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-1081/ieu-a-1081.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-1081/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  5 11:33:15 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1081/ieu-a-1081.vcf.gz ...
Read summary statistics for 277902 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, 273456 SNPs remain.
After merging with regression SNP LD, 273456 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0052 (0.0904)
Lambda GC: 1.0069
Mean Chi^2: 1.0065
Intercept: 1.0059 (0.0081)
Ratio: 0.9132 (1.2547)
Analysis finished at Wed Feb  5 11:33:26 2020
Total time elapsed: 10.69s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.901,
    "inflation_factor": 1.0114,
    "mean_EFFECT": -0.0019,
    "n": 5983,
    "n_snps": 277902,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "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": 1523,
    "n_est": 5932.8311,
    "ratio_se_n": 0.9958,
    "mean_diff": 0.0017,
    "ratio_diff": 7.3296,
    "sd_y_est1": 4.374,
    "sd_y_est2": 4.3557,
    "r2_sum1": 0.1165,
    "r2_sum2": 0.0061,
    "r2_sum3": 0.0061,
    "r2_sum4": 0.0061,
    "ldsc_nsnp_merge_refpanel_ld": 273456,
    "ldsc_nsnp_merge_regression_ld": 273456,
    "ldsc_observed_scale_h2_beta": 0.0052,
    "ldsc_observed_scale_h2_se": 0.0904,
    "ldsc_intercept_beta": 1.0059,
    "ldsc_intercept_se": 0.0081,
    "ldsc_lambda_gc": 1.0069,
    "ldsc_mean_chisq": 1.0065,
    "ldsc_ratio": 0.9077
}
 

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 TRUE
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 30 0 277902 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 8.870951e+00 5.858931e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▃▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.826565e+07 5.661605e+07 2.75640e+04 3.139125e+07 6.887509e+07 1.148308e+08 2.492107e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.934200e-03 1.061744e-01 -7.88522e-01 -6.762470e-02 -9.579000e-04 6.473530e-02 7.204390e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.017040e-01 2.582270e-02 6.73018e-02 8.272310e-02 9.168540e-02 1.129408e-01 3.751430e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.978997e-01 2.895269e-01 0.00000e+00 2.466538e-01 4.975589e-01 7.486654e-01 9.999935e-01 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.978997e-01 2.895269e-01 0.00000e+00 2.466541e-01 4.975589e-01 7.486660e-01 9.999935e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 3.982212e-01 2.505565e-01 3.16550e-02 1.792160e-01 3.501595e-01 5.925247e-01 9.669060e-01 ▇▆▅▃▂
numeric AF_reference 1523 0.9945197 NA NA NA NA NA 4.002327e-01 2.381874e-01 3.39460e-03 2.002800e-01 3.576280e-01 5.814700e-01 9.892170e-01 ▆▇▆▅▂
numeric N 0 1.0000000 NA NA NA NA NA 5.983000e+03 0.000000e+00 5.98300e+03 5.983000e+03 5.983000e+03 5.983000e+03 5.983000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 1005806 rs3934834 C T -0.1563460 0.1250920 0.2113552 0.2113550 0.136072 0.223442 5983
1 1021415 rs3737728 A G -0.0458677 0.0869825 0.5979708 0.5979707 0.749223 0.812700 5983
1 1030565 rs6687776 C T 0.0973262 0.1103870 0.3779480 0.3779489 0.143079 0.306709 5983
1 1031540 rs9651273 A G -0.0062857 0.0857427 0.9415600 0.9415603 0.743051 0.881989 5983
1 1048955 rs4970405 A G 0.0586434 0.1230670 0.6337077 0.6337068 0.111120 0.110623 5983
1 1049950 rs12726255 A G 0.0877123 0.1105720 0.4276259 0.4276266 0.144108 0.289736 5983
1 1064979 rs2298217 C T 0.1021980 0.1016210 0.3145734 0.3145705 0.158750 0.164736 5983
1 1094738 rs4970362 A G 0.0080655 0.0847725 0.9242009 0.9242013 0.671114 0.604034 5983
1 1099342 rs9660710 A C -0.0752941 0.1493690 0.6142045 0.6142043 0.939391 0.829872 5983
1 1106473 rs4970420 G A 0.0361969 0.0983813 0.7129285 0.7129295 0.194042 0.550319 5983
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51109992 rs9628185 T C 0.0422032 0.0793098 0.5946357 0.5946353 0.5116210 0.4053510 5983
22 51121521 rs7284093 C T 0.0511623 0.1050890 0.6263657 0.6263665 0.1716300 0.0485224 5983
22 51123505 rs9616816 G A 0.0823368 0.0928926 0.3754205 0.3754206 0.2121580 0.3783950 5983
22 51147015 rs2040487 A G -0.0143710 0.0791250 0.8558773 0.8558778 0.4326850 0.4556710 5983
22 51163138 rs715586 C T 0.0796789 0.1080330 0.4607942 0.4607927 0.1560880 0.0902556 5983
22 51165664 rs8137951 G A 0.0360516 0.0877084 0.6810437 0.6810437 0.2895070 0.4063500 5983
22 51171693 rs756638 G A 0.0984933 0.0840269 0.2411315 0.2411313 0.2920750 0.3049120 5983
22 51175626 rs3810648 A G 0.3172360 0.1442060 0.0278157 0.0278154 0.0747168 0.1084270 5983
22 51178090 rs2285395 G A 0.2975080 0.1527970 0.0515252 0.0515251 0.0704060 0.0666933 5983
23 51666786 rs14115 A G 0.1183350 0.1713650 0.4898521 0.4898524 0.0496214 NA 5983

bcf preview

1   1005806 rs3934834   C   T   .   PASS    AF=0.136072 ES:SE:LP:AF:SS:ID   -0.156346:0.125092:0.674987:0.136072:5983:rs3934834
1   1021415 rs3737728   A   G   .   PASS    AF=0.749223 ES:SE:LP:AF:SS:ID   -0.0458677:0.0869825:0.22332:0.749223:5983:rs3737728
1   1030565 rs6687776   C   T   .   PASS    AF=0.143079 ES:SE:LP:AF:SS:ID   0.0973262:0.110387:0.422568:0.143079:5983:rs6687776
1   1031540 rs9651273   A   G   .   PASS    AF=0.743051 ES:SE:LP:AF:SS:ID   -0.0062857:0.0857427:0.026152:0.743051:5983:rs9651273
1   1048955 rs4970405   A   G   .   PASS    AF=0.11112  ES:SE:LP:AF:SS:ID   0.0586434:0.123067:0.198111:0.11112:5983:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.144108 ES:SE:LP:AF:SS:ID   0.0877123:0.110572:0.368936:0.144108:5983:rs12726255
1   1064979 rs2298217   C   T   .   PASS    AF=0.15875  ES:SE:LP:AF:SS:ID   0.102198:0.101621:0.502278:0.15875:5983:rs2298217
1   1094738 rs4970362   A   G   .   PASS    AF=0.671114 ES:SE:LP:AF:SS:ID   0.0080655:0.0847725:0.0342336:0.671114:5983:rs4970362
1   1099342 rs9660710   A   C   .   PASS    AF=0.939391 ES:SE:LP:AF:SS:ID   -0.0752941:0.149369:0.211687:0.939391:5983:rs9660710
1   1106473 rs4970420   G   A   .   PASS    AF=0.194042 ES:SE:LP:AF:SS:ID   0.0361969:0.0983813:0.146954:0.194042:5983:rs4970420
1   1119858 rs1320565   C   T   .   PASS    AF=0.08378  ES:SE:LP:AF:SS:ID   -0.136288:0.159881:0.404534:0.08378:5983:rs1320565
1   1121794 rs11260549  G   A   .   PASS    AF=0.144525 ES:SE:LP:AF:SS:ID   -0.17665:0.127904:0.776649:0.144525:5983:rs11260549
1   1135242 rs9729550   A   C   .   PASS    AF=0.291841 ES:SE:LP:AF:SS:ID   -0.126775:0.0925426:0.767726:0.291841:5983:rs9729550
1   1152631 rs11721 C   A   .   PASS    AF=0.078548 ES:SE:LP:AF:SS:ID   0.226647:0.132965:1.05415:0.078548:5983:rs11721
1   1156131 rs2887286   T   C   .   PASS    AF=0.176749 ES:SE:LP:AF:SS:ID   -0.0171838:0.102955:0.0617586:0.176749:5983:rs2887286
1   1158277 rs3813199   G   A   .   PASS    AF=0.095036 ES:SE:LP:AF:SS:ID   0.194995:0.126008:0.914542:0.095036:5983:rs3813199
1   1162435 rs3766186   C   A   .   PASS    AF=0.091374 ES:SE:LP:AF:SS:ID   0.187029:0.128452:0.837474:0.091374:5983:rs3766186
1   1163804 rs7515488   C   T   .   PASS    AF=0.146067 ES:SE:LP:AF:SS:ID   0.0680357:0.109693:0.271563:0.146067:5983:rs7515488
1   1172907 rs715643    C   T   .   PASS    AF=0.053548 ES:SE:LP:AF:SS:ID   0.0611667:0.161695:0.151676:0.053548:5983:rs715643
1   1176597 rs6675798   T   C   .   PASS    AF=0.0904553    ES:SE:LP:AF:SS:ID   0.162144:0.131714:0.660923:0.0904553:5983:rs6675798
1   1211292 rs6685064   C   T   .   PASS    AF=0.074717 ES:SE:LP:AF:SS:ID   -0.0966783:0.168653:0.246813:0.074717:5983:rs6685064
1   1314015 rs2649588   C   T   .   PASS    AF=0.941089 ES:SE:LP:AF:SS:ID   0.103242:0.173463:0.258278:0.941089:5983:rs2649588
1   1425700 rs819980    T   C   .   PASS    AF=0.0839415    ES:SE:LP:AF:SS:ID   -0.0864362:0.166121:0.219798:0.0839415:5983:rs819980
1   1478180 rs3766178   T   C   .   PASS    AF=0.25121  ES:SE:LP:AF:SS:ID   0.119178:0.0863828:0.775479:0.25121:5983:rs3766178
1   1486834 rs3128342   C   A   .   PASS    AF=0.408215 ES:SE:LP:AF:SS:ID   0.0545345:0.0806727:0.301863:0.408215:5983:rs3128342
1   1493727 rs880051    G   A   .   PASS    AF=0.211571 ES:SE:LP:AF:SS:ID   0.0331818:0.0932597:0.141468:0.211571:5983:rs880051
1   1497824 rs2296716   C   T   .   PASS    AF=0.102089 ES:SE:LP:AF:SS:ID   0.0155289:0.122898:0.046023:0.102089:5983:rs2296716
1   1505255 rs6603793   C   T   .   PASS    AF=0.282715 ES:SE:LP:AF:SS:ID   0.105458:0.0847855:0.670471:0.282715:5983:rs6603793
1   1706160 rs7531583   A   G   .   PASS    AF=0.792666 ES:SE:LP:AF:SS:ID   0.0070347:0.0971174:0.0258314:0.792666:5983:rs7531583
1   1781220 rs6681938   T   C   .   PASS    AF=0.285946 ES:SE:LP:AF:SS:ID   0.0125595:0.0864258:0.053323:0.285946:5983:rs6681938
1   1801034 rs4648592   G   A   .   PASS    AF=0.28907  ES:SE:LP:AF:SS:ID   0.12605:0.0908184:0.782104:0.28907:5983:rs4648592
1   1810090 rs7525092   C   T   .   PASS    AF=0.28907  ES:SE:LP:AF:SS:ID   0.121491:0.0908452:0.742054:0.28907:5983:rs7525092
1   1844046 rs2474460   C   T   .   PASS    AF=0.495148 ES:SE:LP:AF:SS:ID   -0.0999255:0.0820069:0.65163:0.495148:5983:rs2474460
1   1888193 rs3820011   C   A   .   PASS    AF=0.28704  ES:SE:LP:AF:SS:ID   0.0754262:0.0910994:0.389663:0.28704:5983:rs3820011
1   1892325 rs2803291   T   C   .   PASS    AF=0.82761  ES:SE:LP:AF:SS:ID   0.0256214:0.101127:0.0969145:0.82761:5983:rs2803291
1   2026361 rs12755035  G   A   .   PASS    AF=0.134321 ES:SE:LP:AF:SS:ID   0.147651:0.121814:0.646907:0.134321:5983:rs12755035
1   2026749 rs884080    A   G   .   PASS    AF=0.427156 ES:SE:LP:AF:SS:ID   -0.0044289:0.0792607:0.0197969:0.427156:5983:rs884080
1   2033256 rs908742    G   A   .   PASS    AF=0.29379  ES:SE:LP:AF:SS:ID   -0.104933:0.0859801:0.653061:0.29379:5983:rs908742
1   2058023 rs3128291   A   G   .   PASS    AF=0.886321 ES:SE:LP:AF:SS:ID   -0.26974:0.113645:1.75401:0.886321:5983:rs3128291
1   2096638 rs3052  C   T   .   PASS    AF=0.108078 ES:SE:LP:AF:SS:ID   0.200462:0.121497:1.00456:0.108078:5983:rs3052
1   2113565 rs262688    T   G   .   PASS    AF=0.248291 ES:SE:LP:AF:SS:ID   -0.0301399:0.0914075:0.129828:0.248291:5983:rs262688
1   2119833 rs2460002   A   G   .   PASS    AF=0.651429 ES:SE:LP:AF:SS:ID   0.0150125:0.0841968:0.066267:0.651429:5983:rs2460002
1   2140261 rs6665593   G   A   .   PASS    AF=0.130448 ES:SE:LP:AF:SS:ID   0.0136555:0.116732:0.0424529:0.130448:5983:rs6665593
1   2156362 rs2460000   A   G   .   PASS    AF=0.64712  ES:SE:LP:AF:SS:ID   0.0359465:0.0834824:0.176025:0.64712:5983:rs2460000
1   2195117 rs7547453   C   T   .   PASS    AF=0.36506  ES:SE:LP:AF:SS:ID   0.0261378:0.0764293:0.135275:0.36506:5983:rs7547453
1   2199057 rs11588312  C   T   .   PASS    AF=0.06662  ES:SE:LP:AF:SS:ID   -0.198126:0.178239:0.574596:0.06662:5983:rs11588312
1   2204755 rs7553178   G   A   .   PASS    AF=0.685318 ES:SE:LP:AF:SS:ID   -0.0077471:0.0801532:0.0347974:0.685318:5983:rs7553178
1   2211849 rs10910047  A   G   .   PASS    AF=0.595973 ES:SE:LP:AF:SS:ID   -0.0151111:0.07981:0.0706692:0.595973:5983:rs10910047
1   2220649 rs2017143   C   T   .   PASS    AF=0.458096 ES:SE:LP:AF:SS:ID   0.0079258:0.0841943:0.0338581:0.458096:5983:rs2017143
1   2231463 rs903916    C   T   .   PASS    AF=0.311047 ES:SE:LP:AF:SS:ID   -0.111183:0.0864965:0.701912:0.311047:5983:rs903916