PLINK: Whole genome data analysis toolset plink...
Last original PLINK release is v1.07 (10-Oct-2009); PLINK 1.9 is now available for beta-testing

Whole genome association analysis toolset

Introduction | Basics | Download | Reference | Formats | Data management | Summary stats | Filters | Stratification | IBS/IBD | Association | Family-based | Permutation | LD calcualtions | Haplotypes | Conditional tests | Proxy association | Imputation | Dosage data | Meta-analysis | Result annotation | Clumping | Gene Report | Epistasis | Rare CNVs | Common CNPs | R-plugins | SNP annotation | Simulation | Profiles | ID helper | Resources | Flow chart | Misc. | FAQ | gPLINK

1. Introduction

2. Basic information

3. Download and general notes

4. Command reference table

5. Basic usage/data formats 6. Data management

7. Summary stats 8. Inclusion thresholds 9. Population stratification 10. IBS/IBD estimation 11. Association 12. Family-based association 13. Permutation procedures 14. LD calculations 15. Multimarker tests 16. Conditional haplotype tests 17. Proxy association 18. Imputation (beta) 19. Dosage data 20. Meta-analysis 21. Annotation 22. LD-based results clumping 23. Gene-based report 24. Epistasis 25. Rare CNVs 26. Common CNPs 27. R-plugins 28. Annotation web-lookup 29. Simulation tools 30. Profile scoring 31. ID helper 32. Resources 33. Flow-chart 34. Miscellaneous 35. FAQ & Hints

36. gPLINK

Proxy association

This page describes a convenience function designed to provide a quick representation of a single SNP association, in terms of the surrounding haplotypic background. Specifically, given a particular (reference) SNP this approach involves a) finding flanking markers and haplotypes (proxies) that are in strong linkage disequilibrium with the reference SNP, and b) testing these proxies for association with disease, within a haplotype-based framework.

There are three main applications of this utility, which are described in more detail and with examples in the main text below:
  • technical validation of single SNP results ( by looking for flanking haplotypes involving different markers that also show the same result )
  • refining a single SNP association signal ( is there a stronger association with a local haplotype? )
  • more robust single SNP tests ( by framing single SNP tests within a haplotypic framework, some degree of control against non-random genotyping failure can be achieved )

Proxy association: basic usage

The basic command for a proxy association report for a particular SNP, e.g. rs6703905, is

plink --file mydata --proxy-assoc rs10003

which generates the file
This file contains three main sections:
  • Report of all SNPs in local region (reference and flanking SNPs)
  • Report of haplotypes in local region
  • Report of proxies to reference SNP
For example, this is an example of a proxy association report for this SNP. We will step through each part of this output in detail below.
     *** Proxy haplotype association report for rs6703905 ***

         SNP      MAF     GENO       KB      RSQ       OR    CHISQ        P
    rs676913    0.333  0.00288    -19.2   0.0412     1.01   0.0347    0.852
    rs598816     0.31  0.00346    -14.6    0.011    0.951    0.904    0.342
    rs607131     0.27   0.0222   -0.505  0.00964    0.984   0.0912    0.763
   rs6703905   0.0255        0        0        *     1.88     14.3 0.000154
    rs535351    0.245        0     69.8   0.0584    0.983    0.095    0.758
  rs11587221     0.43 0.000577     73.2   0.0282     1.04     0.71      0.4
  rs10922605    0.289        0      102 0.000535     1.03    0.393    0.531

       ...*...       FREQ         OR      CHISQ          P
       TGTCGGC      0.034      0.924      0.342      0.559
       TGTCAGC     0.0575      0.975     0.0579       0.81
       CACCAAC     0.0736      0.938      0.464      0.496
       CATCAAC     0.0107       1.32       1.42      0.233
       TGTCAAC     0.0871      0.971       0.12       0.73
       CGTTGGT     0.0166      0.605       6.25     0.0124
       CACCGGT     0.0403       1.15       1.28      0.259
       TGTCGGT      0.136       1.08       1.28      0.257
       TGTCAGT      0.105      0.886       2.27      0.132
       CACCAAT      0.133      0.995    0.00556      0.941
       CATCAAT     0.0196       1.25       1.65      0.199
       TGTCAAT      0.244       1.05      0.603      0.437

Haplotype frequency estimation based on 3469 of 3469 founders
Omnibus haplotype test statistic: 14.9, df = 11, p = 0.188

           HAP       FREQ        RSQ         OR      CHISQ          P
       CGT ...     0.0233      0.913      0.537       12.9   0.000334
       CG. ...     0.0235      0.907      0.549       12.1   0.000494
       CG. G..     0.0217      0.845      0.547       11.3   0.000764
       CG. .G.     0.0221       0.85      0.553       11.2   0.000832
       C.T .G.     0.0335      0.564      0.673        7.9    0.00493
       CG. ..T     0.0181      0.706      0.595       7.23    0.00718
       C.T G..     0.0266      0.685      0.658       7.01    0.00809
The basic -proxy-assoc command selects 3 SNPs either side of the reference SNP. The 6 SNPs and the central reference SNP are listed in the first section. For each SNP, the minor allele frequency (MAF), rate of genotyping failure (GENO), the kilobase distance to the reference SNP (KB) and r-squared to the reference SNP (RSQ) are shown (i.e. note there is always a * character here for the reference SNP). Then the single SNP association results are given for each SNP: the odds ratio (OR), chi-squared statistic (CHISQ) and asymptotic p-value (P).

Important! These single SNP association tests are different to those given by the standard --assoc command, as they are based in a haplotypic context. For example, the test of the 3rd SNP would be formed by grouping all haplotypes with T at the 3rd position versus all haplotypes with C at the 3rd position:


(In practice, rarer haplotypes which might not be listed in the main report would also be considered). The test is the same as used by the --hap-assoc command: i.e. it is based on the posterior probabilities of haplotype phase given genotype data for each individual, possibily counting fractional haplotypes if phase is ambiguous. Importantly, the E-M algorithm will fill in missing genotype data: the effect of this property with respect to non-random missing genotype data is described below.

In this example, we see that the reference SNP is highly associated, but that no nearby SNPs show any association. Looking at the RSQ column for each SNP, this is not surprising, as none of these 6 SNPs show strong LD with the proxy. Nonetheless, it is possible to look for haplotypes formed by these 6 flanking SNPs that might have high LD with the reference SNP, and ask whether or not these show association with disease. The next section lists the common haplotypes in this region, phasing all 7 SNPs. The standard haplotype-specific association results are given next to each haplotype: in this case, no single haplotype is particularly strongly associated with disease.

The final section represents the main part of the proxy association method: it represents the results of a systematic search for SNPs or haplotypes in strong LD with the proxy SNP, and lists the association results for each, sorted by strength of association. In this particular case, we see that although no single SNP reflected the association of the reference SNP, there are subhaplotypes that are associated with disease at a similar level of magnitude to the reference SNP. The first row shows the CGT haplotype of the first 3 SNPs is in very strong LD with the reference SNP (r-squared of 0.913) and shows a similar magnitude of association:
           HAP       FREQ        RSQ         OR      CHISQ          P
       CGT ...     0.0233      0.913      0.537       12.9   0.000334
That the same signal is seen more than once (i.e. not just by a single SNP) might be taken to suggest that the association (which might still be due to chance, population stratification, etc) is at least not due to some technical artefact with the genotyping of that one SNP, as the same signal is seen elsewhere.

There are a number of parameters that change the specific behavior of the proxy association report, listed here:

Note A version of --proxy-tdt will be implemented in the next release of PLINK -- currently there is only support for basic case/control association tests (i.e. analogous to the --assoc command).

It is possible to specify how many SNPs are selected, or for specific SNPs to be selected around a particular reference SNP; it is also possible to impose different genotyping and frequency thresholds for proxy SNPs, to change the r-squared threshold for 'strong LD', to change the minor haplotype frequency considered for a proxy haplotype, to specify a kb limit to the flanking region and to change the search over subhaplotypes.

By default, 3 SNPs are selected either side, that are above 0.05 MAF and less than 0.05 genotyping failure (in otherwords, we try to look for high genotyping, common SNPs to form proxies with, as lower frequency, low genotyping SNPs are more likely to be biased). By default, the flanking SNPs must be within 250kb of the reference SNP. Haplotypes above 0.01 minor haplotype frequenc

To select a different number of
--proxy-window 6

--proxy-flanking --proxy-maxsnp --proxy-geno --proxy-maf --proxy-kb --proxy-mhf --proxy-r2

HINT To speed up the proxy report, you need only load in the relevant chromosomal region: that is, use the --snp and --window options:
plink --bfile mydata --proxy-assoc rs12345 --snp rs12345 --window 300

Proxy-based single SNP association

--proxy-list --proxy-assoc all --proxy-verbose

Providing some degree of robustness to non-random genotyping failure

Obviously, the assumption here is that most SNPs do not show strong levels of this kind of non-random genotyping failure, such that the flanking SNPs can be assumed to be valid. Most SNPs do not show bias, but the few that do might have quite severe bias; Relatively rare, can be severe
AABAB 0.4 AABBA 0.2 ABBBA 0.2 BBBBB 0.1 AAABB 0.1 In cases only, the BB genotype of rs10003 only has a genotyping rate of 0.5. The pattern of genotyping failure, which is non-random with respect to both phenotype and genotype, can tend to produce spurious association results.
     CHR  SNP   A1      F_A      F_U   A2        CHISQ            P           OR
       1 snp1    B    0.102    0.106    A      0.08585       0.7695        0.958
       1 snp2    B    0.297     0.31    A       0.3997       0.5272       0.9403
       1 snp3    A   0.1812    0.118    B        12.02    0.0005271        1.654   <---
       1 snp4    A    0.406    0.383    B        1.107       0.2927        1.101
       1 snp5    A    0.388    0.393    B      0.05252       0.8187       0.9792

     *** Proxy haplotype association report for snp3 ***

 SNP      MAF     GENO       KB      RSQ       OR    CHISQ        P
snp1    0.104        0   -0.002   0.0145     1.04   0.0859     0.77
snp2    0.303        0   -0.001   0.0544     1.06      0.4    0.527
snp3    0.141    0.213        0        *     1.15    0.993    0.319
snp4    0.394        0    0.001   0.0813    0.908     1.11    0.293
snp5     0.39        0    0.002     0.08     1.02   0.0525    0.819

         ..*..       FREQ         OR      CHISQ          P
         ABBBA      0.199      0.945      0.254      0.615
         AABBA      0.191       1.03     0.0518       0.82
         AABAB      0.394        1.1       1.11      0.293
         AAABB      0.111      0.868      0.993      0.319
         BBBBB      0.104      0.958     0.0859       0.77

Haplotype frequency estimation based on 1000 of 1000 founders
Omnibus haplotype test statistic: 1.88, df = 4, p = 0.759

           HAP       FREQ        RSQ         OR      CHISQ          P
         A. BB      0.111          1      0.868      0.993      0.319
with the matrix of r or r^2 values in it.

It is possible to add the --matrix option, which creates a matrix of LD values rather than a list.

TODO Describe this file; add ability to restrict LD scan (default behavior is to automatically attempt to calculate LD between all pairs of SNPs).

IBS sharing association tests

These tests are currently being implemented and are not ready for general use.
plink --file mydata --sharing

Feature to be implemented

TODO Display heterozygosity and genotype frequencies in the .frq file.

Known issues

Version 0.99n

ISSUE Versions prior to v0.99o will mistakenly include unaffected offspring in the haplotype-based TDT test.

Version 0.99m

ISSUE If using the --model, --model-gen permutation procedure, the asymptotic p-value in the plink.model.mperm file is incorrectly based on 1 df rather than 2 df. The asymptotic p-value in the standard plink.model is correct however. This will be fixed in v0.99n.

ISSUE If a non-existent allele tag --hap is specified in the haplotype list file, a warning should be written to the plink.mishap file, and that non-existent haplotype skipped. Currently this is not working -- it will give an incorrect haplotype frequency estimate for the missing haplotype. ISSUE The --epistasis command should work be used with haploid data; this will be fixed in a future version

ISSUE A potential issue with DOS and long command lines -- the current length seems to be 127 characters. For a workaround, use the --script option described here; alternatively, see this link; this issue will be investigated for future.

This document last modified Wednesday, 25-Jan-2017 11:52:28 EST