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/public/UKB-b-7966/UKB-b-7966_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7966/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7966/UKB-b-7966_data.vcf.gz ...
Read summary statistics for 4098180 SNPs.
Dropped 791 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 970817 SNPs remain.
After merging with regression SNP LD, 970817 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0024 (0.0011)
Lambda GC: 1.0265
Mean Chi^2: 1.0283
Intercept: 1.0039 (0.0083)
Ratio: 0.1369 (0.294)
Analysis finished at Thu Oct 17 14:42:22 2019
Total time elapsed: 1.0m:15.5s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8792,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 5.3932e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "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": 33517,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 970817,
    "ldsc_nsnp_merge_regression_ld": 970817,
    "ldsc_observed_scale_h2_beta": 0.0024,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0039,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.0265,
    "ldsc_mean_chisq": 1.0283,
    "ldsc_ratio": 0.1378
}

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 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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 4097394 0 NA NA 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 NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 4098180 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.656738e+00 5.766717e+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 NA NA 7.857993e+07 5.674756e+07 828.0000000 3.164108e+07 6.892083e+07 1.146945e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 5.000000e-07 2.056000e-04 -0.0012842 -1.343000e-04 3.000000e-07 1.354000e-04 1.287600e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.005000e-04 2.900000e-05 0.0001639 1.754000e-04 1.909000e-04 2.203000e-04 5.994000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.959275e-01 2.903643e-01 0.0000005 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.959297e-01 2.903404e-01 0.0000005 2.432042e-01 4.945022e-01 7.475665e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.901390e-01 2.158725e-01 0.1121440 2.021940e-01 3.406890e-01 5.492602e-01 8.878560e-01 ▇▅▃▂▂
numeric AF_reference 33517 0.9918215 NA NA NA NA NA NA NA 3.795879e-01 2.190112e-01 0.0000000 1.992810e-01 3.376600e-01 5.371410e-01 1.000000e+00 ▆▇▅▃▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -0.0003359 0.0003016 0.2700001 0.2653715 0.623763 0.782149 NA
1 54676 rs2462492 C T 0.0000097 0.0002988 0.9699999 0.9742057 0.400401 NA NA
1 91536 rs6702460 G T 0.0000481 0.0002942 0.8700001 0.8701141 0.456851 0.420727 NA
1 534192 rs6680723 C T -0.0000584 0.0003361 0.8600001 0.8620946 0.240960 NA NA
1 693731 rs12238997 A G 0.0004181 0.0002816 0.1400000 0.1376782 0.116325 0.141773 NA
1 706368 rs55727773 A G -0.0003036 0.0002086 0.1499999 0.1456322 0.515650 0.275160 NA
1 729679 rs4951859 C G -0.0003011 0.0002441 0.2200002 0.2173578 0.843212 0.639976 NA
1 731718 rs142557973 T C 0.0003421 0.0002672 0.2000000 0.2004446 0.122307 0.154353 NA
1 734349 rs141242758 T C 0.0003207 0.0002673 0.2300001 0.2302274 0.121549 0.152556 NA
1 736289 rs79010578 T A 0.0002073 0.0002634 0.4299995 0.4313614 0.132330 0.139577 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G -0.0002771 0.0002081 0.1800002 0.1829074 0.254557 0.0984425 NA
22 51208537 rs72619593 G A 0.0007024 0.0002781 0.0120000 0.0115459 0.120739 0.1142170 NA
22 51210289 rs112565862 C T -0.0001951 0.0002770 0.4799997 0.4811041 0.129955 0.1018370 NA
22 51211106 rs9628250 T C -0.0001661 0.0002063 0.4199997 0.4205730 0.271547 0.1671330 NA
22 51211392 rs3888396 T C -0.0002125 0.0002745 0.4400003 0.4387473 0.132635 0.1641370 NA
22 51212875 rs2238837 A C 0.0000274 0.0001960 0.8900000 0.8886802 0.331455 0.3724040 NA
22 51213613 rs34726907 C T -0.0001396 0.0002582 0.5900000 0.5888564 0.127816 0.1727240 NA
22 51216564 rs9616970 T C -0.0001290 0.0002571 0.6200004 0.6158187 0.128330 0.1563500 NA
22 51219006 rs28729663 G A -0.0001233 0.0002517 0.6200004 0.6241264 0.137953 0.2052720 NA
22 51237063 rs3896457 T C 0.0001318 0.0002006 0.5099998 0.5113970 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  -0.000335942:0.000301622:0.568636:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  9.66179e-06:0.000298812:0.0132283:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  4.81093e-05:0.000294222:0.0604807:0.456851:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  -5.83789e-05:0.000336074:0.0655015:0.24096:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.116325 ES:SE:LP:AF:ID  0.000418103:0.000281647:0.853872:0.116325:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -0.000303586:0.000208631:0.823909:0.51565:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843212 ES:SE:LP:AF:ID  -0.000301097:0.000244083:0.657577:0.843212:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122307 ES:SE:LP:AF:ID  0.000342054:0.00026717:0.69897:0.122307:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121549 ES:SE:LP:AF:ID  0.000320679:0.000267283:0.638272:0.121549:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13233  ES:SE:LP:AF:ID  0.000207286:0.000263433:0.366532:0.13233:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838951 ES:SE:LP:AF:ID  -0.000258459:0.000236377:0.568636:0.838951:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83858  ES:SE:LP:AF:ID  -0.000257576:0.000236123:0.552842:0.83858:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869781 ES:SE:LP:AF:ID  -0.000265145:0.000253369:0.522879:0.869781:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129871 ES:SE:LP:AF:ID  0.000271396:0.000253888:0.537602:0.129871:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869123 ES:SE:LP:AF:ID  -0.000259654:0.000252873:0.522879:0.869123:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:ID  -0.000264802:0.000252974:0.522879:0.869221:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869126 ES:SE:LP:AF:ID  -0.000268232:0.000252868:0.537602:0.869126:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838033 ES:SE:LP:AF:ID  -0.000251497:0.000235468:0.537602:0.838033:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838664 ES:SE:LP:AF:ID  -0.000246299:0.000236129:0.522879:0.838664:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  -0.000249023:0.000239323:0.522879:0.839777:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869405 ES:SE:LP:AF:ID  -0.000274449:0.000252576:0.552842:0.869405:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:ID  -0.000264361:0.00025194:0.537602:0.868952:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867905 ES:SE:LP:AF:ID  -0.000275411:0.000251457:0.568636:0.867905:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  -0.000277838:0.000252147:0.568636:0.869095:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  -0.0002776:0.000252166:0.568636:0.869104:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869112 ES:SE:LP:AF:ID  -0.000278261:0.000252172:0.568636:0.869112:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869589 ES:SE:LP:AF:ID  -0.000276366:0.000252864:0.568636:0.869589:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838313 ES:SE:LP:AF:ID  -0.000271207:0.000235021:0.60206:0.838313:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838434 ES:SE:LP:AF:ID  -0.00026827:0.000235187:0.60206:0.838434:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862261 ES:SE:LP:AF:ID  -0.000321117:0.00025126:0.69897:0.862261:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -0.000445206:0.000244599:1.16115:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761304 ES:SE:LP:AF:ID  -0.000146179:0.000199637:0.337242:0.761304:rs2977608
1   769223  rs60320384  C   G   .   PASS    AF=0.129576 ES:SE:LP:AF:ID  0.000319307:0.000253737:0.677781:0.129576:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868911 ES:SE:LP:AF:ID  -0.000294251:0.000252381:0.619789:0.868911:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129677 ES:SE:LP:AF:ID  0.000313301:0.000253573:0.657577:0.129677:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868921 ES:SE:LP:AF:ID  -0.000299225:0.000252386:0.619789:0.868921:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  4.65263e-05:0.000222998:0.0809219:0.26539:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870044 ES:SE:LP:AF:ID  -0.000361942:0.000252901:0.823909:0.870044:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.128576 ES:SE:LP:AF:ID  0.000379489:0.000253899:0.853872:0.128576:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128873 ES:SE:LP:AF:ID  0.000386322:0.000253469:0.886057:0.128873:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868786 ES:SE:LP:AF:ID  -0.000369585:0.000252227:0.853872:0.868786:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.129513 ES:SE:LP:AF:ID  0.000392591:0.000253387:0.920819:0.129513:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.868539 ES:SE:LP:AF:ID  -0.000359328:0.000252168:0.823909:0.868539:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.86848  ES:SE:LP:AF:ID  -0.000355419:0.000252325:0.79588:0.86848:rs2980300
1   787399  rs2905055   G   T   .   PASS    AF=0.86078  ES:SE:LP:AF:ID  -0.000338791:0.000252152:0.744727:0.86078:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.128461 ES:SE:LP:AF:ID  0.000376171:0.000254753:0.853872:0.128461:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.861493 ES:SE:LP:AF:ID  -0.000346654:0.000252318:0.769551:0.861493:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.869229 ES:SE:LP:AF:ID  -0.000347229:0.000253247:0.769551:0.869229:rs2905053
1   791191  rs111818025 G   A   .   PASS    AF=0.127879 ES:SE:LP:AF:ID  0.000369514:0.000256385:0.823909:0.127879:rs111818025
1   795988  rs59380221  C   T   .   PASS    AF=0.143051 ES:SE:LP:AF:ID  0.000257279:0.000261537:0.481486:0.143051:rs59380221