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-1043/ieu-a-1043.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-1043/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 08:58:59 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1043/ieu-a-1043.vcf.gz ...
Read summary statistics for 6507245 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, 1170948 SNPs remain.
After merging with regression SNP LD, 1170948 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0178 (0.0313)
Lambda GC: 0.9943
Mean Chi^2: 0.9964
Intercept: 1.0011 (0.0058)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Wed Feb  5 09:00:08 2020
Total time elapsed: 1.0m:8.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9427,
    "inflation_factor": 0.9967,
    "mean_EFFECT": -0.0713,
    "n": 13160,
    "n_snps": 6507245,
    "n_clumped_hits": 1,
    "n_p_sig": 3,
    "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": 89193,
    "n_est": 12832.1503,
    "ratio_se_n": 0.9875,
    "mean_diff": 0.071,
    "ratio_diff": 62949.7349,
    "sd_y_est1": 193.806,
    "sd_y_est2": 191.3767,
    "r2_sum1": 245.3973,
    "r2_sum2": 0.0065,
    "r2_sum3": 0.0067,
    "r2_sum4": 0.0038,
    "ldsc_nsnp_merge_refpanel_ld": 1170948,
    "ldsc_nsnp_merge_regression_ld": 1170948,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0011,
    "ldsc_intercept_se": 0.0058,
    "ldsc_lambda_gc": 0.9943,
    "ldsc_mean_chisq": 0.9964,
    "ldsc_ratio": -0.3056
}

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 TRUE
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 6507245 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 8.614409e+00 5.742120e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.937395e+07 5.625300e+07 828.000000 3.318054e+07 7.028398e+07 1.150832e+08 2.492178e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -7.134970e-02 6.673993e+00 -130.708000 -2.643900e+00 -3.990000e-02 2.550600e+00 1.127640e+02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 5.232039e+00 4.107934e+00 2.254000 2.594300e+00 3.472100e+00 6.065300e+00 3.464120e+01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.999929e-01 2.884708e-01 0.000000 2.497998e-01 5.007005e-01 7.494005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.999929e-01 2.884708e-01 0.000000 2.497963e-01 5.006673e-01 7.493985e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.603523e-01 2.612737e-01 0.002639 4.485000e-02 1.596000e-01 4.129000e-01 9.986810e-01 ▇▂▂▁▁
numeric AF_reference 89193 0.9862933 NA NA NA NA NA 2.623903e-01 2.530068e-01 0.000000 5.511180e-02 1.747200e-01 4.103430e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.228399e+04 1.708630e+03 5589.000000 1.256300e+04 1.316000e+04 1.316000e+04 1.316000e+04 ▁▁▁▁▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 752566 rs3094315 G A -3.5251 3.2260 0.2744998 0.2745188 0.8364 0.718251 11685
1 752721 rs3131972 A G -3.6723 3.3011 0.2658998 0.2659458 0.8325 0.653355 11685
1 752894 rs3131971 T C -4.2266 3.4933 0.2263002 0.2263111 0.7955 0.753195 11685
1 753541 rs2073813 G A 2.7817 3.8608 0.4711997 0.4712182 0.1332 0.301917 11685
1 754182 rs3131969 A G -2.8768 3.8952 0.4602004 0.4601803 0.8668 0.678514 11685
1 754192 rs3131968 A G -2.8431 3.9194 0.4681996 0.4682118 0.8654 0.678514 11685
1 754334 rs3131967 T C -0.2901 4.6297 0.9500000 0.9500367 0.8377 0.684305 7246
1 754503 rs3115859 G A -3.6026 3.5476 0.3099003 0.3098659 0.8311 0.663938 11685
1 754964 rs3131966 C T -3.5320 3.8213 0.3552998 0.3553339 0.8074 0.663339 11135
1 755775 rs3131965 A G -2.5082 4.2451 0.5546002 0.5546237 0.7942 NA 8159
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51164115 rs5770996 C T 0.0974 2.5442 0.9695000 0.9694619 0.40770 0.5147760 11774
22 51164287 rs6009957 T C 3.1542 2.7670 0.2542998 0.2543134 0.28630 0.4155350 11774
22 51165390 rs76268556 C T 0.2409 13.3052 0.9856000 0.9855545 0.02507 0.0515176 6612
22 51165664 rs8137951 G A 3.2874 2.7567 0.2330999 0.2330602 0.28100 0.4063500 11774
22 51169045 rs8140772 C T 7.1788 11.8861 0.5458999 0.5458663 0.02770 0.0632987 7154
22 51171667 rs41281537 G A 6.7459 11.5388 0.5587995 0.5587982 0.02770 0.0577077 7426
22 51171693 rs756638 G A 3.8269 3.0445 0.2088002 0.2087580 0.25990 0.3049120 11028
22 51172460 rs5770824 T C 6.7378 11.5673 0.5601999 0.5602388 0.02770 0.0684904 7426
22 51175626 rs3810648 A G 9.1582 5.3579 0.0873997 0.0873974 0.05277 0.1084270 12034
22 51178090 rs2285395 G A 8.9808 5.5906 0.1081999 0.1081837 0.05145 0.0666933 12034

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.8364   ES:SE:LP:AF:SS:ID   -3.5251:3.226:0.561458:0.8364:11685:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.8325   ES:SE:LP:AF:SS:ID   -3.6723:3.3011:0.575282:0.8325:11685:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.7955   ES:SE:LP:AF:SS:ID   -4.2266:3.4933:0.645315:0.7955:11685:rs3131971
1   753541  rs2073813   G   A   .   PASS    AF=0.1332   ES:SE:LP:AF:SS:ID   2.7817:3.8608:0.326795:0.1332:11685:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -2.8768:3.8952:0.337053:0.8668:11685:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.8654   ES:SE:LP:AF:SS:ID   -2.8431:3.9194:0.329569:0.8654:11685:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8377   ES:SE:LP:AF:SS:ID   -0.2901:4.6297:0.0222764:0.8377:7246:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.8311   ES:SE:LP:AF:SS:ID   -3.6026:3.5476:0.508778:0.8311:11685:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.8074   ES:SE:LP:AF:SS:ID   -3.532:3.8213:0.449405:0.8074:11135:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.7942   ES:SE:LP:AF:SS:ID   -2.5082:4.2451:0.25602:0.7942:8159:rs3131965
1   756604  rs3131962   A   G   .   PASS    AF=0.8351   ES:SE:LP:AF:SS:ID   -1.9739:4.5467:0.177701:0.8351:7532:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -0.1127:4.56:0.008641:0.8668:7727:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.8681   ES:SE:LP:AF:SS:ID   -0.1052:4.5657:0.00806545:0.8681:7727:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -0.2473:4.5669:0.0191788:0.8668:7727:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.8391   ES:SE:LP:AF:SS:ID   -0.089:4.1962:0.0074023:0.8391:9063:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8641   ES:SE:LP:AF:SS:ID   0.9036:4.7078:0.0717066:0.8641:6860:rs3131954
1   768448  rs12562034  G   A   .   PASS    AF=0.09763  ES:SE:LP:AF:SS:ID   -9.6035:4.704:1.3851:0.09763:8790:rs12562034
1   769963  rs7518545   G   A   .   PASS    AF=0.09499  ES:SE:LP:AF:SS:ID   -9.7268:4.9598:1.30225:0.09499:8790:rs7518545
1   798400  rs10900604  A   G   .   PASS    AF=0.2203   ES:SE:LP:AF:SS:ID   -4.6428:3.8629:0.639407:0.2203:7675:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.2269   ES:SE:LP:AF:SS:ID   -4.3922:3.6566:0.638839:0.2269:7675:rs11240777
1   876499  rs4372192   A   G   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -11.2257:7.136:0.936667:0.94987:8487:rs4372192
1   879676  rs6605067   G   A   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -10.2731:7.0266:0.842543:0.94987:8487:rs6605067
1   879687  rs2839  T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -8.7777:6.9321:0.6874:0.95119:9037:rs2839
1   880238  rs3748592   A   G   .   PASS    AF=0.95251  ES:SE:LP:AF:SS:ID   -8.967:6.9233:0.709298:0.95251:9037:rs3748592
1   882803  rs2340582   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -8.5355:6.7285:0.689094:0.95119:9037:rs2340582
1   884815  rs4246503   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -8.1052:6.5287:0.668775:0.95119:9037:rs4246503
1   885676  rs4970377   C   A   .   PASS    AF=0.94327  ES:SE:LP:AF:SS:ID   -4.8959:6.3638:0.354873:0.94327:9037:rs4970377
1   885689  rs4970452   G   A   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   -8.2109:6.5956:0.671213:0.94987:9037:rs4970452
1   885699  rs4970376   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -8.0955:6.5025:0.671417:0.95119:9037:rs4970376
1   886006  rs4970375   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -8.2221:6.4254:0.697453:0.95119:9037:rs4970375
1   887801  rs3828047   A   G   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -8.2728:6.337:0.717378:0.95119:9037:rs3828047
1   888639  rs3748596   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -8.2829:6.3253:0.720333:0.95119:9037:rs3748596
1   888659  rs3748597   T   C   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -8.2246:6.3154:0.714893:0.95119:9037:rs3748597
1   889238  rs3828049   G   A   .   PASS    AF=0.04749  ES:SE:LP:AF:SS:ID   8.4078:6.4226:0.720105:0.04749:9037:rs3828049
1   889713  rs13303051  C   A   .   PASS    AF=0.94063  ES:SE:LP:AF:SS:ID   -5.2364:6.0912:0.408935:0.94063:9037:rs13303051
1   891021  rs13302957  G   A   .   PASS    AF=0.94591  ES:SE:LP:AF:SS:ID   -8.1022:6.3198:0.699405:0.94591:9037:rs13302957
1   892745  rs13303227  G   A   .   PASS    AF=0.95119  ES:SE:LP:AF:SS:ID   -8.4946:6.4457:0.726999:0.95119:9037:rs13303227
1   893280  rs4970371   G   A   .   PASS    AF=0.95251  ES:SE:LP:AF:SS:ID   -8.5466:6.5563:0.715795:0.95251:9037:rs4970371
1   893631  rs6605069   A   G   .   PASS    AF=0.93931  ES:SE:LP:AF:SS:ID   -5.6926:6.2571:0.440213:0.93931:9037:rs6605069
1   893719  rs4970445   G   A   .   PASS    AF=0.92744  ES:SE:LP:AF:SS:ID   -7.1093:6.2715:0.590067:0.92744:8487:rs4970445
1   896476  rs28393498  A   G   .   PASS    AF=0.93536  ES:SE:LP:AF:SS:ID   -8.7769:6.5798:0.739452:0.93536:8487:rs28393498
1   897564  rs13303229  T   C   .   PASS    AF=0.94459  ES:SE:LP:AF:SS:ID   -7.1739:6.6894:0.547447:0.94459:8487:rs13303229
1   897738  rs6696971   C   T   .   PASS    AF=0.05541  ES:SE:LP:AF:SS:ID   7.525:6.6891:0.584026:0.05541:8487:rs6696971
1   898323  rs6605071   T   C   .   PASS    AF=0.94723  ES:SE:LP:AF:SS:ID   -8.1153:6.9184:0.618344:0.94723:9037:rs6605071
1   898467  rs41285808  C   T   .   PASS    AF=0.04617  ES:SE:LP:AF:SS:ID   8.4611:6.941:0.652085:0.04617:9037:rs41285808
1   913889  rs2340596   G   A   .   PASS    AF=0.6003   ES:SE:LP:AF:SS:ID   -0.0893:2.8569:0.0109508:0.6003:10039:rs2340596
1   914940  rs13303033  T   C   .   PASS    AF=0.5858   ES:SE:LP:AF:SS:ID   -0.3993:2.7732:0.0528114:0.5858:10039:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.5989   ES:SE:LP:AF:SS:ID   -0.2455:2.7213:0.0324052:0.5989:10039:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.5871   ES:SE:LP:AF:SS:ID   -0.4134:2.678:0.0568519:0.5871:10039:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.5963   ES:SE:LP:AF:SS:ID   -0.2917:2.6797:0.0393865:0.5963:10039:rs2341354