Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_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 /data/cromwell-executions/qc/97049f53-ff78-41d3-8bf6-98a2e48d4c24/call-ldsc/inputs/-1729375641/bbj-a-70.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/bbj-a-70/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Sat Aug 21 03:30:44 2021
Reading summary statistics from /data/cromwell-executions/qc/97049f53-ff78-41d3-8bf6-98a2e48d4c24/call-ldsc/inputs/-1729375641/bbj-a-70.vcf.gz ...
Read summary statistics for 0 SNPs.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
Traceback (most recent call last):
  File "./ldsc/ldsc.py", line 647, in <module>
    sumstats.estimate_h2(args, log)
  File "/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
    args, log, args.h2)
  File "/ldsc/ldscore/sumstats.py", line 252, in _read_ld_sumstats
    sumstats = _merge_and_log(ref_ld, sumstats, 'reference panel LD', log)
  File "/ldsc/ldscore/sumstats.py", line 238, in _merge_and_log
    raise ValueError(msg.format(N=len(sumstats), F=noun))
ValueError: After merging with reference panel LD, 0 SNPs remain.

Analysis finished at Sat Aug 21 03:32:59 2021
Total time elapsed: 2.0m:14.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9393,
    "inflation_factor": 1.1999,
    "mean_EFFECT": "-Inf",
    "n": "-Inf",
    "n_snps": 27198769,
    "n_clumped_hits": 399,
    "n_p_sig": 68647,
    "n_mono": 176046,
    "n_ns": 1836749,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 7108179,
    "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": 0,
    "ldsc_nsnp_merge_regression_ld": "NA",
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": "NA",
    "ldsc_intercept_se": "NA",
    "ldsc_lambda_gc": "NA",
    "ldsc_mean_chisq": "NA",
    "ldsc_ratio": "NA"
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite TRUE
mean_EFFECT_05 TRUE
mean_EFFECT_01 TRUE
mean_chisq NA
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio NA
ldsc_intercept_beta NA
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 2563538 0.9057480 3 12 0 24611912 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 308 0 110177 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 577 0 51370 0 NA NA NA NA NA NA NA NA NA NA
logical N 27198769 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 8.541649e+00 5.712393e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.20000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.963094e+07 5.567255e+07 78.000000 3.408597e+07 7.083952e+07 1.148177e+08 2.49233e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -Inf NaN -Inf -2.488030e-02 -1.550000e-05 2.514760e-02 1.13643e+16 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA Inf NaN 0.003061 1.187750e-02 4.937500e-02 8.920540e-02 Inf ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.735429e-01 3.025131e-01 0.000000 2.000000e-01 4.600002e-01 7.400005e-01 1.00000e+00 ▇▆▆▆▆
numeric PVAL_ztest 4288 0.9998423 NA NA NA NA NA NA NA 4.733435e-01 3.022302e-01 0.000000 2.038077e-01 4.637857e-01 7.356452e-01 1.00000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 8.444470e-02 1.999705e-01 0.000000 5.800000e-04 1.620000e-03 2.247000e-02 1.00000e+00 ▇▁▁▁▁
numeric AF_reference 7108179 0.7386581 NA NA NA NA NA NA NA 1.079467e-01 2.049737e-01 0.000000 3.994000e-04 2.396200e-03 1.124200e-01 1.00000e+00 ▇▁▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 693206 rs543880342 G A -0.0427065 0.0402224 0.3700002 0.2883451 0.00369 0.0007987 NA
1 707522 rs371890604 G C -0.0055277 0.0077110 0.5600000 0.4734590 0.12364 0.1293930 NA
1 711310 rs200531508 G A -0.0115671 0.0098578 0.2800000 0.2406372 0.07469 0.0736821 NA
1 713979 rs117217250 C G -0.0293429 0.0328352 0.4500005 0.3715137 0.00550 0.0009984 NA
1 716131 rs148067420 C T -0.0241439 0.0224855 0.2500000 0.2829329 0.01464 0.0041933 NA
1 725848 rs1318476454 GATGGAATGGAATGGAATGGACTCGAAAGGATTGGAATGGAATACAATGGAATGGTCTCGAATGGAATGGAATGGAATGGACTCGA G -0.0493338 0.0178572 0.0290001 0.0057328 0.02113 NA NA
1 729739 rs148932570 C T -0.0279453 0.0311759 0.4500005 0.3700525 0.00570 0.0011981 NA
1 731718 rs142557973 T C -0.0047938 0.0065229 0.5500004 0.4623940 0.13705 0.1543530 NA
1 732032 rs61770163 A C -0.0048137 0.0064487 0.5500004 0.4553888 0.13607 0.1555510 NA
1 734349 rs141242758 T C -0.0042912 0.0063683 0.5800000 0.5004092 0.13696 0.1525560 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51234290 rs531245009 T C -0.0223122 0.0251258 0.6200004 0.3745303 0.01227 0.0005990 NA
22 51234343 rs374867791 G T 0.0048186 0.0071276 0.4100001 0.4990074 0.12310 0.1002400 NA
22 51235959 rs200189535 T C 0.0072258 0.0058235 0.2800000 0.2146794 0.26343 0.1996810 NA
22 51237063 rs3896457 T C -0.0009887 0.0051629 0.8000000 0.8481342 0.29423 0.2050720 NA
22 51237069 rs183661957 T C 0.0004793 0.0147826 0.6899999 0.9741330 0.02185 0.0029952 NA
22 51237533 rs570924129 C A 0.0298430 0.1065380 0.7700005 0.7793885 0.00065 0.0003994 NA
22 51237692 rs1316686161 CTTAT C 0.0166340 0.0421721 0.3300000 0.6932626 0.00437 NA NA
22 51239678 rs573137567 G T 0.0021119 0.0089838 0.8700001 0.8141483 0.06323 0.0233626 NA
22 51240084 rs529322970 G C -0.0349987 0.0344102 0.2700001 0.3091047 0.00583 0.0027955 NA
22 51240820 rs202228854 C T 0.0024341 0.0072027 0.6600001 0.7354015 0.13802 0.1267970 NA

bcf preview

1   693206  rs543880342 G   A   .   PASS    AF=0.00369  ES:SE:LP:AF:ID  -0.0427065:0.0402224:0.431798:0.00369:rs543880342
1   707522  rs371890604 G   C   .   PASS    AF=0.12364  ES:SE:LP:AF:ID  -0.00552769:0.00771095:0.251812:0.12364:rs371890604
1   711310  rs200531508 G   A   .   PASS    AF=0.07469  ES:SE:LP:AF:ID  -0.0115671:0.0098578:0.552842:0.07469:rs200531508
1   713979  rs117217250 C   G   .   PASS    AF=0.0055   ES:SE:LP:AF:ID  -0.0293429:0.0328352:0.346787:0.0055:rs117217250
1   716131  rs148067420 C   T   .   PASS    AF=0.01464  ES:SE:LP:AF:ID  -0.0241439:0.0224855:0.60206:0.01464:rs148067420
1   725848  rs1318476454    GATGGAATGGAATGGAATGGACTCGAAAGGATTGGAATGGAATACAATGGAATGGTCTCGAATGGAATGGAATGGAATGGACTCGA  G   .   PASS    AF=0.02113  ES:SE:LP:AF:ID  -0.0493338:0.0178572:1.5376:0.02113:rs1318476454
1   729739  rs148932570 C   T   .   PASS    AF=0.0057   ES:SE:LP:AF:ID  -0.0279453:0.0311759:0.346787:0.0057:rs148932570
1   731718  rs58276399  T   C   .   PASS    AF=0.13705  ES:SE:LP:AF:ID  -0.00479377:0.00652293:0.259637:0.13705:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.13607  ES:SE:LP:AF:ID  -0.00481369:0.00644868:0.259637:0.13607:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.13696  ES:SE:LP:AF:ID  -0.00429124:0.00636828:0.236572:0.13696:rs141242758
1   736289  rs1254887344    T   A   .   PASS    AF=0.13532  ES:SE:LP:AF:ID  -0.00743545:0.00664986:0.522879:0.13532:rs1254887344
1   737801  rs540210562 T   C   .   PASS    AF=0.01034  ES:SE:LP:AF:ID  -0.0770339:0.0260492:2.16115:0.01034:rs540210562
1   739990  rs571946818 G   A   .   PASS    AF=0.03131  ES:SE:LP:AF:ID  -0.0206662:0.0132633:0.638272:0.03131:rs571946818
1   742990  rs202009397 C   T   .   PASS    AF=0.12004  ES:SE:LP:AF:ID  -0.00647338:0.00656103:0.443698:0.12004:rs202009397
1   743420  rs201920982 G   A   .   PASS    AF=0.04118  ES:SE:LP:AF:ID  0.000263807:0.0139822:0.107905:0.04118:rs201920982
1   746898  rs374909644 G   A   .   PASS    AF=0.00409  ES:SE:LP:AF:ID  0.0436364:0.0326423:0.920819:0.00409:rs374909644
1   748878  rs2519043   G   T   .   PASS    AF=0.68565  ES:SE:LP:AF:ID  0.00569774:0.0058099:0.408935:0.68565:rs2519043
1   749068  rs1275281910    A   G   .   PASS    AF=0.00546  ES:SE:LP:AF:ID  0.0445089:0.0358727:0.853872:0.00546:rs1275281910
1   749963  rs56197012  T   TAA .   PASS    AF=0.83135  ES:SE:LP:AF:ID  0.00301699:0.00510669:0.154902:0.83135:rs56197012
1   751343  rs28544273  T   A   .   PASS    AF=0.14804  ES:SE:LP:AF:ID  -0.00313333:0.00455951:0.236572:0.14804:rs28544273
1   751756  rs28527770  T   C   .   PASS    AF=0.14753  ES:SE:LP:AF:ID  -0.00311209:0.00454779:0.236572:0.14753:rs28527770
1   751763  rs1414790336    T   A   .   PASS    AF=0.00256  ES:SE:LP:AF:ID  -0.0267582:0.055154:0.130768:0.00256:rs1414790336
1   752566  rs3094315   G   A   .   PASS    AF=0.84228  ES:SE:LP:AF:ID  0.00307242:0.0042133:0.259637:0.84228:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.71954  ES:SE:LP:AF:ID  0.00334445:0.00459863:0.275724:0.71954:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.84964  ES:SE:LP:AF:ID  0.00313397:0.00443094:0.244125:0.84964:rs3131971
1   753405  rs3115860   C   A   .   PASS    AF=0.85122  ES:SE:LP:AF:ID  0.0031398:0.00451579:0.236572:0.85122:rs3115860
1   753425  rs1431026348    T   C   .   PASS    AF=0.85054  ES:SE:LP:AF:ID  0.00313179:0.0044967:0.236572:0.85054:rs1431026348
1   753474  rs2073814   C   G   .   PASS    AF=0.64977  ES:SE:LP:AF:ID  0.00746591:0.00484494:0.920819:0.64977:rs2073814
1   753541  rs1388595942    G   A   .   PASS    AF=0.32291  ES:SE:LP:AF:ID  -0.0080626:0.00515645:0.958607:0.32291:rs1388595942
1   754182  rs3131969   A   G   .   PASS    AF=0.67308  ES:SE:LP:AF:ID  0.00796217:0.00502533:0.958607:0.67308:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.67306  ES:SE:LP:AF:ID  0.00796636:0.00502577:0.958607:0.67306:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.72692  ES:SE:LP:AF:ID  0.00345326:0.00488987:0.267606:0.72692:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.72062  ES:SE:LP:AF:ID  0.00351547:0.0047252:0.29243:0.72062:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.72021  ES:SE:LP:AF:ID  0.00350358:0.00473662:0.283997:0.72021:rs3131966
1   755214  rs572106104 T   A   .   PASS    AF=0.00135  ES:SE:LP:AF:ID  0.100372:0.0648658:0.69897:0.00135:rs572106104
1   756285  rs1557551112    ATCCACCCTGTCTACACTACCTGCTTGTCCAGCAGG    A   .   PASS    AF=0.14115  ES:SE:LP:AF:ID  -0.00391906:0.00480094:0.327902:0.14115:rs1557551112
1   759293  rs10157329  T   A   .   PASS    AF=0.12328  ES:SE:LP:AF:ID  -0.0043955:0.0053503:0.318759:0.12328:rs10157329
1   759700  rs989694037 T   C   .   PASS    AF=0.8457   ES:SE:LP:AF:ID  0.00294491:0.00441848:0.229148:0.8457:rs989694037
1   759837  rs3115851   T   A   .   PASS    AF=0.85067  ES:SE:LP:AF:ID  0.00298325:0.00456154:0.221849:0.85067:rs3115851
1   760912  rs1048488   C   T   .   PASS    AF=0.84412  ES:SE:LP:AF:ID  0.00292112:0.00442955:0.221849:0.84412:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.84382  ES:SE:LP:AF:ID  0.00291606:0.0044311:0.221849:0.84382:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.65285  ES:SE:LP:AF:ID  0.00763754:0.00505964:0.958607:0.65285:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.84894  ES:SE:LP:AF:ID  0.00293061:0.00457642:0.21467:0.84894:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.84768  ES:SE:LP:AF:ID  0.00233423:0.00472628:0.154902:0.84768:rs3115849
1   762407  rs550428451 C   A   .   PASS    AF=0.00143  ES:SE:LP:AF:ID  0.128044:0.0665158:1.20066:0.00143:rs550428451
1   762485  rs12095200  C   A   .   PASS    AF=0.10643  ES:SE:LP:AF:ID  -0.00308616:0.00623223:0.173925:0.10643:rs12095200
1   762589  rs772021405 G   C   .   PASS    AF=0.85425  ES:SE:LP:AF:ID  0.00231773:0.00477732:0.148742:0.85425:rs772021405
1   762592  rs1209077270    C   G   .   PASS    AF=0.85425  ES:SE:LP:AF:ID  0.0023221:0.00477803:0.148742:0.85425:rs1209077270
1   762601  rs3131949   T   C   .   PASS    AF=0.85433  ES:SE:LP:AF:ID  0.00232753:0.00477827:0.154902:0.85433:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.85454  ES:SE:LP:AF:ID  0.00232164:0.00477849:0.154902:0.85454:rs3131948