Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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}

LDSC

*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call: 
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/folkersen-pqtl-gwas-import/processed/PROT-b-81/PROT-b-81.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/folkersen-pqtl-gwas-import/processed/PROT-b-81/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Oct 28 22:10:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/folkersen-pqtl-gwas-import/processed/PROT-b-81/PROT-b-81.vcf.gz ...
Read summary statistics for 4217519 SNPs.
Dropped 1 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 625178 SNPs remain.
After merging with regression SNP LD, 625178 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1745 (0.1801)
Lambda GC: 1.003
Mean Chi^2: 1.0078
Intercept: 0.9941 (0.0109)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Oct 28 22:11:00 2019
Total time elapsed: 42.56s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.956,
    "inflation_factor": 1.0103,
    "mean_EFFECT": 0.0041,
    "n": "-Inf",
    "n_snps": 4217519,
    "n_clumped_hits": 0,
    "n_p_sig": 9,
    "n_mono": 417,
    "n_ns": 261122,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 311294,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 625178,
    "ldsc_nsnp_merge_regression_ld": 625178,
    "ldsc_observed_scale_h2_beta": 0.1745,
    "ldsc_observed_scale_h2_se": 0.1801,
    "ldsc_intercept_beta": 0.9941,
    "ldsc_intercept_se": 0.0109,
    "ldsc_lambda_gc": 1.003,
    "ldsc_mean_chisq": 1.0078,
    "ldsc_ratio": -0.7564
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
n_p_sig FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 FALSE
r2_sum2 FALSE
r2_sum3 FALSE
r2_sum4 FALSE

Definitions

General metrics

  • af_correlation: Correlation coefficient between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations for <*> column.

se_n metrics

  • n_est: Estimated sample size value, \(\widehat{n}\).
  • ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expect ratio_se_n to be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.
  • mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.
    • \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
    • \({z}_j = \frac{\beta_j}{{se}_j}\),
    • and \(\beta_j\) is the reported effect size.
  • ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff and the mean of diff2 (expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.
    • \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
    • \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
  • sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.
    • \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
    • \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
    • and \({se}_j\) is the reported standard error.
  • sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.
    • \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
    • \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),

r2 metrics

Sum of variance explained, calculated from the clumped top hits sample.

  • r2_sum<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),
    • 3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),
    • 4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).

LDSC metrics

Metrics from LD regression

  • ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.
  • ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.
  • ldsc_observed_scale_h2_{beta,se} Coefficient value and SE for total observed scale h2.
  • ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.
  • ldsc_lambda_gc: Lambda GC statistics.
  • ldsc_mean_chisq: Mean \(\chi^2\) statistics.
  • ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).

Flags

When a metric needs attention, the flag should return TRUE.

  • af_correlation: abs(af_correlation) < 0.7.
  • inflation_factor: inflation_factor > 1.2.
  • n: n (max reported sample size) < 10000.
  • is_snpid_non_unique: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_sum<*>: r2_sum<*> > 0.5

Plots

  • Manhattan plot
    • Red line: \(-log_{10}^{5 \times 10^{-8}}\)
    • Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
  • QQ plot
  • AF plot
  • P-Z plot
  • beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)

Diagnostics

Details

Summary stats

skim_type skim_variable n_missing complete_rate character.min character.max character.empty character.n_unique character.whitespace logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 4217516 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 3 0 80 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 3 0 80 0 NA NA NA NA NA NA NA NA NA NA
logical N 4217519 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 9.844030e+00 5.113267e+00 1.0000 5.000000e+00 9.000000e+00 1.300000e+01 2.200000e+01 ▇▇▇▅▃
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.057353e+07 4.563585e+07 34918.0000 3.236389e+07 6.477455e+07 1.035942e+08 1.977961e+08 ▇▇▆▃▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.058700e-03 2.794070e-01 -15.2037 -3.650000e-02 4.000000e-04 3.770000e-02 8.204900e+00 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.318065e-01 2.360986e-01 0.0233 3.390000e-02 4.740000e-02 1.090000e-01 3.319800e+00 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.987661e-01 2.885233e-01 0.0000 2.498999e-01 4.978001e-01 7.481006e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.985788e-01 2.886386e-01 0.0000 2.494989e-01 4.976503e-01 7.480081e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.803965e-01 2.812576e-01 0.0000 3.810000e-02 1.804000e-01 4.641000e-01 1.000000e+00 ▇▃▂▂▁
numeric AF_reference 311294 0.9261903 NA NA NA NA NA NA NA 2.547631e-01 2.537602e-01 0.0000 3.913740e-02 1.693290e-01 4.075480e-01 1.000000e+00 ▇▃▂▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 104917910 rs113234741 G A 0.4183 0.5733 0.4666003 0.4656131 0.0156 NA NA
2 18642530 rs111710788 G C 0.0825 0.0815 0.3117001 0.3114090 0.9708 NA NA
2 161008726 rs77875881 C T 0.0807 0.0506 0.1109001 0.1107432 0.1037 0.0095847 NA
3 60363 rs141398405 A G 0.0526 0.0716 0.4626004 0.4625607 0.0556 0.0257588 NA
3 60596 rs13067307 C A -0.0082 0.0268 0.7589008 0.7596274 0.4852 0.5591050 NA
3 60648 rs138886950 A G -0.1274 0.0961 0.1852000 0.1849383 0.0470 0.0325479 NA
3 61044 rs9755941 T C 0.0090 0.0256 0.7243993 0.7251664 0.5048 0.5976440 NA
3 61113 rs9756992 A T 0.0019 0.0246 0.9387000 0.9384360 0.4468 0.5710860 NA
3 61466 rs13081384 G C 0.0310 0.0290 0.2846997 0.2850852 0.2629 0.1725240 NA
3 61495 rs13060385 A G 0.0027 0.0273 0.9213001 0.9212168 0.4530 0.4826280 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51163039 rs715584 G T 0.0573 0.0301 0.0569600 0.0569552 0.4131 0.4736420 NA
22 51163138 rs715586 C T 0.0607 0.0361 0.0931001 0.0926774 0.1273 0.0902556 NA
22 51163910 rs192700691 C T 0.1128 0.1074 0.2933999 0.2935897 0.0304 0.0295527 NA
22 51164109 rs5770995 G C 0.0422 0.0283 0.1360000 0.1359179 0.4411 0.5109820 NA
22 51164115 rs5770996 C T 0.0426 0.0284 0.1340001 0.1336144 0.4446 0.5147760 NA
22 51164287 rs6009957 T C 0.0148 0.0274 0.5882000 0.5890964 0.3052 0.4155350 NA
22 51165664 rs8137951 G A 0.0154 0.0266 0.5627001 0.5626247 0.2954 0.4063500 NA
22 51171693 rs756638 G A 0.0084 0.0387 0.8275000 0.8281661 0.3046 0.3049120 NA
22 51175626 rs3810648 A G 0.0887 0.0604 0.1418999 0.1419568 0.0735 0.1084270 NA
22 51178090 rs2285395 G A 0.0840 0.0573 0.1424000 0.1426568 0.0481 0.0666933 NA

bcf preview

1   104917910   rs113234741 G   A   .   PASS    AF=0.0156   ES:SE:LP:AF:ID  0.4183:0.5733:0.331055:0.0156:rs113234741
2   18642530    rs111710788 G   C   .   PASS    AF=0.9708   ES:SE:LP:AF:ID  0.0825:0.0815:0.506263:0.9708:rs111710788
2   161008726   rs77875881  C   T   .   PASS    AF=0.1037   ES:SE:LP:AF:ID  0.0807:0.0506:0.955068:0.1037:rs77875881
3   60363   rs141398405 A   G   .   PASS    AF=0.0556   ES:SE:LP:AF:ID  0.0526:0.0716:0.334794:0.0556:rs141398405
3   60596   rs13067307  C   A   .   PASS    AF=0.4852   ES:SE:LP:AF:ID  -0.0082:0.0268:0.119815:0.4852:rs13067307
3   60648   rs138886950 A   G   .   PASS    AF=0.047    ES:SE:LP:AF:ID  -0.1274:0.0961:0.732359:0.047:rs138886950
3   61044   rs9755941   T   C   .   PASS    AF=0.5048   ES:SE:LP:AF:ID  0.009:0.0256:0.140022:0.5048:rs9755941
3   61113   rs9756992   A   T   .   PASS    AF=0.4468   ES:SE:LP:AF:ID  0.0019:0.0246:0.0274732:0.4468:rs9756992
3   61466   rs13081384  G   C   .   PASS    AF=0.2629   ES:SE:LP:AF:ID  0.031:0.029:0.545613:0.2629:rs13081384
3   61495   rs13060385  A   G   .   PASS    AF=0.453    ES:SE:LP:AF:ID  0.0027:0.0273:0.0355989:0.453:rs13060385
3   61662   rs73009205  T   C   .   PASS    AF=0.0581   ES:SE:LP:AF:ID  0.0505:0.0682:0.337714:0.0581:rs73009205
3   61762   rs62240674  T   A   .   PASS    AF=0.3163   ES:SE:LP:AF:ID  0.0154:0.026:0.257118:0.3163:rs62240674
3   62226   rs9799162   C   T   .   PASS    AF=0.3198   ES:SE:LP:AF:ID  0.0172:0.0261:0.29243:0.3198:rs9799162
3   62309   rs9681823   T   G   .   PASS    AF=0.2467   ES:SE:LP:AF:ID  0.0171:0.0339:0.212115:0.2467:rs9681823
3   62337   rs180933565 G   A   .   PASS    AF=0.002    ES:SE:LP:AF:ID  -0.6497:0.4567:0.809949:0.002:rs180933565
3   62425   rs73009208  A   C   .   PASS    AF=0.0582   ES:SE:LP:AF:ID  0.0501:0.0679:0.336582:0.0582:rs73009208
3   62437   rs9682412   A   T   .   PASS    AF=0.7703   ES:SE:LP:AF:ID  0.0292:0.0317:0.446845:0.7703:rs9682412
3   62614   rs9799274   G   C   .   PASS    AF=0.316    ES:SE:LP:AF:ID  0.0153:0.0259:0.256725:0.316:rs9799274
3   62746   rs13073823  C   G   .   PASS    AF=0.1151   ES:SE:LP:AF:ID  -0.0391:0.0405:0.474566:0.1151:rs13073823
3   62759   rs34815673  A   C   .   PASS    AF=0.1151   ES:SE:LP:AF:ID  -0.0391:0.0405:0.474696:0.1151:rs34815673
3   62886   rs58497705  A   T   .   PASS    AF=0.3197   ES:SE:LP:AF:ID  0.0169:0.0261:0.287687:0.3197:rs58497705
3   62971   rs9682645   C   A   .   PASS    AF=0.3262   ES:SE:LP:AF:ID  0.0194:0.0276:0.315873:0.3262:rs9682645
3   62981   rs59670147  C   T   .   PASS    AF=0.3197   ES:SE:LP:AF:ID  0.0168:0.0261:0.284916:0.3197:rs59670147
3   63411   rs13072188  A   C   .   PASS    AF=0.4445   ES:SE:LP:AF:ID  0.0017:0.0241:0.0246601:0.4445:rs13072188
3   63989   3_63989_C_CAT   CAT C   .   PASS    AF=0.641    ES:SE:LP:AF:ID  -0.0123:0.031:0.159518:0.641:3_63989_C_CAT
3   64165   rs9311287   C   A   .   PASS    AF=0.1836   ES:SE:LP:AF:ID  -0.0433:0.0365:0.62764:0.1836:rs9311287
3   64189   rs113405791 C   T   .   PASS    AF=0.0583   ES:SE:LP:AF:ID  0.0499:0.0673:0.338471:0.0583:rs113405791
3   64221   rs9311316   C   T   .   PASS    AF=0.7677   ES:SE:LP:AF:ID  0.0282:0.0317:0.427709:0.7677:rs9311316
3   64492   rs34166985  T   A   .   PASS    AF=0.2673   ES:SE:LP:AF:ID  0.0295:0.0281:0.533281:0.2673:rs34166985
3   64940   rs142582846 G   A   .   PASS    AF=0.0453   ES:SE:LP:AF:ID  -0.1324:0.0982:0.750068:0.0453:rs142582846
3   65592   rs150394040 T   C   .   PASS    AF=0.0442   ES:SE:LP:AF:ID  -0.1345:0.098:0.769551:0.0442:rs150394040
3   65982   rs73009220  G   A   .   PASS    AF=0.2977   ES:SE:LP:AF:ID  0.0391:0.0293:0.740884:0.2977:rs73009220
3   66083   rs9713920   T   C   .   PASS    AF=0.1463   ES:SE:LP:AF:ID  -0.0635:0.0398:0.95546:0.1463:rs9713920
3   66164   rs35007339  C   G   .   PASS    AF=0.6275   ES:SE:LP:AF:ID  0.0536:0.0281:1.24911:0.6275:rs35007339
3   66342   rs28716985  T   G   .   PASS    AF=0.3315   ES:SE:LP:AF:ID  0.0164:0.0267:0.268653:0.3315:rs28716985
3   66519   3_66519_G_GA    GA  G   .   PASS    AF=0.9529   ES:SE:LP:AF:ID  0.1246:0.0935:0.738499:0.9529:3_66519_G_GA
3   66866   rs9683305   C   T   .   PASS    AF=0.3009   ES:SE:LP:AF:ID  0.0361:0.029:0.671824:0.3009:rs9683305
3   66894   rs9681213   G   A   .   PASS    AF=0.3018   ES:SE:LP:AF:ID  0.0361:0.0289:0.674484:0.3018:rs9681213
3   67116   rs9681345   G   A   .   PASS    AF=0.3018   ES:SE:LP:AF:ID  0.0361:0.0289:0.674484:0.3018:rs9681345
3   67176   rs150705890 C   T   .   PASS    AF=0.0096   ES:SE:LP:AF:ID  0.0046:0.1337:0.0120657:0.0096:rs150705890
3   67279   rs67010098  G   A   .   PASS    AF=0.2406   ES:SE:LP:AF:ID  0.0485:0.0297:0.9897:0.2406:rs67010098
3   67801   rs9681389   G   C   .   PASS    AF=0.4932   ES:SE:LP:AF:ID  -0.0088:0.0266:0.130358:0.4932:rs9681389
3   67818   rs62240679  T   G   .   PASS    AF=0.3244   ES:SE:LP:AF:ID  0.0156:0.0265:0.254613:0.3244:rs62240679
3   68079   rs12631621  G   C   .   PASS    AF=0.1186   ES:SE:LP:AF:ID  -0.0347:0.04:0.413863:0.1186:rs12631621
3   68204   rs67723366  G   C   .   PASS    AF=0.1225   ES:SE:LP:AF:ID  -0.03:0.0389:0.356942:0.1225:rs67723366
3   68426   rs71306185  C   T   .   PASS    AF=0.1071   ES:SE:LP:AF:ID  -0.043:0.0428:0.501689:0.1071:rs71306185
3   68528   rs113565524 C   G   .   PASS    AF=0.0231   ES:SE:LP:AF:ID  -0.033:0.1075:0.119701:0.0231:rs113565524
3   69244   rs13089679  T   C   .   PASS    AF=0.2871   ES:SE:LP:AF:ID  0.0279:0.0263:0.538802:0.2871:rs13089679
3   69456   rs112317660 G   T   .   PASS    AF=0.0237   ES:SE:LP:AF:ID  -0.0302:0.1074:0.108686:0.0237:rs112317660
3   70895   rs9682794   T   C   .   PASS    AF=0.3279   ES:SE:LP:AF:ID  0.0177:0.0268:0.293709:0.3279:rs9682794