rsnps tutorial
for v0.2.0
Installation
Stable version from CRAN
install.packages("rsnps")
Or get from Github
install.packages("devtools")
devtools::install_github("ropensci/rsnps")
library("rsnps")
OpenSNP data
All Genotypes
Get genotype data for all users at a particular SNP
allgensnp(snp='rs7412')[1:3]
#> https://opensnp.org/snps/rs7412.json
#> [[1]]
#> [[1]]$snp
#> [[1]]$snp$name
#> [1] "rs7412"
#>
#> [[1]]$snp$chromosome
#> [1] "19"
#>
#> [[1]]$snp$position
#> [1] "44908822"
#>
#>
#> [[1]]$user
#> [[1]]$user$name
#> [1] "Luke Reid"
#>
#> [[1]]$user$id
#> [1] 6621
#>
#> [[1]]$user$genotypes
#> [[1]]$user$genotypes[[1]]
#> [[1]]$user$genotypes[[1]]$genotype_id
#> [1] 5023
#>
#> [[1]]$user$genotypes[[1]]$local_genotype
#> [1] "CC"
#>
#>
#>
#>
#>
#> [[2]]
#> [[2]]$snp
#> [[2]]$snp$name
#> [1] "rs7412"
#>
#> [[2]]$snp$chromosome
#> [1] "19"
#>
#> [[2]]$snp$position
#> [1] "44908822"
#>
#>
#> [[2]]$user
#> [[2]]$user$name
#> [1] "Ganesha18"
#>
#> [[2]]$user$id
#> [1] 6598
#>
#> [[2]]$user$genotypes
#> [[2]]$user$genotypes[[1]]
#> [[2]]$user$genotypes[[1]]$genotype_id
#> [1] 5001
#>
#> [[2]]$user$genotypes[[1]]$local_genotype
#> [1] "CC"
#>
#>
#>
#>
#>
#> [[3]]
#> [[3]]$snp
#> [[3]]$snp$name
#> [1] "rs7412"
#>
#> [[3]]$snp$chromosome
#> [1] "19"
#>
#> [[3]]$snp$position
#> [1] "44908822"
#>
#>
#> [[3]]$user
#> [[3]]$user$name
#> [1] "mdmoore07"
#>
#> [[3]]$user$id
#> [1] 6597
#>
#> [[3]]$user$genotypes
#> [[3]]$user$genotypes[[1]]
#> [[3]]$user$genotypes[[1]]$genotype_id
#> [1] 5000
#>
#> [[3]]$user$genotypes[[1]]$local_genotype
#> [1] "--"
allgensnp('rs7412', df=TRUE)[1:10,]
#> https://opensnp.org/snps/rs7412.json
#> snp_name snp_chromosome snp_position user_name user_id genotype_id
#> 1 rs7412 19 44908822 Luke Reid 6621 5023
#> 2 rs7412 19 44908822 Ganesha18 6598 5001
#> 3 rs7412 19 44908822 mdmoore07 6597 5000
#> 4 rs7412 19 44908822 KevinHendricks 6590 4988
#> 5 rs7412 19 44908822 jlafount 6589 4987
#> 6 rs7412 19 44908822 fawaz 6587 4985
#> 7 rs7412 19 44908822 tzankel 6582 4980
#> 8 rs7412 19 44908822 David53 3997 2691
#> 9 rs7412 19 44908822 marsha 6577 4974
#> 10 rs7412 19 44908822 wbworkman 6574 4973
#> genotype
#> 1 CC
#> 2 CC
#> 3 --
#> 4 CC
#> 5 CC
#> 6 CC
#> 7 CT
#> 8 CT
#> 9 CC
#> 10 CC
All Phenotypes
Get all phenotypes, their variations, and how many users have data available for a given phenotype
Get all data
allphenotypes(df = TRUE)[1:10,]
#> id characteristic known_variations number_of_users
#> 1 1 Eye color Brown 1168
#> 2 1 Eye color Brown-green 1168
#> 3 1 Eye color Blue-green 1168
#> 4 1 Eye color Blue-grey 1168
#> 5 1 Eye color Green 1168
#> 6 1 Eye color Blue 1168
#> 7 1 Eye color Hazel (brown/green) 1168
#> 8 1 Eye color Hazel 1168
#> 9 1 Eye color Mixed 1168
#> 10 1 Eye color Gray-blue 1168
Output a list, then call the characterisitc of interest by ‘id’ or ‘characteristic’
datalist <- allphenotypes()
Get a list of all characteristics you can call
names(datalist)[1:10]
#> [1] "Eye color" "Lactose intolerance"
#> [3] "Handedness" "white skin"
#> [5] "Ability to find a bug in openSNP" "Beard Color"
#> [7] "Hair Color" "Ability to Tan"
#> [9] "Height" "Hair Type"
Get data.frame for ADHD
datalist[["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
#> 9 29 ADHD Rs1801260
#> 10 29 ADHD Adult onset
#> number_of_users
#> 1 261
#> 2 261
#> 3 261
#> 4 261
#> 5 261
#> 6 261
#> 7 261
#> 8 261
#> 9 261
#> 10 261
Get data.frame for mouth size and SAT Writing
datalist[c("mouth size","SAT Writing")]
#> $`mouth size`
#> id characteristic known_variations number_of_users
#> 1 120 mouth size Medium 173
#> 2 120 mouth size Small 173
#> 3 120 mouth size Large 173
#> 4 120 mouth size Slightly wide mouth 173
#>
#> $`SAT Writing`
#> id characteristic
#> 1 41 SAT Writing
#> 2 41 SAT Writing
#> 3 41 SAT Writing
#> 4 41 SAT Writing
#> 5 41 SAT Writing
#> 6 41 SAT Writing
#> 7 41 SAT Writing
#> 8 41 SAT Writing
#> 9 41 SAT Writing
#> 10 41 SAT Writing
#> 11 41 SAT Writing
#> 12 41 SAT Writing
#> 13 41 SAT Writing
#> 14 41 SAT Writing
#> 15 41 SAT Writing
#> known_variations number_of_users
#> 1 750 92
#> 2 Tested before 2005 92
#> 3 800 92
#> 4 Country with no sat 92
#> 5 N/a 92
#> 6 Never & have ba & above 92
#> 7 720 92
#> 8 Did well - don't remember score 92
#> 9 511 92
#> 10 700 92
#> 11 760 92
#> 12 780 92
#> 13 Not part of sat when i took test in august 1967 at uiuc 92
#> 14 Not part of sat in 1961 92
#> 15 620 92
Annotations
Get just the metadata
annotations(snp = 'rs7903146', output = 'metadata')
#> https://opensnp.org/snps/json/annotation/rs7903146.json
#> .id V1
#> 1 name rs7903146
#> 2 chromosome 10
#> 3 position 112998590
Just from PLOS journals
annotations(snp = 'rs7903146', output = 'plos')[c(1:2),]
#> https://opensnp.org/snps/json/annotation/rs7903146.json
#> author
#> 1 Maggie C. Y. Ng
#> 2 André Gustavo P. Sousa
#> title
#> 1 Meta-Analysis of Genome-Wide Association Studies in African Americans Provides Insights into the Genetic Architecture of Type 2 Diabetes
#> 2 Genetic Variants of Diabetes Risk and Incident Cardiovascular Events in Chronic Coronary Artery Disease
#> publication_date number_of_readers
#> 1 2014-08-07T00:00:00.000Z 7783
#> 2 2011-01-20T00:00:00.000Z 2080
#> url
#> 1 https://doi.org/10.1371/journal.pgen.1004517
#> 2 https://doi.org/10.1371/journal.pone.0016341
#> doi
#> 1 10.1371/journal.pgen.1004517
#> 2 10.1371/journal.pone.0016341
Just from SNPedia
annotations(snp = 'rs7903146', output = 'snpedia')
#> https://opensnp.org/snps/json/annotation/rs7903146.json
#> 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 diabetes
Get all annotations
annotations(snp = 'rs7903146', output = 'all')[1:5,]
#> https://opensnp.org/snps/json/annotation/rs7903146.json
#> .id author
#> 1 mendeley T E Meyer
#> 2 mendeley Camilla Cervin
#> 3 mendeley Nicholette D Palmer
#> 4 mendeley Ashis K Mondal
#> 5 mendeley Julian Munoz
#> title
#> 1 Diabetes genes and prostate cancer in the Atherosclerosis Risk in Communities study
#> 2 Diabetes in Adults , Type 1 Diabetes , and Type 2 Diabetes GENETICS OF LADA
#> 3 Association of TCF7L2 gene polymorphisms with reduced acute insulin response in Hispanic Americans.
#> 4 Genotype and tissue-specific effects on alternative splicing of the transcription factor 7-like 2 gene in humans.
#> 5 Polymorphism in the transcription factor 7-like 2 (TCF7L2) gene is associated with reduced insulin secretion in nondiabetic women.
#> publication_year number_of_readers open_access
#> 1 2010 3 TRUE
#> 2 2008 2 FALSE
#> 3 2008 8 FALSE
#> 4 2010 13 TRUE
#> 5 2006 10 TRUE
#> url
#> 1 http://www.mendeley.com/research/diabetes-genes-prostate-cancer-atherosclerosis-risk-communities-study-4/
#> 2 http://www.mendeley.com/research/diabetes-adults-type-1-diabetes-type-2-diabetes-genetics-lada/
#> 3 http://www.mendeley.com/research/association-tcf7l2-gene-polymorphisms-reduced-acute-insulin-response-hispanic-americans/
#> 4 http://www.mendeley.com/research/genotype-tissuespecific-effects-alternative-splicing-transcription-factor-7like-2-gene-humans/
#> 5 http://www.mendeley.com/research/polymorphism-transcription-factor-7like-2-tcf7l2-gene-associated-reduced-insulin-secretion-nondiabet/
#> doi publication_date summary
#> 1 19/2/558 [pii]\\r10.1158/1055-9965.EPI-09-0902 <NA> <NA>
#> 2 10.2337/db07-0299.Leif <NA> <NA>
#> 3 10.1210/jc.2007-1225 <NA> <NA>
#> 4 10.1210/jc.2009-2064 <NA> <NA>
#> 5 10.2337/db06-0574 <NA> <NA>
#> first_author pubmed_link journal trait pvalue pvalue_description
#> 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>
#> confidence_interval
#> 1 <NA>
#> 2 <NA>
#> 3 <NA>
#> 4 <NA>
#> 5 <NA>
Download
Download genotype data for a user from 23andme or other repo. (not evaluated in this example)
data <- users(df=TRUE)
head( data[[1]] )
fetch_genotypes(url = data[[1]][1,"genotypes.download_url"], rows=15)
Genotype user data
Genotype data for one or multiple users
genotypes(snp='rs9939609', userid=1)
#> https://opensnp.org/snps/json/rs9939609/1.json
#> $snp
#> $snp$name
#> [1] "rs9939609"
#>
#> $snp$chromosome
#> [1] "16"
#>
#> $snp$position
#> [1] "53786615"
#>
#>
#> $user
#> $user$name
#> [1] "Bastian Greshake Tzovaras"
#>
#> $user$id
#> [1] 1
#>
#> $user$genotypes
#> $user$genotypes[[1]]
#> $user$genotypes[[1]]$genotype_id
#> [1] 9
#>
#> $user$genotypes[[1]]$local_genotype
#> [1] "AT"
genotypes('rs9939609', userid='1,6,8', df=TRUE)
#> https://opensnp.org/snps/json/rs9939609/1,6,8.json
#> snp_name snp_chromosome snp_position user_name user_id
#> 1 rs9939609 16 53786615 Bastian Greshake Tzovaras 1
#> 2 rs9939609 16 53786615 Nash Parovoz 6
#> 3 rs9939609 16 53786615 Samantha B. Clark 8
#> genotype_id genotype
#> 1 9 AT
#> 2 5 AT
#> 3 2 TT
genotypes('rs9939609', userid='1-2', df=FALSE)
#> https://opensnp.org/snps/json/rs9939609/1-2.json
#> [[1]]
#> [[1]]$snp
#> [[1]]$snp$name
#> [1] "rs9939609"
#>
#> [[1]]$snp$chromosome
#> [1] "16"
#>
#> [[1]]$snp$position
#> [1] "53786615"
#>
#>
#> [[1]]$user
#> [[1]]$user$name
#> [1] "Bastian Greshake Tzovaras"
#>
#> [[1]]$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] "53786615"
#>
#>
#> [[2]]$user
#> [[2]]$user$name
#> [1] "Senficon"
#>
#> [[2]]$user$id
#> [1] 2
#>
#> [[2]]$user$genotypes
#> list()
Phenotype user data
Get phenotype data for one or multiple users
phenotypes(userid=1)$phenotypes[1:3]
#> https://opensnp.org/phenotypes/json/1.json
#> $syndactyly
#> $syndactyly$phenotype_id
#> [1] 372
#>
#> $syndactyly$variation
#> [1] "None"
#>
#>
#> $`Allergy to Hair Dye`
#> $`Allergy to Hair Dye`$phenotype_id
#> [1] 370
#>
#> $`Allergy to Hair Dye`$variation
#> [1] "None"
#>
#>
#> $`Do You Have Lucid Dreams?`
#> $`Do You Have Lucid Dreams?`$phenotype_id
#> [1] 328
#>
#> $`Do You Have Lucid Dreams?`$variation
#> [1] "No"
phenotypes(userid='1,6,8', df=TRUE)[[1]][1:10,]
#> https://opensnp.org/phenotypes/json/1,6,8.json
#> phenotype phenotypeID variation
#> 1 syndactyly 372 None
#> 2 Allergy to Hair Dye 370 None
#> 3 Do You Have Lucid Dreams? 328 No
#> 4 Multiple Sclerosis 215 None
#> 5 Can you smell cut-grass? 168 Yes
#> 6 Daily Sleep Duration (hours) 269 4-6
#> 7 blood type 290 A+
#> 8 Cocaine addiction 486 No
#> 9 macular degeneration 542 No
#> 10 Diet 533 Vegetarian
out <- phenotypes(userid='1-8', df=TRUE)
#> https://opensnp.org/phenotypes/json/1-8.json
lapply(out, head)
#> $`Bastian Greshake Tzovaras`
#> phenotype phenotypeID variation
#> 1 syndactyly 372 None
#> 2 Allergy to Hair Dye 370 None
#> 3 Do You Have Lucid Dreams? 328 No
#> 4 Multiple Sclerosis 215 None
#> 5 Can you smell cut-grass? 168 Yes
#> 6 Daily Sleep Duration (hours) 269 4-6
#>
#> $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 B. Clark`
#> phenotype phenotypeID variation
#> 1 Gambling 539 No
#> 2 Caffeine dependence 538 No
#> 3 Dietary supplements used 534 b12
#> 4 Diet 533 Vegan / plant-based
#> 5 Tooth sensitivity 532 Sweet, cold
#> 6 OCD - Obsessive-Compulsive Disorder 555 No
All known variations
Get all known variations and all users sharing that phenotype for one phenotype(-ID).
phenotypes_byid(phenotypeid=12, return_ = 'desc')
#> https://opensnp.org/phenotypes/json/variations/12.json
#> $id
#> [1] 12
#>
#> $characteristic
#> [1] "Beard Color"
#>
#> $description
#> [1] "coloration of facial hair"
phenotypes_byid(phenotypeid=12, return_ = 'knownvars')
#> https://opensnp.org/phenotypes/json/variations/12.json
#> $known_variations
#> $known_variations[[1]]
#> [1] "Red"
#>
#> $known_variations[[2]]
#> [1] "Blonde"
#>
#> $known_variations[[3]]
#> [1] "Red-brown"
#>
#> $known_variations[[4]]
#> [1] "Red-blonde-brown-black(in diferent parts i have different color,for example near the lips blond-red"
#>
#> $known_variations[[5]]
#> [1] "No beard-female"
#>
#> $known_variations[[6]]
#> [1] "Brown-black"
#>
#> $known_variations[[7]]
#> [1] "Blonde-brown"
#>
#> $known_variations[[8]]
#> [1] "Black"
#>
#> $known_variations[[9]]
#> [1] "Dark brown with minor blondish-red"
#>
#> $known_variations[[10]]
#> [1] "Brown-grey"
#>
#> $known_variations[[11]]
#> [1] "Red-blonde-brown-black"
#>
#> $known_variations[[12]]
#> [1] "Blond-brown"
#>
#> $known_variations[[13]]
#> [1] "Brown, some red"
#>
#> $known_variations[[14]]
#> [1] "Brown"
#>
#> $known_variations[[15]]
#> [1] "Brown-gray"
#>
#> $known_variations[[16]]
#> [1] "Never had a beard"
#>
#> $known_variations[[17]]
#> [1] "I'm a woman"
#>
#> $known_variations[[18]]
#> [1] "Black-brown-blonde"
#>
#> $known_variations[[19]]
#> [1] "Was red-brown now mixed with gray,"
#>
#> $known_variations[[20]]
#> [1] "Red-blonde-brown"
#>
#> $known_variations[[21]]
#> [1] "Dark brown w/few blonde & red hairs"
#>
#> $known_variations[[22]]
#> [1] "Dark blonde with red and light blonde on goatee area."
#>
#> $known_variations[[23]]
#> [1] "Black with few red hairs"
#>
#> $known_variations[[24]]
#> [1] "Black, graying"
#>
#> $known_variations[[25]]
#> [1] "Red, moustache still is, beard mostly white"
#>
#> $known_variations[[26]]
#> [1] "Blonde/brown-some black-and red on chin-all starting to gray"
#>
#> $known_variations[[27]]
#> [1] "Dark brown"
#>
#> $known_variations[[28]]
#> [1] "Every possible color, most hair shafts have more than one color at different points along the shaft"
phenotypes_byid(phenotypeid=12, return_ = 'users')[1:10,]
#> https://opensnp.org/phenotypes/json/variations/12.json
#> user_id
#> 1 22
#> 2 1
#> 3 26
#> 4 10
#> 5 14
#> 6 42
#> 7 45
#> 8 16
#> 9 8
#> 10 661
#> variation
#> 1 Red
#> 2 Blonde
#> 3 red-brown
#> 4 Red-Blonde-Brown-Black(in diferent parts i have different color,for example near the lips blond-red
#> 5 No beard-female
#> 6 Brown-black
#> 7 Red-Blonde-Brown-Black(in diferent parts i have different color,for example near the lips blond-red
#> 8 blonde-brown
#> 9 No beard-female
#> 10 Brown-black
OpenSNP users
data <- users(df=FALSE)
data[1:2]
#> [[1]]
#> [[1]]$name
#> [1] "gigatwo"
#>
#> [[1]]$id
#> [1] 31
#>
#> [[1]]$genotypes
#> list()
#>
#>
#> [[2]]
#> [[2]]$name
#> [1] "Anu Acharya"
#>
#> [[2]]$id
#> [1] 385
#>
#> [[2]]$genotypes
#> list()
NCBI SNP data
dbSNP
Query NCBI’s dbSNP for information on a set of SNPs
An 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)
#> Warning: use ncbi_snp_query instead - NCBI_snp_query removed in next
#> version
#> Warning: The following rsIds had no information available on NCBI:
#> rs1209415715, rs111068718
#> Warning: rs332 has been merged into rs121909001
#> Query Chromosome Marker Class Gene Alleles Major Minor MAF
#> 1 rs332 7 rs121909001 in-del CFTR -/TTT <NA> <NA> NA
#> 2 rs420358 1 rs420358 snp <NA> G,T G T NA
#> 3 rs1837253 5 rs1837253 snp <NA> C/T C T 0.3822
#> BP AncestralAllele
#> 1 117559593 <NA>
#> 2 40341239 T,T,T,T,T,T
#> 3 111066174 T,T,T,T,T,T
Citing
To cite rsnps in publications use:
Scott Chamberlain, Kevin Ushey and Hao Zhu (2016). rsnps: Get ‘SNP’ (‘Single-Nucleotide’ ‘Polymorphism’) Data on the Web. R package version 0.2.0. https://CRAN.R-project.org/package=rsnps
License and bugs
- License: MIT
- Report bugs at our Github repo for rsnps
