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-1044/ieu-a-1044.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-1044/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 08:24:48 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1044/ieu-a-1044.vcf.gz ...
Read summary statistics for 6500141 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, 1170964 SNPs remain.
After merging with regression SNP LD, 1170964 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2436 (0.0382)
Lambda GC: 1.0274
Mean Chi^2: 1.0327
Intercept: 0.97 (0.006)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb  5 08:26:02 2020
Total time elapsed: 1.0m:13.38s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9426,
    "inflation_factor": 1.0098,
    "mean_EFFECT": -0.1126,
    "n": 13171,
    "n_snps": 6500141,
    "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": 89010,
    "n_est": 12880.3672,
    "ratio_se_n": 0.9889,
    "mean_diff": 0.1124,
    "ratio_diff": 4134.7476,
    "sd_y_est1": 401.7511,
    "sd_y_est2": 397.2939,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1170964,
    "ldsc_nsnp_merge_regression_ld": 1170964,
    "ldsc_observed_scale_h2_beta": 0.2436,
    "ldsc_observed_scale_h2_se": 0.0382,
    "ldsc_intercept_beta": 0.97,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0274,
    "ldsc_mean_chisq": 1.0327,
    "ldsc_ratio": -0.9174
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 TRUE
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 58 0 6500141 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 8.614879e+00 5.742563e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.937055e+07 5.625637e+07 828.0000000 3.317411e+07 7.028167e+07 1.150802e+08 2.492178e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.126209e-01 1.316518e+01 -180.2410000 -5.522800e+00 -7.650000e-02 5.351800e+00 2.252690e+02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.063570e+01 7.964178e+00 4.6742000 5.385100e+00 7.194500e+00 1.252220e+01 6.434450e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.984869e-01 2.896379e-01 0.0000001 2.470000e-01 4.978999e-01 7.496007e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.984869e-01 2.896379e-01 0.0000001 2.470213e-01 4.979106e-01 7.496083e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.606224e-01 2.612725e-01 0.0026390 4.617000e-02 1.609000e-01 4.129000e-01 9.986810e-01 ▇▂▂▁▁
numeric AF_reference 89010 0.9863065 NA NA NA NA NA 2.626582e-01 2.529963e-01 0.0000000 5.531150e-02 1.751200e-01 4.107430e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.230245e+04 1.694275e+03 5590.0000000 1.256900e+04 1.317100e+04 1.317100e+04 1.317100e+04 ▁▁▁▁▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 752566 rs3094315 G A -5.2670 6.5561 0.4218004 0.4217586 0.8364 0.718251 11697
1 752721 rs3131972 A G -5.5229 6.7266 0.4115997 0.4116157 0.8325 0.653355 11697
1 752894 rs3131971 T C -6.3300 7.0498 0.3692003 0.3692400 0.7955 0.753195 11697
1 753541 rs2073813 G A 0.6080 7.7823 0.9377000 0.9377278 0.1332 0.301917 11697
1 754182 rs3131969 A G -0.6260 7.7899 0.9358999 0.9359506 0.8668 0.678514 11697
1 754192 rs3131968 A G -0.6444 7.8314 0.9343999 0.9344208 0.8654 0.678514 11697
1 754334 rs3131967 T C -3.3401 9.0046 0.7106995 0.7106877 0.8377 0.684305 7259
1 754503 rs3115859 G A -6.2273 7.1035 0.3807001 0.3806755 0.8311 0.663938 11697
1 754964 rs3131966 C T -7.0450 7.6495 0.3571001 0.3570634 0.8074 0.663339 11147
1 755775 rs3131965 A G -11.4683 8.3949 0.1719000 0.1719066 0.7942 NA 8172
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51164115 rs5770996 C T 6.8721 5.2452 0.1900999 0.1901386 0.40770 0.5147760 11783
22 51164287 rs6009957 T C 0.2905 5.6611 0.9591000 0.9590744 0.28630 0.4155350 11783
22 51165390 rs76268556 C T -53.0846 26.9070 0.0485099 0.0485079 0.02507 0.0515176 6609
22 51165664 rs8137951 G A 1.0769 5.6404 0.8485999 0.8485834 0.28100 0.4063500 11783
22 51169045 rs8140772 C T -35.6534 23.7622 0.1334999 0.1335043 0.02770 0.0632987 7154
22 51171667 rs41281537 G A -35.8971 23.4364 0.1256001 0.1256011 0.02770 0.0577077 7429
22 51171693 rs756638 G A -7.2917 6.3199 0.2485999 0.2485952 0.25990 0.3049120 11041
22 51172460 rs5770824 T C -35.8172 23.4902 0.1272999 0.1273160 0.02770 0.0684904 7429
22 51175626 rs3810648 A G 3.6697 11.0409 0.7396002 0.7396074 0.05277 0.1084270 12042
22 51178090 rs2285395 G A -1.5362 11.4908 0.8936001 0.8936481 0.05145 0.0666933 12042

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.8364   ES:SE:LP:AF:SS:ID   -5.267:6.5561:0.374893:0.8364:11697:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.8325   ES:SE:LP:AF:SS:ID   -5.5229:6.7266:0.385525:0.8325:11697:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.7955   ES:SE:LP:AF:SS:ID   -6.33:7.0498:0.432738:0.7955:11697:rs3131971
1   753541  rs2073813   G   A   .   PASS    AF=0.1332   ES:SE:LP:AF:SS:ID   0.608:7.7823:0.0279361:0.1332:11697:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -0.626:7.7899:0.0287706:0.8668:11697:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.8654   ES:SE:LP:AF:SS:ID   -0.6444:7.8314:0.0294672:0.8654:11697:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8377   ES:SE:LP:AF:SS:ID   -3.3401:9.0046:0.148314:0.8377:7259:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.8311   ES:SE:LP:AF:SS:ID   -6.2273:7.1035:0.419417:0.8311:11697:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.8074   ES:SE:LP:AF:SS:ID   -7.045:7.6495:0.44721:0.8074:11147:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.7942   ES:SE:LP:AF:SS:ID   -11.4683:8.3949:0.764724:0.7942:8172:rs3131965
1   756604  rs3131962   A   G   .   PASS    AF=0.8351   ES:SE:LP:AF:SS:ID   -5.0438:8.8696:0.24443:0.8351:7545:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -1.9493:8.8993:0.0827046:0.8668:7740:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.8681   ES:SE:LP:AF:SS:ID   -1.9119:8.9108:0.0808696:0.8681:7740:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -1.7908:8.9137:0.0753073:0.8668:7740:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.8391   ES:SE:LP:AF:SS:ID   -6.406:8.2242:0.360514:0.8391:9075:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8641   ES:SE:LP:AF:SS:ID   -3.3863:9.1396:0.14813:0.8641:6873:rs3131954
1   768448  rs12562034  G   A   .   PASS    AF=0.09763  ES:SE:LP:AF:SS:ID   10.1912:9.7708:0.52739:0.09763:8796:rs12562034
1   769963  rs7518545   G   A   .   PASS    AF=0.09499  ES:SE:LP:AF:SS:ID   11.5305:10.3035:0.579879:0.09499:8796:rs7518545
1   798400  rs10900604  A   G   .   PASS    AF=0.2203   ES:SE:LP:AF:SS:ID   -2.2096:7.7785:0.109914:0.2203:7687:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.2269   ES:SE:LP:AF:SS:ID   -2.1225:7.2886:0.113002:0.2269:7687:rs11240777
1   876499  rs4372192   A   G   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -9.2804:14.2667:0.287856:0.94987:8496:rs4372192
1   879676  rs6605067   G   A   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -6.7498:14.0043:0.200797:0.94987:8496:rs6605067
1   879687  rs2839  T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -3.6955:13.8393:0.102703:0.95119:9046:rs2839
1   880238  rs3748592   A   G   .   PASS    AF=0.95251  ES:SE:LP:AF:SS:ID   -3.9599:13.8245:0.110979:0.95251:9046:rs3748592
1   882803  rs2340582   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -3.4293:13.5048:0.0971815:0.95119:9046:rs2340582
1   884815  rs4246503   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.6382:13.0889:0.0755656:0.95119:9046:rs4246503
1   885676  rs4970377   C   A   .   PASS    AF=0.94327  ES:SE:LP:AF:SS:ID   -1.662:12.756:0.0475466:0.94327:9046:rs4970377
1   885689  rs4970452   G   A   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -4.2108:13.2946:0.124071:0.94987:9046:rs4970452
1   885699  rs4970376   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.7526:13.0467:0.0794071:0.95119:9046:rs4970376
1   886006  rs4970375   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.6879:12.97:0.0778976:0.95119:9046:rs4970375
1   887801  rs3828047   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.5724:12.7768:0.075514:0.95119:9046:rs3828047
1   888639  rs3748596   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.5978:12.7552:0.0764451:0.95119:9046:rs3748596
1   888659  rs3748597   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.427:12.7301:0.0711946:0.95119:9046:rs3748597
1   889238  rs3828049   G   A   .   PASS    AF=0.04749  ES:SE:LP:AF:SS:ID   3.4732:12.9796:0.102923:0.04749:9046:rs3828049
1   889713  rs13303051  C   A   .   PASS    AF=0.94063  ES:SE:LP:AF:SS:ID   -1.16:12.2188:0.0341401:0.94063:9046:rs13303051
1   891021  rs13302957  G   A   .   PASS    AF=0.94591  ES:SE:LP:AF:SS:ID   -0.1798:12.7496:0.00489154:0.94591:9046:rs13302957
1   892745  rs13303227  G   A   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.5412:12.9584:0.0734003:0.95119:9046:rs13303227
1   893280  rs4970371   G   A   .   PASS    AF=0.95251  ES:SE:LP:AF:SS:ID   -3.5345:13.2344:0.102703:0.95251:9046:rs4970371
1   893631  rs6605069   A   G   .   PASS    AF=0.93931  ES:SE:LP:AF:SS:ID   1.2433:12.5285:0.0357875:0.93931:9046:rs6605069
1   893719  rs4970445   G   A   .   PASS    AF=0.92744  ES:SE:LP:AF:SS:ID   1.8074:12.5148:0.0529586:0.92744:8496:rs4970445
1   896476  rs28393498  A   G   .   PASS    AF=0.93536  ES:SE:LP:AF:SS:ID   -0.0458:13.1585:0.00121773:0.93536:8496:rs28393498
1   897564  rs13303229  T   C   .   PASS    AF=0.94459  ES:SE:LP:AF:SS:ID   -2.921:13.3271:0.0827571:0.94459:8496:rs13303229
1   897738  rs6696971   C   T   .   PASS    AF=0.05541  ES:SE:LP:AF:SS:ID   2.3235:13.3438:0.0645935:0.05541:8496:rs6696971
1   898323  rs6605071   T   C   .   PASS    AF=0.94723  ES:SE:LP:AF:SS:ID   -4.6117:13.8609:0.131121:0.94723:9046:rs6605071
1   898467  rs41285808  C   T   .   PASS    AF=0.04617  ES:SE:LP:AF:SS:ID   4.0518:13.9228:0.112946:0.04617:9046:rs41285808
1   913889  rs2340596   G   A   .   PASS    AF=0.6003   ES:SE:LP:AF:SS:ID   8.4702:5.7366:0.854493:0.6003:10048:rs2340596
1   914940  rs13303033  T   C   .   PASS    AF=0.5858   ES:SE:LP:AF:SS:ID   9.1407:5.5784:0.994391:0.5858:10048:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.5989   ES:SE:LP:AF:SS:ID   8.0285:5.5101:0.838333:0.5989:10048:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.5871   ES:SE:LP:AF:SS:ID   8.7232:5.4224:0.967784:0.5871:10048:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.5963   ES:SE:LP:AF:SS:ID   7.6027:5.4339:0.791021:0.5963:10048:rs2341354