss8880081982 | NC_000010.11:94645744:G:A | NC_000010.11:94645744:G:A | (self) |
| ss20698542 | NT_030059.11:15154027:G:A | NC_000010.11:94645744:G:A | (self) |
| ss23586501, ss39757121, ss83017592, ss97675547, ss161036297 | NT_030059.13:47209965:G:A | NC_000010.11:94645744:G:A | (self) |
| ss6859847258 | NC_000010.11:94645744:G:T | NC_000010.11:94645744:G:T | (self) |
Publications tab displays PubMed articles citing the variation as a listing of PMID, Title, Author, Year, Journal, ordered by Year, descending.
| PMID | Title | Author | Year | Journal |
|---|---|---|---|---|
| 19706858 | Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. | Shuldiner AR et al. | 2009 | JAMA |
| 20440227 | Clopidogrel pathway. | Sangkuhl K et al. | 2010 | Pharmacogenetics and genomics |
| 22992668 | Pharmacogenomics knowledge for personalized medicine. | Whirl-Carrillo M et al. | 2012 | Clinical pharmacology and therapeutics |
| 23755828 | Genetic variants associated with warfarin dose in African-American individuals: a genome-wide association study. | Perera MA et al. | 2013 | Lancet (London, England) |
| 24018621 | Ethnicity-specific pharmacogenetics: the case of warfarin in African Americans. | Hernandez W et al. | 2014 | The pharmacogenomics journal |
| 24944790 | Screening for 392 polymorphisms in 141 pharmacogenes. | Kim JY et al. | 2014 | Biomedical reports |
| 25461246 | Poor warfarin dose prediction with pharmacogenetic algorithms that exclude genotypes important for African Americans. | Drozda K et al. | 2015 | Pharmacogenetics and genomics |
| 26024874 | Race influences warfarin dose changes associated with genetic factors. | Limdi NA et al. | 2015 | Blood |
| 26355760 | Pharmacogenetic-guided Warfarin Dosing Algorithm in African-Americans. | Alzubiedi S et al. | 2016 | Journal of cardiovascular pharmacology |
| 26369774 | Impact of New Genomic Technologies on Understanding Adverse Drug Reactions. | Maggo SD et al. | 2016 | Clinical pharmacokinetics |
| 28198005 | Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Pharmacogenetics-Guided Warfarin Dosing: 2017 Update. | Johnson JA et al. | 2017 | Clinical pharmacology and therapeutics |
| 29218998 | VKORC1-1639A allele influences warfarin maintenance dosage among Blacks receiving warfarin anticoagulation: a retrospective cohort study. | Mili FD et al. | 2018 | Future cardiology |
| 30566377 | Warfarin Dose and CYP2C Gene Cluster: An African Ancestral-Specific Variant Is a Strong Predictor of Dose in Black South African Patients. | Ndadza A et al. | 2019 | Omics |
| 30758238 | Development and Cross-Validation of High-Resolution Melting Analysis-Based Cardiovascular Pharmacogenetics Genotyping Panel. | Langaee T et al. | 2019 | Genetic testing and molecular biomarkers |
| 31869433 | Genetic Factors Influencing Warfarin Dose in Black-African Patients: A Systematic Review and Meta-Analysis. | Asiimwe IG et al. | 2020 | Clinical pharmacology and therapeutics |
| 32380173 | Recommendations for Clinical Warfarin Genotyping Allele Selection: A Report of the Association for Molecular Pathology and the College of American Pathologists. | Pratt VM et al. | 2020 | The Journal of molecular diagnostics |
| 33278335 | Implications of Polymorphisms in the BCKDK and GATA-4 Gene Regions on Stable Warfarin Dose in African Americans. | Bargal SA et al. | 2021 | Clinical and translational science |
| 34020041 | Characterization of Reference Materials with an Association for Molecular Pathology Pharmacogenetics Working Group Tier 2 Status: CYP2C9, CYP2C19, VKORC1, CYP2C Cluster Variant, and GGCX: A GeT-RM Collaborative Project. | Pratt VM et al. | 2021 | The Journal of molecular diagnostics |
| 34382722 | Profiling of warfarin pharmacokinetics-associated genetic variants: Black Africans portray unique genetic markers important for an African specific warfarin pharmacogenetics-dosing algorithm. | Ndadza A et al. | 2021 | Journal of thrombosis and haemostasis |
| 34415683 | Pharmacogenomic polygenic risk score for clopidogrel responsiveness among Caribbean Hispanics: A candidate gene approach. | Duconge J et al. | 2021 | Clinical and translational science |
| 34958284 | Warfarin Pharmacogenomics for Precision Medicine in Real-Life Clinical Practice in Southern Africa: Harnessing 73 Variants in 29 Pharmacogenes. | Muyambo S et al. | 2022 | Omics |
| 36210801 | A genome-wide association study of plasma concentrations of warfarin enantiomers and metabolites in sub-Saharan black-African patients. | Asiimwe IG et al. | 2022 | Frontiers in pharmacology |
The Flanks tab provides retrieving flanking sequences of a SNP on all molecules that have placements.
Genomic regions, transcripts, and products
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NCBI Graphical Sequence Viewer display of the genomic region, transcripts and protein products for the reported RefSNP (rs).
Use the zoom option to view the nucleotides around the RefSNP and find other neighboring RefSNPs.
Visit Sequence Viewer for help with navigating inside the display and modifying the selection of displayed data tracks.
NCBI Graphical Sequence Viewer display of the genomic region, transcripts and protein products for the reported RefSNP (rs).
Use the zoom option to view the nucleotides around the RefSNP and find other neighboring RefSNPs.
Visit Sequence Viewer for help with navigating inside the display and modifying the selection of displayed data tracks.