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-1082/ieu-a-1082.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-1082/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 20:59:38 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1082/ieu-a-1082.vcf.gz ...
Read summary statistics for 571078 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, 458290 SNPs remain.
After merging with regression SNP LD, 458290 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 4.3408 (0.5693)
Lambda GC: 1.201
Mean Chi^2: 1.3166
Intercept: 1.2273 (0.009)
Ratio: 0.7179 (0.0284)
Analysis finished at Tue Feb  4 20:59:52 2020
Total time elapsed: 13.45s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9029,
    "inflation_factor": 1.2053,
    "mean_EFFECT": 0.0002,
    "n": 1187,
    "n_snps": 571078,
    "n_clumped_hits": 347,
    "n_p_sig": 795,
    "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": 3569,
    "n_est": 1179.0631,
    "ratio_se_n": 0.9967,
    "mean_diff": -0.0004,
    "ratio_diff": 1.459,
    "sd_y_est1": 2.0338,
    "sd_y_est2": 2.0269,
    "r2_sum1": 200.757,
    "r2_sum2": 48.5371,
    "r2_sum3": 48.8638,
    "r2_sum4": 29.028,
    "ldsc_nsnp_merge_refpanel_ld": 458290,
    "ldsc_nsnp_merge_regression_ld": 458290,
    "ldsc_observed_scale_h2_beta": 4.3408,
    "ldsc_observed_scale_h2_se": 0.5693,
    "ldsc_intercept_beta": 1.2273,
    "ldsc_intercept_se": 0.009,
    "ldsc_lambda_gc": 1.201,
    "ldsc_mean_chisq": 1.3166,
    "ldsc_ratio": 0.7179
}

Flags

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

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 4 33 0 571078 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 9.240865e+00 6.157312e+00 1.0000000 4.000000e+00 8.000000e+00 1.400000e+01 2.400000e+01 ▇▆▅▃▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.716883e+07 5.667229e+07 8547.0000000 3.013598e+07 6.762251e+07 1.140089e+08 2.491747e+08 ▇▆▃▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.234000e-04 1.284808e-01 -4.6511100 -7.510750e-02 0.000000e+00 7.601750e-02 5.390440e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.061470e-01 2.619420e-02 0.0832000 8.622000e-02 9.584000e-02 1.177000e-01 1.003000e+00 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.697693e-01 2.966296e-01 0.0000000 2.061000e-01 4.590003e-01 7.272002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.698686e-01 2.965496e-01 0.0000000 2.063543e-01 4.589897e-01 7.270172e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 3.836163e-01 2.448132e-01 0.0500000 1.720000e-01 3.332000e-01 5.656000e-01 9.499600e-01 ▇▆▅▃▂
numeric AF_reference 3569 0.9937504 NA NA NA NA NA 3.839601e-01 2.324002e-01 0.0001997 1.896960e-01 3.370610e-01 5.549120e-01 9.899340e-01 ▇▇▅▃▂
numeric N 0 1.0000000 NA NA NA NA NA 1.187000e+03 0.000000e+00 1187.0000000 1.187000e+03 1.187000e+03 1.187000e+03 1.187000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 752566 rs3094315 G A 0.0690286 0.10620 0.5157996 0.5157007 0.81200 0.718251 1187
1 752721 rs3131972 A G 0.0627268 0.10580 0.5533998 0.5532609 0.81040 0.653355 1187
1 768448 rs12562034 G A 0.1578580 0.12870 0.2198002 0.2199888 0.12290 0.191893 1187
1 798959 rs11240777 G A -0.0196926 0.09714 0.8395000 0.8393508 0.24140 0.409944 1187
1 838555 rs4970383 C A -0.1118260 0.09675 0.2477998 0.2477530 0.24660 0.336262 1187
1 846808 rs4475691 C T -0.1192340 0.10010 0.2334001 0.2335952 0.21950 0.254792 1187
1 854250 rs7537756 A G -0.1578240 0.09930 0.1117000 0.1119779 0.22390 0.215655 1187
1 873558 rs1110052 G T -0.3293040 0.08771 0.0001685 0.0001737 0.61940 0.494609 1187
1 882033 rs2272756 G A -0.1368510 0.09708 0.1584999 0.1586364 0.23950 0.136781 1187
1 888659 rs3748597 T C -0.3393250 0.16150 0.0347600 0.0356336 0.92285 0.922724 1187
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
24 23452965 rs9786576 C T 0.767224 0.2554 0.0024700 0.0026645 0.6413 0.8264 1187
24 23550924 rs2033003 C A 0.646454 0.2510 0.0096590 0.0100091 0.5784 0.5061 1187
24 23984056 rs1276034 A G 0.769381 0.2544 0.0023130 0.0024921 0.6341 0.8248 1187
24 23992762 rs1276033 A C 0.838404 0.2575 0.0010200 0.0011302 0.6410 NA 1187
24 24359931 rs9786095 C T 0.449801 0.3790 0.2325000 0.2353026 0.1273 NA 1187
24 24437979 rs9786856 C T 0.449801 0.3790 0.2325000 0.2353026 0.1273 0.2612 1187
24 24444622 rs7893048 T C 0.764643 0.2562 0.0026350 0.0028399 0.6374 0.8273 1187
24 25029969 rs158435 T G 0.877070 0.2590 0.0006302 0.0007082 0.6241 NA 1187
24 28650343 rs9786795 G C 0.492254 0.3766 0.1879001 0.1911786 0.1304 0.3114 1187
24 28699018 rs2049642 G A 0.575489 0.2867 0.0434000 0.0447192 0.2609 0.3771 1187

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.812    ES:SE:LP:AF:SS:ID   0.0690286:0.1062:0.287519:0.812:1187:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.8104   ES:SE:LP:AF:SS:ID   0.0627268:0.1058:0.256961:0.8104:1187:rs3131972
1   768448  rs12562034  G   A   .   PASS    AF=0.1229   ES:SE:LP:AF:SS:ID   0.157858:0.1287:0.657972:0.1229:1187:rs12562034
1   798959  rs11240777  G   A   .   PASS    AF=0.2414   ES:SE:LP:AF:SS:ID   -0.0196926:0.09714:0.0759793:0.2414:1187:rs11240777
1   838555  rs4970383   C   A   .   PASS    AF=0.2466   ES:SE:LP:AF:SS:ID   -0.111826:0.09675:0.605899:0.2466:1187:rs4970383
1   846808  rs4475691   C   T   .   PASS    AF=0.2195   ES:SE:LP:AF:SS:ID   -0.119234:0.1001:0.631899:0.2195:1187:rs4475691
1   854250  rs7537756   A   G   .   PASS    AF=0.2239   ES:SE:LP:AF:SS:ID   -0.157824:0.0993:0.951947:0.2239:1187:rs7537756
1   873558  rs1110052   G   T   .   PASS    AF=0.6194   ES:SE:LP:AF:SS:ID   -0.329304:0.08771:3.7734:0.6194:1187:rs1110052
1   882033  rs2272756   G   A   .   PASS    AF=0.2395   ES:SE:LP:AF:SS:ID   -0.136851:0.09708:0.799971:0.2395:1187:rs2272756
1   888659  rs3748597   T   C   .   PASS    AF=0.92285  ES:SE:LP:AF:SS:ID   -0.339325:0.1615:1.45892:0.92285:1187:rs3748597
1   891945  rs13303106  A   G   .   PASS    AF=0.5893   ES:SE:LP:AF:SS:ID   -0.0305292:0.0846:0.142547:0.5893:1187:rs13303106
1   894573  rs13303010  G   A   .   PASS    AF=0.868    ES:SE:LP:AF:SS:ID   -0.360468:0.127:2.35694:0.868:1187:rs13303010
1   910935  rs2340592   G   A   .   PASS    AF=0.1812   ES:SE:LP:AF:SS:ID   -0.0462534:0.1093:0.172437:0.1812:1187:rs2340592
1   918384  rs13303118  G   T   .   PASS    AF=0.5733   ES:SE:LP:AF:SS:ID   -0.07139:0.0842:0.405055:0.5733:1187:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.5813   ES:SE:LP:AF:SS:ID   -0.0657877:0.08441:0.358129:0.5813:1187:rs2341354
1   924898  rs6665000   C   A   .   PASS    AF=0.92285  ES:SE:LP:AF:SS:ID   0.0560414:0.1554:0.143694:0.92285:1187:rs6665000
1   927309  rs2341362   T   C   .   PASS    AF=0.92291  ES:SE:LP:AF:SS:ID   0.0576291:0.1554:0.148253:0.92291:1187:rs2341362
1   928836  rs9777703   C   T   .   PASS    AF=0.92249  ES:SE:LP:AF:SS:ID   0.0712812:0.1549:0.190238:0.92249:1187:rs9777703
1   932457  rs1891910   G   A   .   PASS    AF=0.1775   ES:SE:LP:AF:SS:ID   0.0843411:0.1095:0.355266:0.1775:1187:rs1891910
1   944564  rs3128117   T   C   .   PASS    AF=0.3465   ES:SE:LP:AF:SS:ID   0.0285875:0.08754:0.129889:0.3465:1187:rs3128117
1   947034  rs2465126   G   A   .   PASS    AF=0.90733  ES:SE:LP:AF:SS:ID   0.0999308:0.1427:0.315693:0.90733:1187:rs2465126
1   948692  rs2341365   G   A   .   PASS    AF=0.90944  ES:SE:LP:AF:SS:ID   0.0831642:0.1443:0.248644:0.90944:1187:rs2341365
1   948921  rs15842 T   C   .   PASS    AF=0.91319  ES:SE:LP:AF:SS:ID   0.146414:0.1472:0.495529:0.91319:1187:rs15842
1   959842  rs2710888   C   T   .   PASS    AF=0.3416   ES:SE:LP:AF:SS:ID   -0.0734313:0.08802:0.393404:0.3416:1187:rs2710888
1   962210  rs3128126   A   G   .   PASS    AF=0.3644   ES:SE:LP:AF:SS:ID   -0.151637:0.08647:1.10007:0.3644:1187:rs3128126
1   977780  rs2710875   C   T   .   PASS    AF=0.8842   ES:SE:LP:AF:SS:ID   -0.10436:0.131:0.372122:0.8842:1187:rs2710875
1   990417  rs2465136   T   C   .   PASS    AF=0.3163   ES:SE:LP:AF:SS:ID   -0.0842516:0.08926:0.462055:0.3163:1187:rs2465136
1   994391  rs2488991   G   T   .   PASS    AF=0.8568   ES:SE:LP:AF:SS:ID   -0.176471:0.1203:0.8471:0.8568:1187:rs2488991
1   998395  rs7526076   A   G   .   PASS    AF=0.7578   ES:SE:LP:AF:SS:ID   -0.00697561:0.09713:0.0261336:0.7578:1187:rs7526076
1   1005806 rs3934834   C   T   .   PASS    AF=0.1854   ES:SE:LP:AF:SS:ID   -0.240035:0.1063:1.62397:0.1854:1187:rs3934834
1   1017197 rs3766192   C   T   .   PASS    AF=0.5202   ES:SE:LP:AF:SS:ID   0.0979436:0.0833:0.620332:0.5202:1187:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.1847   ES:SE:LP:AF:SS:ID   -0.237369:0.1064:1.59363:0.1847:1187:rs3766191
1   1018704 rs9442372   A   G   .   PASS    AF=0.5299   ES:SE:LP:AF:SS:ID   0.0956302:0.08336:0.599462:0.5299:1187:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.1955   ES:SE:LP:AF:SS:ID   -0.171738:0.1042:1.00406:0.1955:1187:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.7281   ES:SE:LP:AF:SS:ID   -0.0506931:0.09374:0.22856:0.7281:1187:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.1955   ES:SE:LP:AF:SS:ID   -0.177215:0.1047:1.04436:0.1955:1187:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.72 ES:SE:LP:AF:SS:ID   -0.0372958:0.09287:0.161277:0.72:1187:rs9442398
1   1025301 rs9442400   T   C   .   PASS    AF=0.91912  ES:SE:LP:AF:SS:ID   -0.24686:0.1561:0.947306:0.91912:1187:rs9442400
1   1030565 rs6687776   C   T   .   PASS    AF=0.1912   ES:SE:LP:AF:SS:ID   -0.176737:0.1051:1.03433:0.1912:1187:rs6687776
1   1036959 rs11579015  T   C   .   PASS    AF=0.1516   ES:SE:LP:AF:SS:ID   -0.282761:0.1148:1.86519:0.1516:1187:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.1771   ES:SE:LP:AF:SS:ID   -0.129881:0.1084:0.637141:0.1771:1187:rs6671356
1   1060174 rs7548798   C   T   .   PASS    AF=0.2728   ES:SE:LP:AF:SS:ID   0.0934903:0.09388:0.494036:0.2728:1187:rs7548798
1   1061262 rs12757754  A   G   .   PASS    AF=0.155    ES:SE:LP:AF:SS:ID   -0.260197:0.1139:1.65659:0.155:1187:rs12757754
1   1062638 rs9442373   C   A   .   PASS    AF=0.5527   ES:SE:LP:AF:SS:ID   -0.0188218:0.08368:0.0842309:0.5527:1187:rs9442373
1   1064979 rs2298217   C   T   .   PASS    AF=0.1647   ES:SE:LP:AF:SS:ID   -0.190676:0.1113:1.06344:0.1647:1187:rs2298217
1   1066403 rs10907182  T   C   .   PASS    AF=0.6004   ES:SE:LP:AF:SS:ID   -0.0971267:0.0858:0.586365:0.6004:1187:rs10907182
1   1087683 rs9442380   T   C   .   PASS    AF=0.91955  ES:SE:LP:AF:SS:ID   0.162872:0.1516:0.549135:0.91955:1187:rs9442380
1   1097335 rs9442385   T   G   .   PASS    AF=0.91997  ES:SE:LP:AF:SS:ID   0.103806:0.1524:0.305044:0.91997:1187:rs9442385
1   1099342 rs9660710   A   C   .   PASS    AF=0.92628  ES:SE:LP:AF:SS:ID   0.168892:0.1578:0.546376:0.92628:1187:rs9660710
1   1100217 rs1891905   C   T   .   PASS    AF=0.93708  ES:SE:LP:AF:SS:ID   0.302863:0.1694:1.13674:0.93708:1187:rs1891905