When available on CRAN
install.packages("rsnps")Or get from Github
install.packages("devtools")
library(devtools)
install_github("rsnps", "ropensci")library(rsnps)allgensnp(snp = "rs7412")[1:3][[1]]
[[1]]$snp
[[1]]$snp$name
[1] "rs7412"
[[1]]$snp$chromosome
[1] "19"
[[1]]$snp$position
[1] "50103919"
[[1]]$user
[[1]]$user$name
[1] "Lisa"
[[1]]$user$id
[1] 1653
[[1]]$user$genotypes
[[1]]$user$genotypes[[1]]
[[1]]$user$genotypes[[1]]$genotype_id
[1] 944
[[1]]$user$genotypes[[1]]$local_genotype
[1] "CC"
[[2]]
[[2]]$snp
[[2]]$snp$name
[1] "rs7412"
[[2]]$snp$chromosome
[1] "19"
[[2]]$snp$position
[1] "50103919"
[[2]]$user
[[2]]$user$name
[1] "karl"
[[2]]$user$id
[1] 1651
[[2]]$user$genotypes
[[2]]$user$genotypes[[1]]
[[2]]$user$genotypes[[1]]$genotype_id
[1] 943
[[2]]$user$genotypes[[1]]$local_genotype
[1] "CC"
[[3]]
[[3]]$snp
[[3]]$snp$name
[1] "rs7412"
[[3]]$snp$chromosome
[1] "19"
[[3]]$snp$position
[1] "50103919"
[[3]]$user
[[3]]$user$name
[1] "bpaslc"
[[3]]$user$id
[1] 1639
[[3]]$user$genotypes
[[3]]$user$genotypes[[1]]
[[3]]$user$genotypes[[1]]$genotype_id
[1] 933
[[3]]$user$genotypes[[1]]$local_genotype
[1] "CT"allgensnp("rs7412", df = TRUE)[1:10, ] snp_name snp_chromosome snp_position user_name user_id
1 rs7412 19 50103919 Lisa 1653
2 rs7412 19 50103919 karl 1651
3 rs7412 19 50103919 bpaslc 1639
4 rs7412 19 50103919 Wally97 1641
5 rs7412 19 50103919 Paul 1635
6 rs7412 19 50103919 Arthur 1621
7 rs7412 19 50103919 Justin Anzalone 1620
8 rs7412 19 50103919 Brenda Ramos 1619
9 rs7412 19 50103919 Jeremy McEntire 1617
10 rs7412 19 50103919 jonathan 1616
genotype_id genotype
1 944 CC
2 943 CC
3 933 CT
4 935 CT
5 931 CC
6 919 CC
7 918 CC
8 917 CC
9 915 CC
10 914 CTGet all data
allphenotypes(df = TRUE)[1:10, ] id characteristic known_variations number_of_users
1 1 Eye color Brown 411
2 1 Eye color Brown-green 411
3 1 Eye color Blue-green 411
4 1 Eye color Blue-grey 411
5 1 Eye color Green 411
6 1 Eye color Blue 411
7 1 Eye color Hazel 411
8 1 Eye color Mixed 411
9 1 Eye color Gray-blue 411
10 1 Eye color Blue-grey; broken amber collarette 411Output a list, then call the characterisitc of interest by 'id' or 'characteristic'
datalist <- allphenotypes()
names(datalist)[1:10] # get list of all characteristics you can call [1] "Eye color" "Handedness" "Height"
[4] "Sex" "Hair Color" "Tongue roller"
[7] "Colour Blindness" "Lactose intolerance" "white skin"
[10] "Coffee consumption" datalist[["ADHD"]] # get data.frame for 'ADHD' id characteristic known_variations
1 29 ADHD False
2 29 ADHD True
3 29 ADHD Undiagnosed, but probably true
4 29 ADHD No
5 29 ADHD Yes
6 29 ADHD Not diagnosed
7 29 ADHD Diagnosed as not having but with some signs
8 29 ADHD Mthfr c677t
number_of_users
1 114
2 114
3 114
4 114
5 114
6 114
7 114
8 114datalist[c("mouth size", "SAT Writing")] # get data.frame for 'ADHD' $`mouth size`
id characteristic known_variations number_of_users
1 120 mouth size Medium 44
2 120 mouth size Small 44
3 120 mouth size Large 44
$`SAT Writing`
id characteristic known_variations number_of_users
1 41 SAT Writing 750 37
2 41 SAT Writing Tested before 2005 37
3 41 SAT Writing 800 37
4 41 SAT Writing Country with no sat 37
5 41 SAT Writing N/a 37
6 41 SAT Writing Never & have ba & above 37
7 41 SAT Writing 720 37
8 41 SAT Writing 511 37
9 41 SAT Writing Did well - don't remember score 37
10 41 SAT Writing 700 37Get just the metadata
annotations(snp = "rs7903146", output = "metadata") .id V1
1 name rs7903146
2 chromosome 10
3 position 114748339Just from PLOS journals
annotations(snp = "rs7903146", output = "plos")[c(1:10), ] author
1 Marguerite R. Irvin
2 Huixiao Hong
3 Daniel Savic
4 Jeanne M. McCaffery
5 Cornelia Then
6 Changzheng Dong
7 Anette P. Gjesing
8 Jeanne M. McCaffery
9 Jinjin Wang
10 Jingxiang Chen
title
1 Genome-Wide Detection of Allele Specific Copy Number Variation Associated with Insulin Resistance in African Americans from the HyperGEN Study
2 Technical Reproducibility of Genotyping SNP Arrays Used in Genome-Wide Association Studies
3 An <i>in vivo cis</i>-Regulatory Screen at the Type 2 Diabetes Associated <i>TCF7L2</i> Locus Identifies Multiple Tissue-Specific Enhancers
4 <i>TCF7L2</i> Polymorphism, Weight Loss and Proinsulin∶Insulin Ratio in the Diabetes Prevention Program
5 Plasma Metabolomics Reveal Alterations of Sphingo- and Glycerophospholipid Levels in Non-Diabetic Carriers of the Transcription Factor 7-Like 2 Polymorphism rs7903146
6 Gene-Centric Characteristics of Genome-Wide Association Studies
7 The Effect of <i>PCSK1</i> Variants on Waist, Waist-Hip Ratio and Glucose Metabolism Is Modified by Sex and Glucose Tolerance Status
8 <i>TCF7L2</i> Polymorphism, Weight Loss and Proinsulin∶Insulin Ratio in the Diabetes Prevention Program
9 Association of rs7903146 (IVS3C/T) and rs290487 (IVS3C/T) Polymorphisms in <i>TCF7L2</i> with Type 2 Diabetes in 9,619 Han Chinese Population
10 Association between TCF7L2 Gene Polymorphism and Cancer Risk: A Meta-Analysis
publication_date number_of_readers
1 2011-08-25T00:00:00Z 1427
2 2012-09-07T00:00:00Z 509
3 2012-05-10T00:00:00Z 697
4 2011-07-26T00:00:00Z 1421
5 2013-10-24T00:00:00Z none
6 2007-12-05T00:00:00Z none
7 2011-09-14T00:00:00Z 296
8 2011-07-26T00:00:00Z 1421
9 2013-03-25T00:00:00Z none
10 2013-08-09T00:00:00Z none
url
1 http://dx.doi.org/10.1371/journal.pone.0024052
2 http://dx.doi.org/10.1371/journal.pone.0044483
3 http://dx.doi.org/10.1371/journal.pone.0036501
4 http://dx.doi.org/10.1371/journal.pone.0021518
5 http://dx.doi.org/10.1371/journal.pone.0078430
6 http://dx.doi.org/10.1371/journal.pone.0001262
7 http://dx.doi.org/10.1371/journal.pone.0023907
8 http://dx.doi.org/10.1371/journal.pone.0021518
9 http://dx.doi.org/10.1371/journal.pone.0059053
10 http://dx.doi.org/10.1371/journal.pone.0071730
doi
1 10.1371/journal.pone.0024052
2 10.1371/journal.pone.0044483
3 10.1371/journal.pone.0036501
4 10.1371/journal.pone.0021518
5 10.1371/journal.pone.0078430
6 10.1371/journal.pone.0001262
7 10.1371/journal.pone.0023907
8 10.1371/journal.pone.0021518
9 10.1371/journal.pone.0059053
10 10.1371/journal.pone.0071730Just from SNPedia
annotations(snp = "rs7903146", output = "snpedia") url
1 http://www.snpedia.com/index.php/Rs7903146(C;C)
2 http://www.snpedia.com/index.php/Rs7903146(C;T)
3 http://www.snpedia.com/index.php/Rs7903146(T;T)
summary
1 Normal (lower) risk of Type 2 Diabetes and Gestational Diabetes.
2 1.4x increased risk for diabetes (and perhaps colon cancer).
3 2x increased risk for Type-2 diabetesGet all annotations
annotations(snp = "rs7903146", output = "all")[1:10, ] .id author
1 mendeley Dhanasekaran Bodhini
2 mendeley Ludmila Alves Sanches Dutra
3 mendeley Thomas Hansen
4 mendeley Laura J Rasmussen-Torvik
5 mendeley Yu Yan
6 mendeley K Pilgaard
7 mendeley André Gustavo P Sousa
8 mendeley Stéphane Cauchi
9 mendeley Panagiotis Christopoulos
10 mendeley Martha L Slattery
title
1 The rs12255372(G/T) and rs7903146(C/T) polymorphisms of the TCF7L2 gene are associated with type 2 diabetes mellitus in Asian Indians.
2 Allele-specific PCR assay to genotype SNP rs7903146 in TCF7L2 gene for rapid screening of diabetes susceptibility.
3 At-Risk Variant in TCF7L2 for Type II Diabetes Increases Risk of Schizophrenia.
4 Preliminary report: No association between TCF7L2 rs7903146 and euglycemic-clamp-derived insulin sensitivity in a mixed-age cohort.
5 The transcription factor 7-like 2 (TCF7L2) polymorphism may be associated with focal arteriolar narrowing in Caucasians with hypertension or without diabetes: the ARIC Study
6 The T allele of rs7903146 TCF7L2 is associated with impaired insulinotropic action of incretin hormones, reduced 24 h profiles of plasma insulin and glucagon, and increased hepatic glucose production in young healthy men.
7 TCF7L2 Polymorphism rs7903146 Is Associated with Coronary Artery Disease Severity and Mortality
8 TCF7L2 rs7903146 variant does not associate with smallness for gestational age in the French population
9 Genetic variants in TCF7L2 and KCNJ11 genes in a Greek population with polycystic ovary syndrome.
10 Transcription factor 7-like 2 polymorphism and colon cancer.
publication_year number_of_readers open_access
1 2007 8 FALSE
2 2008 5 FALSE
3 2011 1 FALSE
4 2009 3 FALSE
5 2010 5 TRUE
6 2009 8 FALSE
7 2009 11 TRUE
8 2007 4 TRUE
9 2008 2 FALSE
10 2008 4 FALSE
url
1 http://www.mendeley.com/research/rs12255372-g-t-rs7903146-c-t-polymorphisms-tcf7l2-gene-associated-type-2-diabetes-mellitus-asian-ind-1/
2 http://www.mendeley.com/research/allelespecific-pcr-assay-to-genotype-snp-rs7903146-in-tcf7l2-gene-for-rapid-screening-of-diabetes-susceptibility/
3 http://www.mendeley.com/research/atrisk-variant-tcf7l2-type-ii-diabetes-increases-risk-schizophrenia/
4 http://www.mendeley.com/research/preliminary-report-association-between-tcf7l2-rs7903146-euglycemicclampderived-insulin-sensitivity-mixedage-cohort/
5 http://www.mendeley.com/research/transcription-factor-7like-2-tcf7l2-polymorphism-associated-focal-arteriolar-narrowing-caucasians-hypertension-diabetes-aric-study-7/
6 http://www.mendeley.com/research/t-allele-rs7903146-tcf7l2-associated-impaired-insulinotropic-action-incretin-hormones-reduced-24-h-profiles-plasma-insulin-glucagon-increased-hepatic-glucose-production-young-healthy-men/
7 http://www.mendeley.com/research/tcf7l2-polymorphism-rs7903146-associated-coronary-artery-disease-severity-mortality/
8 http://www.mendeley.com/research/tcf7l2-rs7903146-variant-does-not-associate-with-smallness-for-gestational-age-in-the-french-population/
9 http://www.mendeley.com/research/genetic-variants-tcf7l2-kcnj11-genes-greek-population-polycystic-ovary-syndrome/
10 http://www.mendeley.com/research/transcription-factor-7-like-2-polymorphism-colon-cancer/
doi publication_date summary first_author
1 none <NA> <NA> <NA>
2 none <NA> <NA> <NA>
3 10.1016/j.biopsych.2011.01.031 <NA> <NA> <NA>
4 none <NA> <NA> <NA>
5 10.1186/1472-6823-10-9 <NA> <NA> <NA>
6 none <NA> <NA> <NA>
7 10.1371/journal.pone.0007697 <NA> <NA> <NA>
8 10.1186/1471-2350-8-37 <NA> <NA> <NA>
9 none <NA> <NA> <NA>
10 none <NA> <NA> <NA>
pubmed_link journal trait pvalue pvalue_description confidence_interval
1 <NA> <NA> <NA> NA <NA> <NA>
2 <NA> <NA> <NA> NA <NA> <NA>
3 <NA> <NA> <NA> NA <NA> <NA>
4 <NA> <NA> <NA> NA <NA> <NA>
5 <NA> <NA> <NA> NA <NA> <NA>
6 <NA> <NA> <NA> NA <NA> <NA>
7 <NA> <NA> <NA> NA <NA> <NA>
8 <NA> <NA> <NA> NA <NA> <NA>
9 <NA> <NA> <NA> NA <NA> <NA>
10 <NA> <NA> <NA> NA <NA> <NA>data <- users(df = TRUE)
head(data[[1]]) # users with links to genome data
fetch_genotypes(url = data[[1]][1, "genotypes.download_url"], rows = 15)genotypes(snp = "rs9939609", userid = 1)$snp
$snp$name
[1] "rs9939609"
$snp$chromosome
[1] "16"
$snp$position
[1] "52378028"
$user
$user$name
[1] "Bastian Greshake"
$user$id
[1] 1
$user$genotypes
$user$genotypes[[1]]
$user$genotypes[[1]]$genotype_id
[1] 9
$user$genotypes[[1]]$local_genotype
[1] "AT"genotypes("rs9939609", userid = "1,6,8", df = TRUE) snp_name snp_chromosome snp_position user_name user_id
1 rs9939609 16 52378028 Bastian Greshake 1
2 rs9939609 16 52378028 Nash Parovoz 6
3 rs9939609 16 52378028 Samantha 8
genotype_id genotype
1 9 AT
2 5 AT
3 2 TTgenotypes("rs9939609", userid = "1-2", df = FALSE)[[1]]
[[1]]$snp
[[1]]$snp$name
[1] "rs9939609"
[[1]]$snp$chromosome
[1] "16"
[[1]]$snp$position
[1] "52378028"
[[1]]$user
[[1]]$user$name
[1] "Bastian Greshake"
[[1]]$user$id
[1] 1
[[1]]$user$genotypes
[[1]]$user$genotypes[[1]]
[[1]]$user$genotypes[[1]]$genotype_id
[1] 9
[[1]]$user$genotypes[[1]]$local_genotype
[1] "AT"
[[2]]
[[2]]$snp
[[2]]$snp$name
[1] "rs9939609"
[[2]]$snp$chromosome
[1] "16"
[[2]]$snp$position
[1] "52378028"
[[2]]$user
[[2]]$user$name
[1] "Senficon"
[[2]]$user$id
[1] 2
[[2]]$user$genotypes
list()phenotypes(userid = 1)$phenotypes[1:3]$`white skin`
$`white skin`$phenotype_id
[1] 4
$`white skin`$variation
[1] "Caucasian"
$`Lactose intolerance`
$`Lactose intolerance`$phenotype_id
[1] 2
$`Lactose intolerance`$variation
[1] "lactose-tolerant"
$`Eye color`
$`Eye color`$phenotype_id
[1] 1
$`Eye color`$variation
[1] "blue-green"phenotypes(userid = "1,6,8", df = TRUE)[[1]][1:10, ] phenotype phenotypeID variation
1 white skin 4 Caucasian
2 Lactose intolerance 2 lactose-tolerant
3 Eye color 1 blue-green
4 Hair Type 16 straight
5 Height 15 Tall ( >180cm )
6 Ability to Tan 14 Yes
7 Short-sightedness (Myopia) 21 low
8 Nicotine dependence 20 Smoker. 10 cigarettes/day
9 Beard Color 12 Blonde
10 Colour Blindness 25 Falseout <- phenotypes(userid = "1-8", df = TRUE)
lapply(out, head)$`Bastian Greshake`
phenotype phenotypeID variation
1 white skin 4 Caucasian
2 Lactose intolerance 2 lactose-tolerant
3 Eye color 1 blue-green
4 Hair Type 16 straight
5 Height 15 Tall ( >180cm )
6 Ability to Tan 14 Yes
$Senficon
phenotype phenotypeID variation
1 no data no data no data
$`no info on user_3`
phenotype phenotypeID variation
1 no data no data no data
$`no info on user_4`
phenotype phenotypeID variation
1 no data no data no data
$`no info on user_5`
phenotype phenotypeID variation
1 no data no data no data
$`Nash Parovoz`
phenotype phenotypeID variation
1 Handedness 3 right-handed
2 Eye color 1 brown
3 white skin 4 Caucasian
4 Lactose intolerance 2 lactose-tolerant
5 Ability to find a bug in openSNP 5 extremely high
6 Number of wisdom teeth 57 4
$`no info on user_7`
phenotype phenotypeID variation
1 no data no data no data
$Samantha
phenotype phenotypeID variation
1 Short-sightedness (Myopia) 21 medium
2 Handedness 3 left-handed
3 Lactose intolerance 2 lactose-intolerant
4 Eye color 1 Brown
5 Ability to Tan 14 Yes
6 Nicotine dependence 20 ex-smoker, 7 cigarettes/dayphenotypes_byid(phenotypeid = 12, return_ = "desc")$id
[1] 12
$characteristic
[1] "Beard Color"
$description
[1] "coloration of facial hair"phenotypes_byid(phenotypeid = 12, return_ = "knownvars")$known_variations
[1] "Red"
[2] "Blonde"
[3] "Red-brown"
[4] "Red-blonde-brown-black(in diferent parts i have different color,for example near the lips blond-red"
[5] "No beard-female"
[6] "Brown-black"
[7] "Blonde-brown"
[8] "Black"
[9] "Dark brown with minor blondish-red"
[10] "Brown-grey"
[11] "Red-blonde-brown-black"
[12] "Blond-brown"
[13] "Brown, some red"
[14] "Brown"
[15] "Brown-gray"
[16] "Never had a beard"
[17] "I'm a woman"
[18] "Black-brown-blonde"
[19] "Was red-brown now mixed with gray,"
[20] "Red-blonde-brown" phenotypes_byid(phenotypeid = 12, return_ = "users")[1:10, ] user_id
1 22
2 1
3 26
4 10
5 14
6 42
7 45
8 16
9 8
10 661
variation
1 Red
2 Blonde
3 red-brown
4 Red-Blonde-Brown-Black(in diferent parts i have different color,for example near the lips blond-red
5 No beard-female
6 Brown-black
7 Red-Blonde-Brown-Black(in diferent parts i have different color,for example near the lips blond-red
8 blonde-brown
9 No beard-female
10 Brown-blackdata <- users(df = FALSE)
data[1:2][[1]]
[[1]]$name
[1] "gigatwo"
[[1]]$id
[1] 31
[[1]]$genotypes
list()
[[2]]
[[2]]$name
[1] "Anu Acharya"
[[2]]$id
[1] 385
[[2]]$genotypes
list()LDSearch("rs420358")Querying SNAP...
Querying NCBI for up-to-date SNP annotation information...
Done!$rs420358
Proxy SNP Distance RSquared DPrime GeneVariant GeneName
4 rs420358 rs420358 0 1.000 1.000 INTERGENIC N/A
5 rs442418 rs420358 122 1.000 1.000 INTERGENIC N/A
8 rs718223 rs420358 1168 1.000 1.000 INTERGENIC N/A
6 rs453604 rs420358 2947 1.000 1.000 INTERGENIC N/A
3 rs372946 rs420358 -70 0.943 1.000 INTERGENIC N/A
1 rs10889290 rs420358 3987 0.800 1.000 INTERGENIC N/A
2 rs10889291 rs420358 4334 0.800 1.000 INTERGENIC N/A
7 rs4660403 rs420358 7021 0.800 1.000 INTERGENIC N/A
GeneDescription Major Minor MAF NObserved Chromosome_NCBI Marker_NCBI
4 N/A C A 0.167 120 1 rs420358
5 N/A C T 0.167 120 1 rs442418
8 N/A A G 0.167 120 1 rs718223
6 N/A A G 0.167 120 1 rs453604
3 N/A G C 0.175 120 1 rs372946
1 N/A G A 0.200 120 1 rs10889290
2 N/A C T 0.200 120 1 rs10889291
7 N/A A G 0.200 120 1 rs4660403
Class_NCBI Gene_NCBI Alleles_NCBI Major_NCBI Minor_NCBI MAF_NCBI
4 snp <NA> G/T G T 0.0891
5 snp <NA> A/G G A 0.0891
8 snp <NA> A/G A G 0.0891
6 snp <NA> A/G A G 0.0836
3 snp <NA> C/G G C 0.0891
1 snp <NA> A/G G A 0.1015
2 snp <NA> C/T C T 0.1015
7 snp <NA> A/G A G 0.0969
BP_NCBI
4 40806910
5 40807032
8 40808078
6 40809857
3 40806840
1 40810897
2 40811244
7 40813931An example with both merged SNPs, non-SNV SNPs, regular SNPs, SNPs not found, microsatellite
snps <- c("rs332", "rs420358", "rs1837253", "rs1209415715", "rs111068718")
NCBI_snp_query(snps) Query Chromosome Marker Class Gene Alleles Major
1 rs332 7 rs121909001 in-del CFTR -/TTT <NA>
2 rs420358 1 rs420358 snp <NA> G/T G
3 rs1837253 5 rs1837253 snp <NA> C/T C
4 rs111068718 <NA> rs111068718 microsatellite <NA> (GT)21/24 <NA>
Minor MAF BP
1 <NA> NA 117199646
2 T 0.0891 40806910
3 T 0.3627 110401871
4 <NA> NA NA