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-1042/ieu-a-1042.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-1042/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 09:28:29 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1042/ieu-a-1042.vcf.gz ...
Read summary statistics for 6497752 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, 1170862 SNPs remain.
After merging with regression SNP LD, 1170862 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0875 (0.036)
Lambda GC: 0.9968
Mean Chi^2: 1.0027
Intercept: 0.9801 (0.006)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb  5 09:29:38 2020
Total time elapsed: 1.0m:8.68s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9426,
    "inflation_factor": 0.9888,
    "mean_EFFECT": -0.0031,
    "n": 13112,
    "n_snps": 6497752,
    "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": 89021,
    "n_est": 12870.1528,
    "ratio_se_n": 0.9907,
    "mean_diff": 0.0031,
    "ratio_diff": 243.6839,
    "sd_y_est1": 89.9928,
    "sd_y_est2": 89.159,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1170862,
    "ldsc_nsnp_merge_regression_ld": 1170862,
    "ldsc_observed_scale_h2_beta": 0.0875,
    "ldsc_observed_scale_h2_se": 0.036,
    "ldsc_intercept_beta": 0.9801,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 0.9968,
    "ldsc_mean_chisq": 1.0027,
    "ldsc_ratio": -7.3704
}

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 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 58 0 6497752 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 8.614590e+00 5.741998e+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 7.937599e+07 5.625196e+07 828.0000000 3.318435e+07 7.028517e+07 1.150864e+08 2.492178e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.101300e-03 3.027570e+00 -40.6485000 -1.213100e+00 -5.700000e-03 1.205500e+00 4.626310e+01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.419642e+00 1.870677e+00 1.0377000 1.214900e+00 1.615200e+00 2.818000e+00 1.572220e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.014144e-01 2.887480e-01 0.0000002 2.515000e-01 5.024004e-01 7.516004e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.014144e-01 2.887480e-01 0.0000002 2.514644e-01 5.023988e-01 7.516114e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.606928e-01 2.612690e-01 0.0026390 4.617000e-02 1.609000e-01 4.142000e-01 9.986810e-01 ▇▂▂▁▁
numeric AF_reference 89021 0.9862997 NA NA NA NA NA 2.627235e-01 2.529969e-01 0.0000000 5.551120e-02 1.751200e-01 4.107430e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.225270e+04 1.685151e+03 5589.0000000 1.251700e+04 1.311200e+04 1.311200e+04 1.311200e+04 ▁▁▁▁▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 752566 rs3094315 G A -0.0559 1.4725 0.9697000 0.9697175 0.8364 0.718251 11676
1 752721 rs3131972 A G -0.1739 1.5064 0.9081001 0.9080958 0.8325 0.653355 11676
1 752894 rs3131971 T C -0.0502 1.6213 0.9752999 0.9752992 0.7955 0.753195 11676
1 753541 rs2073813 G A 0.0021 1.7928 0.9991000 0.9990654 0.1332 0.301917 11676
1 754182 rs3131969 A G -0.0203 1.8094 0.9910000 0.9910486 0.8668 0.678514 11676
1 754192 rs3131968 A G -0.0345 1.8213 0.9849000 0.9848870 0.8654 0.678514 11676
1 754334 rs3131967 T C -1.1630 2.1849 0.5945002 0.5945253 0.8377 0.684305 7235
1 754503 rs3115859 G A -0.3219 1.6000 0.8406000 0.8405520 0.8311 0.663938 11676
1 754964 rs3131966 C T -0.5683 1.7665 0.7476993 0.7476727 0.8074 0.663339 11127
1 755775 rs3131965 A G -1.3907 2.0086 0.4886996 0.4887032 0.7942 NA 8148
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51164115 rs5770996 C T 0.5239 1.1543 0.6499007 0.6499237 0.40770 0.5147760 11742
22 51164287 rs6009957 T C 0.7725 1.2802 0.5462004 0.5462284 0.28630 0.4155350 11742
22 51165390 rs76268556 C T 4.1317 6.1954 0.5047996 0.5048373 0.02507 0.0515176 6611
22 51165664 rs8137951 G A 0.7929 1.2749 0.5339997 0.5339872 0.28100 0.4063500 11742
22 51169045 rs8140772 C T 2.5030 5.4866 0.6482000 0.6482445 0.02770 0.0632987 7158
22 51171667 rs41281537 G A 1.4425 5.3337 0.7867994 0.7868140 0.02770 0.0577077 7432
22 51171693 rs756638 G A 2.1092 1.4511 0.1460999 0.1460800 0.25990 0.3049120 10995
22 51172460 rs5770824 T C 1.4800 5.3513 0.7820995 0.7821116 0.02770 0.0684904 7432
22 51175626 rs3810648 A G 2.8932 2.4691 0.2412998 0.2412922 0.05277 0.1084270 12000
22 51178090 rs2285395 G A 3.0177 2.5558 0.2376999 0.2377115 0.05145 0.0666933 12000

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.8364   ES:SE:LP:AF:SS:ID   -0.0559:1.4725:0.0133626:0.8364:11676:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.8325   ES:SE:LP:AF:SS:ID   -0.1739:1.5064:0.0418663:0.8325:11676:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.7955   ES:SE:LP:AF:SS:ID   -0.0502:1.6213:0.0108618:0.7955:11676:rs3131971
1   753541  rs2073813   G   A   .   PASS    AF=0.1332   ES:SE:LP:AF:SS:ID   0.0021:1.7928:0.000391041:0.1332:11676:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -0.0203:1.8094:0.00392635:0.8668:11676:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.8654   ES:SE:LP:AF:SS:ID   -0.0345:1.8213:0.00660786:0.8654:11676:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8377   ES:SE:LP:AF:SS:ID   -1.163:2.1849:0.225848:0.8377:7235:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.8311   ES:SE:LP:AF:SS:ID   -0.3219:1.6:0.0754106:0.8311:11676:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.8074   ES:SE:LP:AF:SS:ID   -0.5683:1.7665:0.126273:0.8074:11127:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.7942   ES:SE:LP:AF:SS:ID   -1.3907:2.0086:0.310958:0.7942:8148:rs3131965
1   756604  rs3131962   A   G   .   PASS    AF=0.8351   ES:SE:LP:AF:SS:ID   -1.2383:2.1615:0.246647:0.8351:7521:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -0.9621:2.1583:0.183229:0.8668:7716:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.8681   ES:SE:LP:AF:SS:ID   -0.8237:2.1609:0.152983:0.8681:7716:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -0.8734:2.1614:0.163549:0.8668:7716:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.8391   ES:SE:LP:AF:SS:ID   -0.227:1.9355:0.0425843:0.8391:9055:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8641   ES:SE:LP:AF:SS:ID   -1.04:2.2287:0.193345:0.8641:6849:rs3131954
1   768448  rs12562034  G   A   .   PASS    AF=0.09763  ES:SE:LP:AF:SS:ID   0.8027:2.1873:0.146545:0.09763:8782:rs12562034
1   769963  rs7518545   G   A   .   PASS    AF=0.09499  ES:SE:LP:AF:SS:ID   0.8073:2.3028:0.139123:0.09499:8782:rs7518545
1   798400  rs10900604  A   G   .   PASS    AF=0.2203   ES:SE:LP:AF:SS:ID   -0.4886:1.8046:0.104246:0.2203:7662:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.2269   ES:SE:LP:AF:SS:ID   -0.6182:1.7136:0.143694:0.2269:7662:rs11240777
1   876499  rs4372192   A   G   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -3.5692:3.3182:0.549597:0.94987:8477:rs4372192
1   879676  rs6605067   G   A   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -3.7084:3.267:0.591251:0.94987:8477:rs6605067
1   879687  rs2839  T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -3.007:3.2325:0.453087:0.95119:9026:rs2839
1   880238  rs3748592   A   G   .   PASS    AF=0.95251  ES:SE:LP:AF:SS:ID   -2.939:3.2286:0.440452:0.95251:9026:rs3748592
1   882803  rs2340582   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.7589:3.1523:0.418505:0.95119:9026:rs2340582
1   884815  rs4246503   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.6259:3.0252:0.414088:0.95119:9026:rs4246503
1   885676  rs4970377   C   A   .   PASS    AF=0.94327  ES:SE:LP:AF:SS:ID   -2.418:2.9543:0.383945:0.94327:9026:rs4970377
1   885689  rs4970452   G   A   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -2.8924:3.0573:0.463315:0.94987:9026:rs4970452
1   885699  rs4970376   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.6746:3.0136:0.4262:0.95119:9026:rs4970376
1   886006  rs4970375   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.6474:2.9938:0.424235:0.95119:9026:rs4970375
1   887801  rs3828047   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.6807:2.9534:0.438779:0.95119:9026:rs3828047
1   888639  rs3748596   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.6877:2.948:0.441411:0.95119:9026:rs3748596
1   888659  rs3748597   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.6579:2.9437:0.435808:0.95119:9026:rs3748597
1   889238  rs3828049   G   A   .   PASS    AF=0.04749  ES:SE:LP:AF:SS:ID   2.854:2.9961:0.4675:0.04749:9026:rs3828049
1   889713  rs13303051  C   A   .   PASS    AF=0.94063  ES:SE:LP:AF:SS:ID   -2.5265:2.8479:0.425969:0.94063:9026:rs13303051
1   891021  rs13302957  G   A   .   PASS    AF=0.94591  ES:SE:LP:AF:SS:ID   -3.0707:2.9487:0.526221:0.94591:9026:rs13302957
1   892745  rs13303227  G   A   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -2.7026:2.9891:0.436638:0.95119:9026:rs13303227
1   893280  rs4970371   G   A   .   PASS    AF=0.95251  ES:SE:LP:AF:SS:ID   -2.8187:3.0413:0.450997:0.95251:9026:rs4970371
1   893631  rs6605069   A   G   .   PASS    AF=0.93931  ES:SE:LP:AF:SS:ID   -2.4149:2.9147:0.389979:0.93931:9026:rs6605069
1   893719  rs4970445   G   A   .   PASS    AF=0.92744  ES:SE:LP:AF:SS:ID   -3.9151:2.9163:0.746178:0.92744:8477:rs4970445
1   896476  rs28393498  A   G   .   PASS    AF=0.93536  ES:SE:LP:AF:SS:ID   -3.8745:3.0875:0.678816:0.93536:8477:rs28393498
1   897564  rs13303229  T   C   .   PASS    AF=0.94459  ES:SE:LP:AF:SS:ID   -3.5124:3.1241:0.583526:0.94459:8477:rs13303229
1   897738  rs6696971   C   T   .   PASS    AF=0.05541  ES:SE:LP:AF:SS:ID   3.5704:3.1263:0.596193:0.05541:8477:rs6696971
1   898323  rs6605071   T   C   .   PASS    AF=0.94723  ES:SE:LP:AF:SS:ID   -2.6177:3.2364:0.378201:0.94723:9026:rs6605071
1   898467  rs41285808  C   T   .   PASS    AF=0.04617  ES:SE:LP:AF:SS:ID   2.879:3.2449:0.426085:0.04617:9026:rs41285808
1   913889  rs2340596   G   A   .   PASS    AF=0.6003   ES:SE:LP:AF:SS:ID   0.1715:1.3524:0.046192:0.6003:10028:rs2340596
1   914940  rs13303033  T   C   .   PASS    AF=0.5858   ES:SE:LP:AF:SS:ID   0.4544:1.3118:0.137272:0.5858:10028:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.5989   ES:SE:LP:AF:SS:ID   0.0317:1.2553:0.00881824:0.5989:10028:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.5871   ES:SE:LP:AF:SS:ID   0.1528:1.2354:0.0449861:0.5871:10028:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.5963   ES:SE:LP:AF:SS:ID   0.1106:1.2373:0.0321246:0.5963:10028:rs2341354