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.
rs2242480
Current Build 157
Released September 3, 2024
- Organism
- Homo sapiens
- Position
-
chr7:99763843 (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
- C>T
- Variation Type
- SNV Single Nucleotide Variation
- Frequency
-
T=0.1352079 (189412/1400894, GnomAD_exomes)T=0.347168 (91892/264690, TOPMED)T=0.312078 (46524/149078, GnomAD_genomes) (+ 23 more)
- Clinical Significance
- Reported in ClinVar
- Gene : Consequence
- CYP3A4 : Intron Variant
- Publications
- 67 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.
Release Version: 20231103111315
| Population | Group | Sample Size | Ref Allele | Alt Allele | Ref HMOZ | Alt HMOZ | HTRZ | HWEP |
|---|---|---|---|---|---|---|---|---|
| Total | Global | 46152 | C=0.84499 | T=0.15501 | 0.744843 | 0.054862 | 0.200295 | 32 |
| European | Sub | 37068 | C=0.90523 | T=0.09477 | 0.818819 | 0.008363 | 0.172818 | 1 |
| African | Sub | 3730 | C=0.3236 | T=0.6764 | 0.1437 | 0.496515 | 0.359786 | 31 |
| African Others | Sub | 132 | C=0.136 | T=0.864 | 0.015152 | 0.742424 | 0.242424 | 0 |
| African American | Sub | 3598 | C=0.3305 | T=0.6695 | 0.148416 | 0.487493 | 0.364091 | 30 |
| Asian | Sub | 212 | C=0.679 | T=0.321 | 0.471698 | 0.113208 | 0.415094 | 0 |
| East Asian | Sub | 156 | C=0.712 | T=0.288 | 0.525641 | 0.102564 | 0.371795 | 0 |
| Other Asian | Sub | 56 | C=0.59 | T=0.41 | 0.321429 | 0.142857 | 0.535714 | 0 |
| Latin American 1 | Sub | 156 | C=0.718 | T=0.282 | 0.538462 | 0.102564 | 0.358974 | 1 |
| Latin American 2 | Sub | 678 | C=0.661 | T=0.339 | 0.480826 | 0.159292 | 0.359882 | 8 |
| South Asian | Sub | 120 | C=0.633 | T=0.367 | 0.383333 | 0.116667 | 0.5 | 0 |
| Other | Sub | 4188 | C=0.8252 | T=0.1748 | 0.700096 | 0.049666 | 0.250239 | 20 |
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 |
|---|---|---|---|---|---|
| gnomAD v4 - Exomes | Global | Study-wide | 1400894 | C=0.8647921 | T=0.1352079 |
| gnomAD v4 - Exomes | European | Sub | 1165162 | C=0.9102494 | T=0.0897506 |
| gnomAD v4 - Exomes | South Asian | Sub | 86188 | C=0.68034 | T=0.31966 |
| gnomAD v4 - Exomes | American | Sub | 44614 | C=0.58556 | T=0.41444 |
| gnomAD v4 - Exomes | East Asian | Sub | 39604 | C=0.74980 | T=0.25020 |
| gnomAD v4 - Exomes | African | Sub | 33446 | C=0.24777 | T=0.75223 |
| gnomAD v4 - Exomes | Ashkenazi Jewish | Sub | 26122 | C=0.89660 | T=0.10340 |
| gnomAD v4 - Exomes | Middle Eastern | sub | 5758 | C=0.8215 | T=0.1785 |
| TopMed | Global | Study-wide | 264690 | C=0.652832 | T=0.347168 |
| gnomAD v4 - Genomes | Global | Study-wide | 149078 | C=0.687922 | T=0.312078 |
| gnomAD v4 - Genomes | European | Sub | 78612 | C=0.90842 | T=0.09158 |
| gnomAD v4 - Genomes | African | Sub | 41448 | C=0.26715 | T=0.73285 |
| gnomAD v4 - Genomes | American | Sub | 15268 | C=0.64141 | T=0.35859 |
| gnomAD v4 - Genomes | East Asian | Sub | 5172 | C=0.7336 | T=0.2664 |
| gnomAD v4 - Genomes | South Asian | Sub | 4816 | C=0.6545 | T=0.3455 |
| gnomAD v4 - Genomes | Ashkenazi Jewish | Sub | 3470 | C=0.8925 | T=0.1075 |
| gnomAD v4 - Genomes | Middle Eastern | sub | 292 | C=0.795 | T=0.205 |
| ExAC | Global | Study-wide | 120446 | C=0.770711 | T=0.229289 |
| ExAC | Europe | Sub | 72908 | C=0.90277 | T=0.09723 |
| ExAC | Asian | Sub | 24886 | C=0.69087 | T=0.30913 |
| ExAC | American | Sub | 11390 | C=0.55838 | T=0.44162 |
| ExAC | African | Sub | 10364 | C=0.26380 | T=0.73620 |
| ExAC | Other | Sub | 898 | C=0.805 | T=0.195 |
| 38KJPN | JAPANESE | Study-wide | 77440 | C=0.75566 | T=0.24434 |
| Allele Frequency Aggregator | Total | Global | 46152 | C=0.84499 | T=0.15501 |
| Allele Frequency Aggregator | European | Sub | 37068 | C=0.90523 | T=0.09477 |
| Allele Frequency Aggregator | Other | Sub | 4188 | C=0.8252 | T=0.1748 |
| Allele Frequency Aggregator | African | Sub | 3730 | C=0.3236 | T=0.6764 |
| Allele Frequency Aggregator | Latin American 2 | Sub | 678 | C=0.661 | T=0.339 |
| Allele Frequency Aggregator | Asian | Sub | 212 | C=0.679 | T=0.321 |
| Allele Frequency Aggregator | Latin American 1 | Sub | 156 | C=0.718 | T=0.282 |
| Allele Frequency Aggregator | South Asian | Sub | 120 | C=0.633 | T=0.367 |
| GO Exome Sequencing Project | Global | Study-wide | 13006 | C=0.69468 | T=0.30532 |
| GO Exome Sequencing Project | European American | Sub | 8600 | C=0.9034 | T=0.0966 |
| GO Exome Sequencing Project | African American | Sub | 4406 | C=0.2873 | T=0.7127 |
| Korean Genome Project 4K | KOREAN | Study-wide | 7234 | C=0.7951 | T=0.2049 |
| 1000Genomes_30X | Global | Study-wide | 6404 | C=0.5659 | T=0.4341 |
| 1000Genomes_30X | African | Sub | 1786 | C=0.1506 | T=0.8494 |
| 1000Genomes_30X | Europe | Sub | 1266 | C=0.9163 | T=0.0837 |
| 1000Genomes_30X | South Asian | Sub | 1202 | C=0.6140 | T=0.3860 |
| 1000Genomes_30X | East Asian | Sub | 1170 | C=0.7376 | T=0.2624 |
| 1000Genomes_30X | American | Sub | 980 | C=0.606 | T=0.394 |
| 1000Genomes | Global | Study-wide | 5008 | C=0.5783 | T=0.4217 |
| 1000Genomes | African | Sub | 1322 | C=0.1498 | T=0.8502 |
| 1000Genomes | East Asian | Sub | 1008 | C=0.7321 | T=0.2679 |
| 1000Genomes | Europe | Sub | 1006 | C=0.9185 | T=0.0815 |
| 1000Genomes | South Asian | Sub | 978 | C=0.629 | T=0.371 |
| 1000Genomes | American | Sub | 694 | C=0.607 | T=0.393 |
| The Avon Longitudinal Study of Parents and Children | PARENT AND CHILD COHORT | Study-wide | 3854 | C=0.9030 | T=0.0970 |
| UK 10K study - Twins | TWIN COHORT | Study-wide | 3708 | C=0.9086 | T=0.0914 |
| KOREAN population from KRGDB | KOREAN | Study-wide | 2930 | C=0.7956 | T=0.2044 |
| Korean Genome Project | KOREAN | Study-wide | 1832 | C=0.7909 | T=0.2091 |
| HapMap | Global | Study-wide | 1528 | C=0.5039 | T=0.4961 |
| HapMap | African | Sub | 686 | C=0.261 | T=0.739 |
| HapMap | American | Sub | 588 | C=0.694 | T=0.306 |
| HapMap | Asian | Sub | 254 | C=0.720 | T=0.280 |
| Genome of the Netherlands Release 5 | Genome of the Netherlands | Study-wide | 998 | C=0.915 | T=0.085 |
| PharmGKB Aggregated | Global | Study-wide | 996 | C=0.569 | T=0.431 |
| PharmGKB Aggregated | PA150087896 | Sub | 354 | C=0.653 | T=0.347 |
| PharmGKB Aggregated | PA164930475 | Sub | 262 | C=0.240 | T=0.760 |
| PharmGKB Aggregated | PA130602275 | Sub | 194 | C=0.701 | T=0.299 |
| PharmGKB Aggregated | PA130250977 | Sub | 186 | C=0.737 | T=0.263 |
| CNV burdens in cranial meningiomas | Global | Study-wide | 782 | C=0.777 | T=0.223 |
| CNV burdens in cranial meningiomas | CRM | Sub | 782 | C=0.777 | T=0.223 |
| A Vietnamese Genetic Variation Database | Global | Study-wide | 614 | C=0.681 | T=0.319 |
| Northern Sweden | ACPOP | Study-wide | 600 | C=0.875 | T=0.125 |
| Medical Genome Project healthy controls from Spanish population | Spanish controls | Study-wide | 534 | C=0.856 | T=0.144 |
| FINRISK | Finnish from FINRISK project | Study-wide | 304 | C=0.928 | T=0.072 |
| SGDP_PRJ | Global | Study-wide | 268 | C=0.265 | T=0.735 |
| Qatari | Global | Study-wide | 216 | C=0.741 | T=0.259 |
| Siberian | Global | Study-wide | 10 | C=0.5 | T=0.5 |
Help
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.
Genomic Placements
| Sequence name | Change |
|---|---|
| GRCh38.p14 chr 7 | NC_000007.14:g.99763843C>T |
| GRCh37.p13 chr 7 | NC_000007.13:g.99361466C>T |
| CYP3A4 RefSeqGene | NG_008421.1:g.25343G>A |
| LOC110366355 genomic region | NG_054907.1:g.313C>T |
Gene: CYP3A4, cytochrome P450 family 3 subfamily A member 4
(minus strand)
| Molecule type | Change | Amino acid[Codon] | SO Term |
|---|---|---|---|
| CYP3A4 transcript variant 2 |
NM_001202855.3:c.1023+12G… NM_001202855.3:c.1023+12G>A |
N/A | Intron Variant |
| CYP3A4 transcript variant 1 | NM_017460.6:c.1026+12G>A | N/A | Intron Variant |
Help
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.
Allele: T (allele ID:
2534494
)
| ClinVar Accession | Disease Names | Clinical Significance |
|---|---|---|
| RCV003228705.3 | fentanyl response - Dosage | Drug-Response |
| RCV003228706.3 | tacrolimus response - Metabolism/PK | Drug-Response |
Help
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 | C= | T |
|---|---|---|
| GRCh38.p14 chr 7 | NC_000007.14:g.99763843= | NC_000007.14:g.99763843C>T |
| GRCh37.p13 chr 7 | NC_000007.13:g.99361466= | NC_000007.13:g.99361466C>T |
| CYP3A4 RefSeqGene | NG_008421.1:g.25343= | NG_008421.1:g.25343G>A |
| LOC110366355 genomic region | NG_054907.1:g.313= | NG_054907.1:g.313C>T |
| CYP3A4 transcript variant 2 | NM_001202855.2:c.1023+12= | NM_001202855.2:c.1023+12G>A |
| CYP3A4 transcript variant 2 | NM_001202855.3:c.1023+12= | NM_001202855.3:c.1023+12G>A |
| CYP3A4 transcript variant 1 | NM_017460.5:c.1026+12= | NM_017460.5:c.1026+12G>A |
| CYP3A4 transcript variant 1 | NM_017460.6:c.1026+12= | NM_017460.6:c.1026+12G>A |
Help
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#.
144 SubSNP,
25 Frequency,
2 ClinVar
submissions
| No | Submitter | Submission ID | Date (Build) |
|---|---|---|---|
| 1 | YUSUKE | ss3198808 | Aug 15, 2001 (98) |
| 2 | MINT | ss4323380 | Mar 26, 2002 (103) |
| 3 | SNP500CANCER | ss5586457 | Jul 02, 2003 (116) |
| 4 | RIKENSNPRC | ss6311601 | Feb 20, 2003 (111) |
| 5 | SC_SNP | ss13448366 | Dec 05, 2003 (123) |
| 6 | WUGSC_SSAHASNP | ss14570091 | Dec 05, 2003 (123) |
| 7 | PERLEGEN | ss23449997 | Sep 20, 2004 (124) |
| 8 | BIOVENTURES | ss32476120 | May 24, 2005 (126) |
| 9 | EGP_SNPS | ss37043551 | May 25, 2005 (125) |
| 10 | SI_EXO | ss52056865 | Oct 16, 2006 (127) |
| 11 | ILLUMINA | ss65804335 | Oct 16, 2006 (127) |
| 12 | PERLEGEN | ss69023414 | May 18, 2007 (127) |
| 13 | PHARMGKB_PAAR-UCHI | ss69367610 | May 18, 2007 (127) |
| 14 | PHARMGKB_PAAR-SJCRH | ss69370612 | May 18, 2007 (127) |
| 15 | ILLUMINA | ss74868694 | Dec 07, 2007 (129) |
| 16 | CGM_KYOTO | ss76860238 | Dec 07, 2007 (129) |
| 17 | CCHMC-CAE-PGCORE | ss79314213 | Dec 15, 2007 (130) |
| 18 | HGSV | ss81197014 | Dec 15, 2007 (130) |
| 19 | PHARMGKB_AB_DME | ss84155309 | Dec 15, 2007 (130) |
| 20 | HGSV | ss84338372 | Dec 15, 2007 (130) |
| 21 | BGI | ss104454245 | Feb 13, 2009 (131) |
| 22 | 1000GENOMES | ss114160144 | Jan 25, 2009 (130) |
| 23 | ILLUMINA-UK | ss116216908 | Feb 14, 2009 (130) |
| 24 | KRIBB_YJKIM | ss119423802 | Dec 01, 2009 (131) |
| 25 | GMI | ss155255118 | Dec 01, 2009 (131) |
| 26 | PHARMGKB_PAAR-UCHI | ss161109912 | Dec 01, 2009 (131) |
| 27 | COMPLETE_GENOMICS | ss164959628 | Jul 04, 2010 (132) |
| 28 | ILLUMINA | ss173209046 | Jul 04, 2010 (132) |
| 29 | BUSHMAN | ss197977782 | Jul 04, 2010 (132) |
| 30 | 1000GENOMES | ss223228763 | Jul 14, 2010 (132) |
| 31 | 1000GENOMES | ss234093098 | Jul 15, 2010 (132) |
| 32 | 1000GENOMES | ss241025209 | Jul 15, 2010 (132) |
| 33 | ILLUMINA | ss244288487 | Jul 04, 2010 (132) |
| 34 | GMI | ss279457376 | May 04, 2012 (137) |
| 35 | PJP | ss293932782 | May 09, 2011 (134) |
| 36 | ILLUMINA | ss484070500 | May 04, 2012 (137) |
| 37 | ILLUMINA | ss485503831 | May 04, 2012 (137) |
| 38 | 1000GENOMES | ss490949843 | May 04, 2012 (137) |
| 39 | CLINSEQ_SNP | ss491910526 | May 04, 2012 (137) |
| 40 | ILLUMINA | ss536261196 | Sep 08, 2015 (146) |
| 41 | TISHKOFF | ss560184375 | Apr 25, 2013 (138) |
| 42 | SSMP | ss654586028 | Apr 25, 2013 (138) |
| 43 | NHLBI-ESP | ss712791179 | Apr 25, 2013 (138) |
| 44 | ILLUMINA | ss779070211 | Sep 08, 2015 (146) |
| 45 | ILLUMINA | ss780515167 | Sep 08, 2015 (146) |
| 46 | ILLUMINA | ss782480077 | Sep 08, 2015 (146) |
| 47 | ILLUMINA | ss834533738 | Sep 08, 2015 (146) |
| 48 | ILLUMINA | ss836006430 | Sep 08, 2015 (146) |
| 49 | JMKIDD_LAB | ss974465110 | Aug 21, 2014 (142) |
| 50 | EVA-GONL | ss984590753 | Aug 21, 2014 (142) |
| 51 | JMKIDD_LAB | ss1067490111 | Aug 21, 2014 (142) |
| 52 | JMKIDD_LAB | ss1074831823 | Aug 21, 2014 (142) |
| 53 | 1000GENOMES | ss1326340539 | Aug 21, 2014 (142) |
| 54 | DDI | ss1431222539 | Apr 01, 2015 (144) |
| 55 | EVA_FINRISK | ss1584053738 | Apr 01, 2015 (144) |
| 56 | EVA_DECODE | ss1594169799 | Apr 01, 2015 (144) |
| 57 | EVA_UK10K_ALSPAC | ss1618800497 | Apr 01, 2015 (144) |
| 58 | EVA_UK10K_TWINSUK | ss1661794530 | Apr 01, 2015 (144) |
| 59 | EVA_EXAC | ss1688841919 | Apr 01, 2015 (144) |
| 60 | EVA_MGP | ss1711173236 | Apr 01, 2015 (144) |
| 61 | EVA_SVP | ss1712974459 | Apr 01, 2015 (144) |
| 62 | HAMMER_LAB | ss1805132990 | Sep 08, 2015 (146) |
| 63 | WEILL_CORNELL_DGM | ss1927851814 | Feb 12, 2016 (147) |
| 64 | ILLUMINA | ss1959035727 | Feb 12, 2016 (147) |
| 65 | GENOMED | ss1970771568 | Jul 19, 2016 (147) |
| 66 | JJLAB | ss2024608695 | Sep 14, 2016 (149) |
| 67 | USC_VALOUEV | ss2152830522 | Dec 20, 2016 (150) |
| 68 | ILLUMINA | ss2634638379 | Nov 08, 2017 (151) |
| 69 | ILLUMINA | ss2634638380 | Nov 08, 2017 (151) |
| 70 | ILLUMINA | ss2635175228 | Nov 08, 2017 (151) |
| 71 | GRF | ss2708541146 | Nov 08, 2017 (151) |
| 72 | ILLUMINA | ss2711117394 | Nov 08, 2017 (151) |
| 73 | GNOMAD | ss2736599916 | Nov 08, 2017 (151) |
| 74 | GNOMAD | ss2747872141 | Nov 08, 2017 (151) |
| 75 | GNOMAD | ss2856772500 | Nov 08, 2017 (151) |
| 76 | AFFY | ss2985413769 | Nov 08, 2017 (151) |
| 77 | AFFY | ss2986045994 | Nov 08, 2017 (151) |
| 78 | SWEGEN | ss3001708497 | Nov 08, 2017 (151) |
| 79 | ILLUMINA | ss3022760841 | Nov 08, 2017 (151) |
| 80 | BIOINF_KMB_FNS_UNIBA | ss3026096704 | Nov 08, 2017 (151) |
| 81 | CSIRBIOHTS | ss3029637951 | Nov 08, 2017 (151) |
| 82 | CSHL | ss3347752863 | Nov 08, 2017 (151) |
| 83 | ILLUMINA | ss3629873181 | Oct 12, 2018 (152) |
| 84 | ILLUMINA | ss3632543972 | Oct 12, 2018 (152) |
| 85 | ILLUMINA | ss3632543973 | Oct 12, 2018 (152) |
| 86 | ILLUMINA | ss3638713170 | Oct 12, 2018 (152) |
| 87 | ILLUMINA | ss3642577979 | Oct 12, 2018 (152) |
| 88 | ILLUMINA | ss3643647742 | Oct 12, 2018 (152) |
| 89 | OMUKHERJEE_ADBS | ss3646359830 | Oct 12, 2018 (152) |
| 90 | ILLUMINA | ss3653294863 | Oct 12, 2018 (152) |
| 91 | ILLUMINA | ss3654175387 | Oct 12, 2018 (152) |
| 92 | EVA_DECODE | ss3720301976 | Jul 13, 2019 (153) |
| 93 | ILLUMINA | ss3726465387 | Jul 13, 2019 (153) |
| 94 | ACPOP | ss3734902891 | Jul 13, 2019 (153) |
| 95 | EVA | ss3766925907 | Jul 13, 2019 (153) |
| 96 | KHV_HUMAN_GENOMES | ss3810097314 | Jul 13, 2019 (153) |
| 97 | EVA | ss3824296576 | Apr 26, 2020 (154) |
| 98 | EVA | ss3825724458 | Apr 26, 2020 (154) |
| 99 | EVA | ss3830722536 | Apr 26, 2020 (154) |
| 100 | SGDP_PRJ | ss3867982692 | Apr 26, 2020 (154) |
| 101 | KRGDB | ss3915272300 | Apr 26, 2020 (154) |
| 102 | KOGIC | ss3962190700 | Apr 26, 2020 (154) |
| 103 | FSA-LAB | ss3984373789 | Apr 26, 2021 (155) |
| 104 | EVA | ss3984592440 | Apr 26, 2021 (155) |
| 105 | EVA | ss3986390980 | Apr 26, 2021 (155) |
| 106 | EVA | ss4017349869 | Apr 26, 2021 (155) |
| 107 | TOPMED | ss4756586965 | Apr 26, 2021 (155) |
| 108 | TOMMO_GENOMICS | ss6081196117 | Oct 31, 2024 (157) |
| 109 | EVA | ss6241637741 | Oct 31, 2024 (157) |
| 110 | EVA | ss6301281716 | Oct 31, 2024 (157) |
| 111 | EVA | ss6321947367 | Oct 31, 2024 (157) |
| 112 | EVA | ss6322315039 | Oct 31, 2024 (157) |
| 113 | EVA | ss6331469630 | Oct 31, 2024 (157) |
| 114 | YEGNASUBRAMANIAN_LAB | ss6340796582 | Oct 31, 2024 (157) |
| 115 | EVA | ss6349711468 | Oct 31, 2024 (157) |
| 116 | KOGIC | ss6374331224 | Oct 31, 2024 (157) |
| 117 | EVA | ss6404379073 | Oct 31, 2024 (157) |
| 118 | GNOMAD | ss6431774282 | Oct 31, 2024 (157) |
| 119 | GNOMAD | ss6763882930 | Oct 31, 2024 (157) |
| 120 | TOMMO_GENOMICS | ss8184665400 | Oct 31, 2024 (157) |
| 121 | EVA | ss8237197117 | Oct 31, 2024 (157) |
| 122 | EVA | ss8237426158 | Oct 31, 2024 (157) |
| 123 | QINSY-LAB | ss8237630499 | Oct 31, 2024 (157) |
| 124 | 1000G_HIGH_COVERAGE | ss8274033948 | Oct 31, 2024 (157) |
| 125 | EVA | ss8315266746 | Oct 31, 2024 (157) |
| 126 | EVA | ss8375501007 | Oct 31, 2024 (157) |
| 127 | HUGCELL_USP | ss8471004679 | Oct 31, 2024 (157) |
| 128 | 1000G_HIGH_COVERAGE | ss8562816210 | Oct 31, 2024 (157) |
| 129 | EVA | ss8624169016 | Oct 31, 2024 (157) |
| 130 | SANFORD_IMAGENETICS | ss8643588334 | Oct 31, 2024 (157) |
| 131 | TOMMO_GENOMICS | ss8725378151 | Oct 31, 2024 (157) |
| 132 | EVA | ss8800140734 | Oct 31, 2024 (157) |
| 133 | YY_MCH | ss8808926055 | Oct 31, 2024 (157) |
| 134 | EVA | ss8823256594 | Oct 31, 2024 (157) |
| 135 | EVA | ss8848146877 | Oct 31, 2024 (157) |
| 136 | EVA | ss8848687651 | Oct 31, 2024 (157) |
| 137 | EVA | ss8856021685 | Oct 31, 2024 (157) |
| 138 | EVA | ss8860089997 | Oct 31, 2024 (157) |
| 139 | EVA | ss8972772927 | Oct 31, 2024 (157) |
| 140 | EVA | ss8979835176 | Oct 31, 2024 (157) |
| 141 | EVA | ss8981244409 | Oct 31, 2024 (157) |
| 142 | EVA | ss8981325938 | Oct 31, 2024 (157) |
| 143 | EVA | ss8981974747 | Oct 31, 2024 (157) |
| 144 | EVA | ss8981974748 | Oct 31, 2024 (157) |
| 145 | 1000Genomes | NC_000007.13 - 99361466 | Oct 12, 2018 (152) |
| 146 | 1000Genomes_30X | NC_000007.14 - 99763843 | Oct 31, 2024 (157) |
| 147 | The Avon Longitudinal Study of Parents and Children | NC_000007.13 - 99361466 | Oct 12, 2018 (152) |
| 148 | ExAC | NC_000007.13 - 99361466 | Oct 12, 2018 (152) |
| 149 | FINRISK | NC_000007.13 - 99361466 | Apr 26, 2020 (154) |
| 150 | gnomAD v4 - Exomes | NC_000007.14 - 99763843 | Oct 31, 2024 (157) |
| 151 | gnomAD v4 - Genomes | NC_000007.14 - 99763843 | Oct 31, 2024 (157) |
| 152 | GO Exome Sequencing Project | NC_000007.13 - 99361466 | Oct 12, 2018 (152) |
| 153 | Genome of the Netherlands Release 5 | NC_000007.13 - 99361466 | Apr 26, 2020 (154) |
| 154 | HapMap | NC_000007.14 - 99763843 | Apr 26, 2020 (154) |
| 155 | KOREAN population from KRGDB | NC_000007.13 - 99361466 | Apr 26, 2020 (154) |
| 156 | Korean Genome Project | NC_000007.14 - 99763843 | Apr 26, 2020 (154) |
| 157 | Korean Genome Project 4K | NC_000007.14 - 99763843 | Oct 31, 2024 (157) |
| 158 | Medical Genome Project healthy controls from Spanish population | NC_000007.13 - 99361466 | Apr 26, 2020 (154) |
| 159 | Northern Sweden | NC_000007.13 - 99361466 | Jul 13, 2019 (153) |
| 160 | CNV burdens in cranial meningiomas | NC_000007.13 - 99361466 | Apr 26, 2021 (155) |
| 161 | PharmGKB Aggregated | NC_000007.14 - 99763843 | Apr 26, 2020 (154) |
| 162 | Qatari | NC_000007.13 - 99361466 | Apr 26, 2020 (154) |
| 163 | SGDP_PRJ | NC_000007.13 - 99361466 | Apr 26, 2020 (154) |
| 164 | Siberian | NC_000007.13 - 99361466 | Apr 26, 2020 (154) |
| 165 | 38KJPN | NC_000007.14 - 99763843 | Oct 31, 2024 (157) |
| 166 | TopMed | NC_000007.14 - 99763843 | Apr 26, 2021 (155) |
| 167 | UK 10K study - Twins | NC_000007.13 - 99361466 | Oct 12, 2018 (152) |
| 168 | A Vietnamese Genetic Variation Database | NC_000007.13 - 99361466 | Jul 13, 2019 (153) |
| 169 | ALFA | NC_000007.14 - 99763843 | Oct 31, 2024 (157) |
| 170 | ClinVar | RCV003228705.3 | Oct 31, 2024 (157) |
| 171 | ClinVar | RCV003228706.3 | Oct 31, 2024 (157) |
Help
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) |
|---|---|
| rs9655766 | Sep 24, 2004 (123) |
| rs10364667 | Sep 24, 2004 (123) |
| rs12721630 | Sep 24, 2004 (123) |
| rs17161804 | Dec 02, 2004 (124) |
| rs28969389 | Mar 11, 2006 (126) |
| rs59491337 | May 25, 2008 (130) |
| rs72494459 | Dec 02, 2009 (131) |
Added to this RefSNP Cluster:
| Submission IDs | Observation SPDI | Canonical SPDI | Source RSIDs |
|---|---|---|---|
| ss81197014, ss84338372 | NC_000007.11:99006116:C:T | NC_000007.14:99763842:C:T | (self) |
| ss114160144, ss116216908, ss164959628, ss197977782, ss279457376, ss293932782, ss485503831, ss491910526, ss1594169799, ss1712974459, ss2635175228, ss3643647742 | NC_000007.12:99199401:C:T | NC_000007.14:99763842:C:T | (self) |
| 38354515, 21342230, 8915771, 50199, 754520, 9527579, 22449694, 288996, 8187756, 141867, 9893744, 19999672, 5346876, 21342230, 4759008, ss223228763, ss234093098, ss241025209, ss484070500, ss490949843, ss536261196, ss560184375, ss654586028, ss712791179, ss779070211, ss780515167, ss782480077, ss834533738, ss836006430, ss974465110, ss984590753, ss1067490111, ss1074831823, ss1326340539, ss1431222539, ss1584053738, ss1618800497, ss1661794530, ss1688841919, ss1711173236, ss1805132990, ss1927851814, ss1959035727, ss1970771568, ss2024608695, ss2152830522, ss2634638379, ss2634638380, ss2708541146, ss2711117394, ss2736599916, ss2747872141, ss2856772500, ss2985413769, ss2986045994, ss3001708497, ss3022760841, ss3029637951, ss3347752863, ss3629873181, ss3632543972, ss3632543973, ss3638713170, ss3642577979, ss3646359830, ss3653294863, ss3654175387, ss3734902891, ss3766925907, ss3824296576, ss3825724458, ss3830722536, ss3867982692, ss3915272300, ss3984373789, ss3984592440, ss3986390980, ss4017349869, ss6241637741, ss6301281716, ss6322315039, ss6331469630, ss6340796582, ss6349711468, ss8184665400, ss8237426158, ss8237630499, ss8315266746, ss8375501007, ss8624169016, ss8643588334, ss8800140734, ss8823256594, ss8848146877, ss8848687651, ss8972772927, ss8979835176, ss8981244409, ss8981325938, ss8981974747, ss8981974748 | NC_000007.13:99361465:C:T | NC_000007.14:99763842:C:T | (self) |
| RCV003228705.3, RCV003228706.3, 50342145, 27089081, 290784838, 3455402, 18568701, 24183122, 11742, 98571937, 593964524, 12324737290, ss3026096704, ss3720301976, ss3726465387, ss3810097314, ss3962190700, ss4756586965, ss6081196117, ss6321947367, ss6374331224, ss6404379073, ss6431774282, ss6763882930, ss8237197117, ss8274033948, ss8471004679, ss8562816210, ss8725378151, ss8808926055, ss8856021685, ss8860089997 | NC_000007.14:99763842:C:T | NC_000007.14:99763842:C:T | (self) |
| ss13448366 | NT_007933.12:24595049:C:T | NC_000007.14:99763842:C:T | (self) |
| ss14570091 | NT_007933.13:24595049:C:T | NC_000007.14:99763842:C:T | (self) |
| ss52056865 | NT_007933.14:24595741:C:T | NC_000007.14:99763842:C:T | (self) |
| ss3198808, ss4323380, ss5586457, ss6311601, ss23449997, ss32476120, ss37043551, ss65804335, ss69023414, ss69367610, ss69370612, ss74868694, ss76860238, ss79314213, ss84155309, ss104454245, ss119423802, ss155255118, ss161109912, ss173209046, ss244288487 | NT_007933.15:37394308:C:T | NC_000007.14:99763842:C:T | (self) |
Help
Publications tab displays PubMed articles citing the variation as a listing of PMID, Title, Author, Year, Journal, ordered by Year, descending.
67
citations for rs2242480
| PMID | Title | Author | Year | Journal |
|---|---|---|---|---|
| 17615053 | Polymorphisms in the cytochrome P450 genes CYP1A2, CYP1B1, CYP3A4, CYP3A5, CYP11A1, CYP17A1, CYP19A1 and colorectal cancer risk. | Bethke L et al. | 2007 | BMC cancer |
| 18163429 | Genetic polymorphisms in CYP17, CYP3A4, CYP19A1, SRD5A2, IGF-1, and IGFBP-3 and prostate cancer risk in African-American men: the Flint Men's Health Study. | Sarma AV et al. | 2008 | The Prostate |
| 18504423 | Polymorphisms in inflammation-related genes are associated with susceptibility to major depression and antidepressant response. | Wong ML et al. | 2008 | Molecular psychiatry |
| 18825162 | Prediction of CYP3A4 enzyme activity using haplotype tag SNPs in African Americans. | Perera MA et al. | 2009 | The pharmacogenomics journal |
| 20386561 | Intronic polymorphism in CYP3A4 affects hepatic expression and response to statin drugs. | Wang D et al. | 2011 | The pharmacogenomics journal |
| 20436251 | Xenobiotic metabolizing genes, meat-related exposures, and risk of advanced colorectal adenoma. | Ferrucci LM et al. | 2010 | World review of nutrition and dietetics |
| 21071160 | Analysis of 50 SNPs in CYP2D6, CYP2C19, CYP2C9, CYP3A4 and CYP1A2 by MALDI-TOF mass spectrometry in Chinese Han population. | Shi Y et al. | 2011 | Forensic science international |
| 21199372 | A functional polymorphism in the CYP3A4 gene is associated with increased risk of coronary heart disease in the Chinese Han population. | He BX et al. | 2011 | Basic & clinical pharmacology & toxicology |
| 21474949 | Xenobiotic metabolizing genes, meat-related exposures, and risk of advanced colorectal adenoma. | Ferrucci LM et al. | 2010 | Journal of nutrigenetics and nutrigenomics |
| 21692828 | The population pharmacokinetics of R- and S-warfarin: effect of genetic and clinical factors. | Lane S et al. | 2012 | British journal of clinical pharmacology |
| 21790905 | CYP2B6 SNPs are associated with methadone dose required for effective treatment of opioid addiction. | Levran O et al. | 2013 | Addiction biology |
| 21918509 | Pharmacogenomics: application to the management of cardiovascular disease. | Johnson JA et al. | 2011 | Clinical pharmacology and therapeutics |
| 22178823 | [Distribution of variant alleles association with warfarin pharmacokinetics and pharmacodynamics in the Han population in China]. | Liu Y et al. | 2011 | Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences |
| 22583563 | Genetic and environmental predictors of serum 25-hydroxyvitamin D concentrations among middle-aged and elderly Chinese in Singapore. | Robien K et al. | 2013 | The British journal of nutrition |
| 23064017 | Donor ABCB1 variant associates with increased risk for kidney allograft failure. | Moore J et al. | 2012 | Journal of the American Society of Nephrology |
| 24884825 | Increased genetic diversity of ADME genes in African Americans compared with their putative ancestral source populations and implications for pharmacogenomics. | Li J et al. | 2014 | BMC genetics |
| 25217544 | Fatal methadone toxicity: potential role of CYP3A4 genetic polymorphism. | Richards-Waugh LL et al. | 2014 | Journal of analytical toxicology |
| 25419701 | Exploring the distribution of genetic markers of pharmacogenomics relevance in Brazilian and Mexican populations. | Bonifaz-Peña V et al. | 2014 | PloS one |
| 25955319 | Finasteride concentrations and prostate cancer risk: results from the Prostate Cancer Prevention Trial. | Chau CH et al. | 2015 | PloS one |
| 26160721 | Correlation analysis of gene polymorphisms and β-lactam allergy. | Li J et al. | 2015 | Journal of Zhejiang University. Science. B |
| 26284404 | [Detection of cytochrome P450 3A4 gene polymorphism guides for labor analgesia with sufentanil medication]. | Chi LQ et al. | 2015 | Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences |
| 26421491 | Effects of CYP3A4/5 and ABCB1 genetic polymorphisms on carbamazepine metabolism and transport in Chinese patients with epilepsy treated with carbamazepine in monotherapy and bitherapy. | Wang P et al. | 2015 | Epilepsy research |
| 26961113 | Association of Cytochrome P450 Genetic Variants with Clopidogrel Resistance and Outcomes in Acute Ischemic Stroke. | Yi X et al. | 2016 | Journal of atherosclerosis and thrombosis |
| 26988277 | Genetic Association of Curative and Adverse Reactions to Tyrosine Kinase Inhibitors in Chinese advanced Non-Small Cell Lung Cancer patients. | Ruan Y et al. | 2016 | Scientific reports |
| 27133299 | Associations of CYP3A4, NR1I2, CYP2C19 and P2RY12 polymorphisms with clopidogrel resistance in Chinese patients with ischemic stroke. | Liu R et al. | 2016 | Acta pharmacologica Sinica |
| 27434656 | Influence of the CYP3A4/5 genetic score and ABCB1 polymorphisms on tacrolimus exposure and renal function in Brazilian kidney transplant patients. | Genvigir FD et al. | 2016 | Pharmacogenetics and genomics |
| 27956118 | Genetic polymorphisms of phase I metabolizing enzyme genes, their interaction with lifetime grilled and smoked meat intake, and breast cancer incidence. | Parada H Jr et al. | 2017 | Annals of epidemiology |
| 28049954 | No Effect of SLCO1B1 and CYP3A4/5 Polymorphisms on the Pharmacokinetics and Pharmacodynamics of Ticagrelor in Healthy Chinese Male Subjects. | Li M et al. | 2017 | Biological & pharmaceutical bulletin |
| 28112181 | IL-3 and CTLA4 gene polymorphisms may influence the tacrolimus dose requirement in Chinese kidney transplant recipients. | Liu MZ et al. | 2017 | Acta pharmacologica Sinica |
| 28335376 | Genetic Polymorphisms Contribute to the Individual Variations of Imatinib Mesylate Plasma Levels and Adverse Reactions in Chinese GIST Patients. | Liu J et al. | 2017 | International journal of molecular sciences |
| 28408884 | Effect of CYP3A4(∗)1G and CYP3A5(∗)3 Polymorphisms on Pharmacokinetics and Pharmacodynamics of Ticagrelor in Healthy Chinese Subjects. | Liu S et al. | 2017 | Frontiers in pharmacology |
| 28593920 | Influence of CYP3A4 and CYP3A5 polymorphisms on tacrolimus and sirolimus exposure in stable kidney transplant recipients. | Tamashiro EY et al. | 2017 | Drug metabolism and personalized therapy |
| 28621555 | SLC28A3 rs7853758 as a new biomarker of tacrolimus elimination and new-onset hypertension in Chinese liver transplantation patients. | Liu Y et al. | 2017 | Biomarkers in medicine |
| 28723497 | Pharmacogenomic Markers of Targeted Therapy Toxicity in Patients with Metastatic Renal Cell Carcinoma. | de Velasco G et al. | 2016 | European urology focus |
| 28771511 | Exploring public genomics data for population pharmacogenomics. | Lakiotaki K et al. | 2017 | PloS one |
| 28871186 | Analysis of population-specific pharmacogenomic variants using next-generation sequencing data. | Ahn E et al. | 2017 | Scientific reports |
| 28900995 | [Association between genetic polymorphisms and variation of imatinib pharmacokinetics in gastrointestinal stromal tumors]. | Qiu H et al. | 2017 | Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery |
| 29153269 | Vitamin D pathway gene polymorphisms influenced vitamin D level among pregnant women. | Shao B et al. | 2018 | Clinical nutrition (Edinburgh, Scotland) |
| 29500141 | Polymorphisms in CYP450 Genes and the Therapeutic Effect of Atorvastatin on Ischemic Stroke: A Retrospective Cohort Study in Chinese Population. | Peng C et al. | 2018 | Clinical therapeutics |
| 29679912 | Effects of UGT2B7, SCN1A and CYP3A4 on the therapeutic response of sodium valproate treatment in children with generalized seizures. | Feng W et al. | 2018 | Seizure |
| 30093869 | Biological Predictors of Clozapine Response: A Systematic Review. | Samanaite R et al. | 2018 | Frontiers in psychiatry |
| 30130726 | UHPLC-MS/MS method for determination of atorvastatin calcium in human plasma: Application to a pharmacokinetic study based on healthy volunteers with specific genotype. | Xia B et al. | 2018 | Journal of pharmaceutical and biomedical analysis |
| 30218411 | Correlations between CYP3A4 polymorphism and susceptibility to breast cancer in Chinese Han population. | Liu X et al. | 2019 | International journal of clinical oncology |
| 30452466 | Characterization of ADME genes variation in Roma and 20 populations worldwide. | Škarić-Jurić T et al. | 2018 | PloS one |
| 31401678 | CYP3A5 and CYP3A7 genetic polymorphisms affect tacrolimus concentration in pediatric patients with nephrotic range proteinuria. | Liu H et al. | 2019 | European journal of clinical pharmacology |
| 31780765 | Pharmacogenetics of amfepramone in healthy Mexican subjects reveals potential markers for tailoring pharmacotherapy of obesity: results of a randomised trial. | Gómez-Silva M et al. | 2019 | Scientific reports |
| 31874497 | [Effect of opioid-related gene polymorphisms on patients with high-dose opioid-tolerant cancer pain]. | Xie GL et al. | 2019 | Zhonghua yi xue za zhi |
| 32042822 | The analysis of pharmacokinetic and pharmacogenomic impact on gefitinib efficacy in advanced non-small cell lung cancer patients: results from a prospective cohort study. | Ma Y et al. | 2019 | Annals of translational medicine |
| 32457635 | Polymorphisms of Drug-Metabolizing Enzymes and Transporters Contribute to the Individual Variations of Erlotinib Steady State Trough Concentration, Treatment Outcomes, and Adverse Reactions in Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Cancer Patients. | Liao D et al. | 2020 | Frontiers in pharmacology |
| 33192522 | Pleiotropic Functions of Cytochrome P450 Monooxygenase-Derived Eicosanoids in Cancer. | Luo Y et al. | 2020 | Frontiers in pharmacology |
| 33217013 | Evaluation of clinical and genetic factors in the population pharmacokinetics of carbamazepine. | Yip VLM et al. | 2021 | British journal of clinical pharmacology |
| 33252269 | Association of ABCB1 and CYP450 Gene Polymorphisms and their DNA Methylation Status with Steroid-Induced Osteonecrosis of the Femoral Head in the Chinese Population. | Huang R et al. | 2020 | Genetic testing and molecular biomarkers |
| 33519226 | Genetic Diversity of Drug-Related Genes in Native Americans of the Brazilian Amazon. | Fernandes MR et al. | 2021 | Pharmacogenomics and personalized medicine |
| 33756436 | Associations between CYP3A4, CYP3A5 and SCN1A polymorphisms and carbamazepine metabolism in epilepsy: A meta-analysis. | Zhao GX et al. | 2021 | Epilepsy research |
| 33776761 | Pharmacogenetics-Based Preliminary Algorithm to Predict the Incidence of Infection in Patients Receiving Cytotoxic Chemotherapy for Hematological Malignancies: A Discovery Cohort. | Martinez MF et al. | 2021 | Frontiers in pharmacology |
| 34320606 | Regulation of CYP3A4 and CYP3A5 by a lncRNA: a potential underlying mechanism explaining the association between CYP3A4*1G and CYP3A metabolism. | Collins JM et al. | 2022 | Pharmacogenetics and genomics |
| 34429635 | Population Genetic Difference of Pharmacogenomic VIP Variants in the Tibetan Population. | He C et al. | 2021 | Pharmacogenomics and personalized medicine |
| 34512362 | Influence of FMO3 and CYP3A4 Polymorphisms on the Pharmacokinetics of Teneligliptin in Humans. | Park JW et al. | 2021 | Frontiers in pharmacology |
| 34688813 | CYP3A7, CYP3A4, and CYP3A5 genetic polymorphisms in recipients rather than donors influence tacrolimus concentrations in the early stages after liver transplantation. | Dong Y et al. | 2022 | Gene |
| 34689350 | Allele and genotype frequencies of CYP3A4, CYP3A5, CYP3A7, and GSTP1 gene polymorphisms among mainland Tibetan, Mongolian, Uyghur, and Han Chinese populations. | Qi G et al. | 2022 | Clinical and experimental pharmacology & physiology |
| 34798807 | Genetic analysis of pharmacogenomic VIP variants in the Wa population from Yunnan Province of China. | Li D et al. | 2021 | BMC genomic data |
| 34949935 | Genetic Polymorphisms of Very Important Pharmacogene Variants in the Blang Population from Yunnan Province in China. | Wang Y et al. | 2021 | Pharmacogenomics and personalized medicine |
| 35547337 | Association of Specific Genetic Polymorphisms with Atraumatic Osteonecrosis of the Femoral Head: A Narrative Review. | Kumar P et al. | 2022 | Indian journal of orthopaedics |
| 35761855 | Pharmacogenetics of Breast Cancer Treatments: A Sub-Saharan Africa Perspective. | Nthontho KC et al. | 2022 | Pharmacogenomics and personalized medicine |
| 35846994 | Characterization of ADME Gene Variation in Colombian Population by Exome Sequencing. | Silgado-Guzmán DF et al. | 2022 | Frontiers in pharmacology |
| 36378297 | Impact of trough abiraterone level on adverse events in patients with prostate cancer treated with abiraterone acetate. | Takahashi Y et al. | 2023 | European journal of clinical pharmacology |
| 37780578 | Genetic association of beta-lactams-induced hypersensitivity reactions: A systematic review of genome-wide evidence and meta-analysis of candidate genes. | Lumkul L et al. | 2023 | The World Allergy Organization journal |
Help
The Flanks tab provides retrieving flanking sequences of a SNP on all molecules that have placements.
Genome context:
Select flank length:
Genomic regions, transcripts, and products
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Help
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.