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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}

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/ieu-a-import/processed/ieu-a-1067/ieu-a-1067.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/ieu-a-import/processed/ieu-a-1067/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Tue Feb  4 20:42:23 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1067/ieu-a-1067.vcf.gz ...
Read summary statistics for 2399817 SNPs.
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, 1141285 SNPs remain.
After merging with regression SNP LD, 1141285 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1723 (0.1455)
Lambda GC: 1.0088
Mean Chi^2: 1.0095
Intercept: 0.9993 (0.0064)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Feb  4 20:42:52 2020
Total time elapsed: 29.48s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9207,
    "inflation_factor": 1.0089,
    "mean_EFFECT": -0.0002,
    "n": 2956,
    "n_snps": 2399817,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 20187,
    "n_est": 2865.0834,
    "ratio_se_n": 0.9845,
    "mean_diff": 0.0001,
    "ratio_diff": 1.0066,
    "sd_y_est1": 1.0187,
    "sd_y_est2": 1.003,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1141285,
    "ldsc_nsnp_merge_regression_ld": 1141285,
    "ldsc_observed_scale_h2_beta": 0.1723,
    "ldsc_observed_scale_h2_se": 0.1455,
    "ldsc_intercept_beta": 0.9993,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0088,
    "ldsc_mean_chisq": 1.0095,
    "ldsc_ratio": -0.0737
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique FALSE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 42 0 2399817 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.595097e+00 5.661961e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.30000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.877936e+07 5.567132e+07 1.1523e+04 3.263069e+07 7.015404e+07 1.142823e+08 2.49219e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.531000e-04 4.691910e-02 -2.0900e+00 -2.390000e-02 -1.000000e-04 2.370000e-02 1.97300e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.986950e-02 2.375780e-02 2.5000e-02 2.740000e-02 3.200000e-02 4.300000e-02 1.01600e+00 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.990008e-01 2.890482e-01 1.8000e-06 2.485999e-01 4.981005e-01 7.498994e-01 1.00000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.990003e-01 2.890497e-01 1.7000e-06 2.485632e-01 4.980733e-01 7.499682e-01 1.00000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 3.633266e-01 2.711912e-01 1.0060e-02 1.285000e-01 2.999000e-01 5.624000e-01 9.89940e-01 ▇▅▃▃▂
numeric AF_reference 20187 0.9915881 NA NA NA NA NA 3.650577e-01 2.532628e-01 1.9970e-04 1.523560e-01 3.051120e-01 5.485220e-01 1.00000e+00 ▇▆▅▃▂
numeric N 0 1.0000000 NA NA NA NA NA 2.956000e+03 0.000000e+00 2.9560e+03 2.956000e+03 2.956000e+03 2.956000e+03 2.95600e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 721290 rs12565286 G C 0.0030 0.1187 0.9801000 0.9798366 0.03048 0.0371406 2956
1 723819 rs11804171 T A -0.0108 0.1179 0.9267999 0.9270134 0.03048 0.1345850 2956
1 723891 rs2977670 G C 0.0080 0.1163 0.9450000 0.9451587 0.96924 0.7799520 2956
1 750235 rs12138618 G A 0.1826 0.0832 0.0281300 0.0281843 0.08166 NA 2956
1 752566 rs3094315 G A 0.0914 0.0552 0.0980393 0.0977629 0.79180 0.7182510 2956
1 754192 rs3131968 A G 0.0840 0.0584 0.1501001 0.1503330 0.81280 0.6785140 2956
1 768448 rs12562034 G A 0.1514 0.0639 0.0177701 0.0178205 0.11050 0.1918930 2956
1 775659 rs2905035 A G 0.0925 0.0588 0.1154001 0.1156889 0.81280 0.7450080 2956
1 777122 rs2980319 A T 0.0895 0.0588 0.1283001 0.1279818 0.81280 0.7472040 2956
1 779322 rs4040617 A G -0.0895 0.0588 0.1283001 0.1279818 0.18720 0.2264380 2956
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51212875 rs2238837 A C -0.0807 0.0421 0.0555802 0.0552551 0.40970 0.3724040 2956
22 51216564 rs9616970 T C -0.0352 0.0438 0.4216004 0.4215974 0.13400 0.1563500 2956
22 51217134 rs117417021 A G -0.0524 0.0421 0.2128002 0.2132584 0.48450 0.2671730 2956
22 51222100 rs114553188 G T 0.0598 0.0599 0.3181002 0.3181191 0.07936 0.0880591 2956
22 51223637 rs375798137 G A 0.0598 0.0599 0.3181002 0.3181191 0.07936 0.0788738 2956
22 51229805 rs9616985 T C -0.1019 0.0739 0.1682000 0.1679286 0.05405 0.0730831 2956
23 35921591 rs2204667 C G -0.0384 0.0341 0.2596002 0.2601233 0.15410 NA 2956
23 51666786 rs14115 A G 0.0795 0.0654 0.2246001 0.2241387 0.06200 NA 2956
23 70163799 rs1626496 A C 0.0470 0.0495 0.3426999 0.3423689 0.03939 NA 2956
23 118495837 rs12882977 G A 0.0010 0.0261 0.9702001 0.9694372 0.42180 0.2307280 2956

bcf preview

1   721290  rs12565286  G   C   .   PASS    AF=0.03048  ES:SE:LP:AF:SS:ID   0.003:0.1187:0.00872961:0.03048:2956:rs12565286
1   723819  rs11804171  T   A   .   PASS    AF=0.03048  ES:SE:LP:AF:SS:ID   -0.0108:0.1179:0.033014:0.03048:2956:rs11804171
1   723891  rs2977670   G   C   .   PASS    AF=0.96924  ES:SE:LP:AF:SS:ID   0.008:0.1163:0.0245682:0.96924:2956:rs2977670
1   750235  rs12138618  G   A   .   PASS    AF=0.08166  ES:SE:LP:AF:SS:ID   0.1826:0.0832:1.55083:0.08166:2956:rs12138618
1   752566  rs3094315   G   A   .   PASS    AF=0.7918   ES:SE:LP:AF:SS:ID   0.0914:0.0552:1.0086:0.7918:2956:rs3094315
1   754192  rs3131968   A   G   .   PASS    AF=0.8128   ES:SE:LP:AF:SS:ID   0.084:0.0584:0.823619:0.8128:2956:rs3131968
1   768448  rs12562034  G   A   .   PASS    AF=0.1105   ES:SE:LP:AF:SS:ID   0.1514:0.0639:1.75031:0.1105:2956:rs12562034
1   775659  rs2905035   A   G   .   PASS    AF=0.8128   ES:SE:LP:AF:SS:ID   0.0925:0.0588:0.937794:0.8128:2956:rs2905035
1   777122  rs2980319   A   T   .   PASS    AF=0.8128   ES:SE:LP:AF:SS:ID   0.0895:0.0588:0.891773:0.8128:2956:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.1872   ES:SE:LP:AF:SS:ID   -0.0895:0.0588:0.891773:0.1872:2956:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.8128   ES:SE:LP:AF:SS:ID   0.0895:0.0588:0.891773:0.8128:2956:rs2977612
1   785050  rs2905062   G   A   .   PASS    AF=0.8131   ES:SE:LP:AF:SS:ID   0.0895:0.0588:0.891773:0.8131:2956:rs2905062
1   798026  rs4951864   C   T   .   PASS    AF=0.8899   ES:SE:LP:AF:SS:ID   -0.1608:0.0669:1.78941:0.8899:2956:rs4951864
1   798801  rs12132517  G   A   .   PASS    AF=0.1104   ES:SE:LP:AF:SS:ID   0.1651:0.0666:1.8791:0.1104:2956:rs12132517
1   798959  rs11240777  G   A   .   PASS    AF=0.2142   ES:SE:LP:AF:SS:ID   -0.012:0.0553:0.0819697:0.2142:2956:rs11240777
1   962210  rs3128126   A   G   .   PASS    AF=0.4612   ES:SE:LP:AF:SS:ID   0.0011:0.0438:0.00917295:0.4612:2956:rs3128126
1   990380  rs3121561   C   T   .   PASS    AF=0.2895   ES:SE:LP:AF:SS:ID   0.1101:0.1085:0.508358:0.2895:2956:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.2294   ES:SE:LP:AF:SS:ID   0.0476:0.0378:0.682563:0.2294:2956:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.7401   ES:SE:LP:AF:SS:ID   0.05:0.0295:1.0491:0.7401:2956:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.2293   ES:SE:LP:AF:SS:ID   0.0444:0.0379:0.616364:0.2293:2956:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.5155   ES:SE:LP:AF:SS:ID   -0.0532:0.0853:0.27311:0.5155:2956:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5106   ES:SE:LP:AF:SS:ID   0.053:0.0389:0.762959:0.5106:2956:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.2174   ES:SE:LP:AF:SS:ID   0.0365:0.0399:0.443336:0.2174:2956:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.5106   ES:SE:LP:AF:SS:ID   0.0213:0.0272:0.363412:0.5106:2956:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.5104   ES:SE:LP:AF:SS:ID   0.0213:0.0272:0.363412:0.5104:2956:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.2168   ES:SE:LP:AF:SS:ID   0.0247:0.04:0.270349:0.2168:2956:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.7174   ES:SE:LP:AF:SS:ID   0.0206:0.0291:0.320027:0.7174:2956:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.2168   ES:SE:LP:AF:SS:ID   0.0247:0.04:0.270349:0.2168:2956:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.7424   ES:SE:LP:AF:SS:ID   0.0223:0.0292:0.352226:0.7424:2956:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.4994   ES:SE:LP:AF:SS:ID   0.02:0.0268:0.341226:0.4994:2956:rs6701114
1   1025301 rs9442400   T   C   .   PASS    AF=0.98189  ES:SE:LP:AF:SS:ID   0.2095:0.1473:0.809949:0.98189:2956:rs9442400
1   1026707 rs4074137   C   A   .   PASS    AF=0.6052   ES:SE:LP:AF:SS:ID   0.021:0.027:0.360016:0.6052:2956:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.1886   ES:SE:LP:AF:SS:ID   -0.0083:0.0362:0.0867161:0.1886:2956:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.1857   ES:SE:LP:AF:SS:ID   -0.0083:0.0362:0.0867161:0.1857:2956:rs6678318
1   1031540 rs9651273   A   G   .   PASS    AF=0.7296   ES:SE:LP:AF:SS:ID   0.0178:0.0298:0.260744:0.7296:2956:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.0529   ES:SE:LP:AF:SS:ID   -0.016:0.0434:0.147276:0.0529:2956:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.09919  ES:SE:LP:AF:SS:ID   -0.0229:0.0385:0.258454:0.09919:2956:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.09919  ES:SE:LP:AF:SS:ID   -0.0268:0.0381:0.316593:0.09919:2956:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.05322  ES:SE:LP:AF:SS:ID   -0.0241:0.043:0.240634:0.05322:2956:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.1112   ES:SE:LP:AF:SS:ID   -0.027:0.038:0.321209:0.1112:2956:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.06613  ES:SE:LP:AF:SS:ID   -0.0202:0.0427:0.19627:0.06613:2956:rs4970409
1   1060174 rs7548798   C   T   .   PASS    AF=0.3258   ES:SE:LP:AF:SS:ID   -0.0308:0.0284:0.555019:0.3258:2956:rs7548798
1   1060235 rs7540009   G   A   .   PASS    AF=0.04543  ES:SE:LP:AF:SS:ID   -0.0304:0.0797:0.152859:0.04543:2956:rs7540009
1   1060608 rs17160824  G   A   .   PASS    AF=0.06642  ES:SE:LP:AF:SS:ID   -0.0126:0.0428:0.114582:0.06642:2956:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.06642  ES:SE:LP:AF:SS:ID   -0.0093:0.043:0.0811313:0.06642:2956:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.06642  ES:SE:LP:AF:SS:ID   -0.0081:0.043:0.0699684:0.06642:2956:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.3921   ES:SE:LP:AF:SS:ID   -0.0407:0.0271:0.874844:0.3921:2956:rs11807848
1   1062015 rs9659914   C   T   .   PASS    AF=0.04457  ES:SE:LP:AF:SS:ID   -0.0472:0.0814:0.249955:0.04457:2956:rs9659914
1   1062638 rs9442373   C   A   .   PASS    AF=0.5233   ES:SE:LP:AF:SS:ID   0.0234:0.0269:0.416235:0.5233:2956:rs9442373
1   1064535 rs6682475   G   C   .   PASS    AF=0.7884   ES:SE:LP:AF:SS:ID   0.0063:0.0333:0.0709389:0.7884:2956:rs6682475