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-1283/ieu-a-1283.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-1283/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 08:26:01 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1283/ieu-a-1283.vcf.gz ...
Read summary statistics for 12145990 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, 1179193 SNPs remain.
After merging with regression SNP LD, 1179193 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0796 (0.0061)
Lambda GC: 1.1569
Mean Chi^2: 1.1867
Intercept: 1.0115 (0.0072)
Ratio: 0.0618 (0.0387)
Analysis finished at Wed Feb  5 08:27:58 2020
Total time elapsed: 1.0m:57.09s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.962,
    "inflation_factor": 1.0916,
    "mean_EFFECT": 5.0312e-06,
    "n": 112176,
    "n_snps": 12145990,
    "n_clumped_hits": 4,
    "n_p_sig": 450,
    "n_mono": 0,
    "n_ns": 737208,
    "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": 209751,
    "n_est": 112726.2133,
    "ratio_se_n": 1.0024,
    "mean_diff": 0.0001,
    "ratio_diff": 1.2823,
    "sd_y_est1": 0.291,
    "sd_y_est2": 0.2917,
    "r2_sum1": 0.0009,
    "r2_sum2": 0.0104,
    "r2_sum3": 0.0103,
    "r2_sum4": 0.003,
    "ldsc_nsnp_merge_refpanel_ld": 1179193,
    "ldsc_nsnp_merge_regression_ld": 1179193,
    "ldsc_observed_scale_h2_beta": 0.0796,
    "ldsc_observed_scale_h2_se": 0.0061,
    "ldsc_intercept_beta": 1.0115,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.1569,
    "ldsc_mean_chisq": 1.1867,
    "ldsc_ratio": 0.0616
}

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 12145990 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 51 0 43874 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 51 0 20053 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.648176e+00 5.773932e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.892473e+07 5.638348e+07 3.0200e+02 3.246477e+07 6.964761e+07 1.146319e+08 2.492397e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.000000e-06 3.153500e-03 -3.4270e-02 -2.102000e-03 1.020000e-05 2.115000e-03 2.895000e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.992200e-03 3.030000e-05 2.9730e-03 2.977000e-03 2.982000e-03 2.994000e-03 3.286000e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.856189e-01 2.928682e-01 0.0000e+00 2.283000e-01 4.809999e-01 7.393992e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.856176e-01 2.928690e-01 0.0000e+00 2.283434e-01 4.809743e-01 7.394111e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.788784e-01 2.487973e-01 1.0000e-03 4.918000e-03 4.794000e-02 2.709000e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 209751 0.9827308 NA NA NA NA NA 1.746916e-01 2.403539e-01 0.0000e+00 3.394600e-03 5.251600e-02 2.655750e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.107771e+05 2.359169e+03 8.9742e+04 1.106470e+05 1.115380e+05 1.119460e+05 1.121760e+05 ▁▁▁▁▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C -0.0004700 0.002994 0.8752999 0.8752601 0.998929 0.9930110 110621
1 13453 rs568927457 T C -0.0021630 0.003017 0.4735000 0.4734128 0.001158 0.0007987 108819
1 13483 rs554760071 G C -0.0012510 0.003011 0.6779006 0.6777931 0.001221 0.0019968 109313
1 15585 rs533630043 G A 0.0011100 0.003018 0.7130993 0.7130274 0.001686 0.0009984 108823
1 16949 rs199745162 A C -0.0010640 0.003103 0.7317993 0.7316782 0.005829 0.0139776 102082
1 18643 rs564023708 G A 0.0006483 0.003009 0.8293999 0.8294137 0.001763 0.0055910 109465
1 18849 rs533090414 C G -0.0011650 0.003089 0.7060005 0.7060661 0.994005 0.9518770 103256
1 51762 rs559190862 A G -0.0010640 0.003015 0.7242008 0.7241618 0.001711 0.0119808 108971
1 51765 rs575564077 C G -0.0010630 0.003015 0.7242992 0.7244105 0.001711 0.0119808 108992
1 52238 rs2691277 T G 0.0035630 0.003108 0.2516999 0.2516312 0.994355 0.9217250 101778
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51234677 rs189571549 A C -0.0014130 0.002985 0.6359003 0.6359515 0.001266 0.0227636 111347
22 51234799 rs191117135 G A 0.0004782 0.003016 0.8739999 0.8740200 0.006522 0.0059904 109016
22 51235497 rs201907533 GA G -0.0024360 0.002983 0.4140998 0.4141413 0.001215 0.0087859 111488
22 51237364 rs200607599 A G 0.0015980 0.003035 0.5986004 0.5985243 0.007061 0.0187700 107494
22 51237712 rs370652263 G A 0.0006481 0.003048 0.8316000 0.8316146 0.041580 0.0690895 106510
22 51238318 rs541098394 A T 0.0036900 0.002988 0.2169002 0.2168529 0.001346 0.0019968 111044
22 51238364 rs564490465 C G -0.0006852 0.003014 0.8201000 0.8201601 0.001181 0.0005990 109185
22 51238394 rs149712012 C T 0.0012620 0.002986 0.6724996 0.6725587 0.001114 0.0033946 111267
22 51241386 rs568168135 C G -0.0015020 0.003015 0.6182996 0.6183601 0.002027 0.0139776 109038
22 51244237 rs575160859 C T -0.0003390 0.003057 0.9117001 0.9117012 0.004097 0.0037939 105810

bcf preview

1   10616   rs376342519 CCGCCGTTGCAAAGGCGCGCCG  C   .   PASS    AF=0.998929 ES:SE:LP:AF:SS:ID   -0.00047:0.002994:0.0578431:0.998929:110621:rs376342519
1   13453   rs568927457 T   C   .   PASS    AF=0.001158 ES:SE:LP:AF:SS:ID   -0.002163:0.003017:0.32468:0.001158:108819:rs568927457
1   13483   rs554760071 G   C   .   PASS    AF=0.001221 ES:SE:LP:AF:SS:ID   -0.001251:0.003011:0.168834:0.001221:109313:rs554760071
1   15585   rs533630043 G   A   .   PASS    AF=0.001686 ES:SE:LP:AF:SS:ID   0.00111:0.003018:0.14685:0.001686:108823:rs533630043
1   16949   rs199745162 A   C   .   PASS    AF=0.005829 ES:SE:LP:AF:SS:ID   -0.001064:0.003103:0.135608:0.005829:102082:rs199745162
1   18643   rs564023708 G   A   .   PASS    AF=0.001763 ES:SE:LP:AF:SS:ID   0.0006483:0.003009:0.081236:0.001763:109465:rs564023708
1   18849   rs533090414 C   G   .   PASS    AF=0.994005 ES:SE:LP:AF:SS:ID   -0.001165:0.003089:0.151195:0.994005:103256:rs533090414
1   51762   rs559190862 A   G   .   PASS    AF=0.001711 ES:SE:LP:AF:SS:ID   -0.001064:0.003015:0.140141:0.001711:108971:rs559190862
1   51765   rs575564077 C   G   .   PASS    AF=0.001711 ES:SE:LP:AF:SS:ID   -0.001063:0.003015:0.140082:0.001711:108992:rs575564077
1   52238   rs2691277   T   G   .   PASS    AF=0.994355 ES:SE:LP:AF:SS:ID   0.003563:0.003108:0.599117:0.994355:101778:rs2691277
1   52253   rs530867301 C   G   .   PASS    AF=0.001311 ES:SE:LP:AF:SS:ID   -0.0001133:0.003:0.013273:0.001311:110195:rs530867301
1   54945   rs569799965 C   A   .   PASS    AF=0.001186 ES:SE:LP:AF:SS:ID   -0.002929:0.003002:0.48254:0.001186:109989:rs569799965
1   55164   rs3091274   C   A   .   PASS    AF=0.995388 ES:SE:LP:AF:SS:ID   0.004138:0.003078:0.747633:0.995388:104182:rs3091274
1   55249   rs200769871 C   CTATGG  .   PASS    AF=0.003635 ES:SE:LP:AF:SS:ID   -0.003445:0.003015:0.596536:0.003635:109068:rs200769871
1   55326   rs3107975   T   C   .   PASS    AF=0.003932 ES:SE:LP:AF:SS:ID   -0.002724:0.003057:0.428408:0.003932:105798:rs3107975
1   57292   rs201418760 C   T   .   PASS    AF=0.005242 ES:SE:LP:AF:SS:ID   -0.006694:0.003095:1.5147:0.005242:102721:rs201418760
1   60249   rs547227933 C   T   .   PASS    AF=0.004939 ES:SE:LP:AF:SS:ID   0.001269:0.003072:0.167747:0.004939:104566:rs547227933
1   61208   rs527362206 T   C   .   PASS    AF=0.001186 ES:SE:LP:AF:SS:ID   -0.002929:0.003002:0.48254:0.001186:109989:rs527362206
1   61743   rs184286948 G   C   .   PASS    AF=0.00142  ES:SE:LP:AF:SS:ID   -0.00394:0.003004:0.721933:0.00142:109843:rs184286948
1   61920   rs62637820  G   A   .   PASS    AF=0.008987 ES:SE:LP:AF:SS:ID   0.001563:0.003136:0.208941:0.008987:99536:rs62637820
1   63093   rs200092917 G   A   .   PASS    AF=0.004763 ES:SE:LP:AF:SS:ID   -0.001319:0.003097:0.173796:0.004763:102674:rs200092917
1   63336   rs62639100  C   T   .   PASS    AF=0.003566 ES:SE:LP:AF:SS:ID   0.0008441:0.003014:0.10824:0.003566:109087:rs62639100
1   64649   rs181431124 A   C   .   PASS    AF=0.008133 ES:SE:LP:AF:SS:ID   0.0002652:0.003117:0.0304909:0.008133:101064:rs181431124
1   65015   rs552404520 C   T   .   PASS    AF=0.001474 ES:SE:LP:AF:SS:ID   0.001555:0.003017:0.217312:0.001474:108872:rs552404520
1   65974   rs531923826 A   G   .   PASS    AF=0.001156 ES:SE:LP:AF:SS:ID   0.001999:0.002992:0.297397:0.001156:110726:rs531923826
1   66219   rs181028663 A   T   .   PASS    AF=0.003343 ES:SE:LP:AF:SS:ID   -0.003921:0.003067:0.696372:0.003343:104999:rs181028663
1   66231   rs556427688 TAATA   T   .   PASS    AF=0.001741 ES:SE:LP:AF:SS:ID   0.0005205:0.002983:0.0647447:0.001741:111433:rs556427688
1   67107   rs545950684 A   G   .   PASS    AF=0.001134 ES:SE:LP:AF:SS:ID   -0.00288:0.003:0.47237:0.001134:110184:rs545950684
1   67580   rs571658168 T   A   .   PASS    AF=0.003226 ES:SE:LP:AF:SS:ID   -0.00381:0.003012:0.686555:0.003226:109259:rs571658168
1   69428   rs140739101 T   G   .   PASS    AF=0.009669 ES:SE:LP:AF:SS:ID   -0.0005128:0.003194:0.0592843:0.009669:94577:rs140739101
1   70351   rs528419934 TA  T   .   PASS    AF=0.001138 ES:SE:LP:AF:SS:ID   0.003172:0.003004:0.536256:0.001138:109872:rs528419934
1   72297   rs200651397 G   GTAT    .   PASS    AF=0.001886 ES:SE:LP:AF:SS:ID   -0.002755:0.00303:0.439854:0.001886:107897:rs200651397
1   72526   rs547237130 A   G   .   PASS    AF=0.01078  ES:SE:LP:AF:SS:ID   0.002666:0.003229:0.388383:0.01078:91485:rs547237130
1   73490   rs558384541 T   C   .   PASS    AF=0.004329 ES:SE:LP:AF:SS:ID   0.0007298:0.003084:0.0899095:0.004329:103609:rs558384541
1   73876   rs534133098 G   A   .   PASS    AF=0.001246 ES:SE:LP:AF:SS:ID   0.006225:0.002986:1.43028:0.001246:111176:rs534133098
1   74790   rs13328700  C   G   .   PASS    AF=0.009164 ES:SE:LP:AF:SS:ID   -0.001418:0.003183:0.183096:0.009164:95531:rs13328700
1   74792   rs13328684  G   A   .   PASS    AF=0.009164 ES:SE:LP:AF:SS:ID   -0.001418:0.003183:0.183096:0.009164:95531:rs13328684
1   77726   rs540748103 C   T   .   PASS    AF=0.001388 ES:SE:LP:AF:SS:ID   -0.004354:0.003014:0.827981:0.001388:109131:rs540748103
1   77763   rs557457745 G   A   .   PASS    AF=0.001186 ES:SE:LP:AF:SS:ID   0.001577:0.002996:0.222863:0.001186:110432:rs557457745
1   78061   rs550898066 C   G   .   PASS    AF=0.00301  ES:SE:LP:AF:SS:ID   0.0008509:0.00303:0.108518:0.00301:107823:rs550898066
1   79137   rs143777184 A   T   .   PASS    AF=0.001693 ES:SE:LP:AF:SS:ID   0.001152:0.003004:0.154096:0.001693:109846:rs143777184
1   80221   rs573179234 C   T   .   PASS    AF=0.002158 ES:SE:LP:AF:SS:ID   -0.002002:0.003017:0.295078:0.002158:108878:rs573179234
1   81032   rs530221379 G   A   .   PASS    AF=0.00123  ES:SE:LP:AF:SS:ID   -0.001415:0.003011:0.194839:0.00123:109328:rs530221379
1   81260   rs571136476 C   T   .   PASS    AF=0.009917 ES:SE:LP:AF:SS:ID   0.0001956:0.003223:0.0215456:0.009917:92066:rs571136476
1   82957   rs189774606 C   T   .   PASS    AF=0.00123  ES:SE:LP:AF:SS:ID   -0.001415:0.003011:0.194839:0.00123:109328:rs189774606
1   83771   rs189906733 T   G   .   PASS    AF=0.001271 ES:SE:LP:AF:SS:ID   -0.001133:0.003015:0.150519:0.001271:109009:rs189906733
1   84139   rs183605470 A   T   .   PASS    AF=0.005448 ES:SE:LP:AF:SS:ID   -0.0003341:0.003072:0.039339:0.005448:104537:rs183605470
1   84183   rs570923646 C   G   .   PASS    AF=0.001384 ES:SE:LP:AF:SS:ID   -0.004123:0.003014:0.766243:0.001384:109142:rs570923646
1   85022   rs552048778 G   A   .   PASS    AF=0.001459 ES:SE:LP:AF:SS:ID   0.002296:0.003007:0.351542:0.001459:109650:rs552048778
1   85892   rs147185795 A   G   .   PASS    AF=0.001156 ES:SE:LP:AF:SS:ID   0.002279:0.002992:0.350373:0.001156:110725:rs147185795