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-3969/UKB-b-3969_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3969/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:53 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3969/UKB-b-3969_data.vcf.gz ...
Read summary statistics for 4918936 SNPs.
Dropped 1358 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, 1104568 SNPs remain.
After merging with regression SNP LD, 1104568 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.001 (0.0012)
Lambda GC: 1.0202
Mean Chi^2: 1.0292
Intercept: 1.0197 (0.0082)
Ratio: 0.6746 (0.2816)
Analysis finished at Thu Oct 17 14:44:53 2019
Total time elapsed: 1.0m:0.07s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9045,
    "inflation_factor": 1,
    "mean_EFFECT": -7.8177e-08,
    "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": 41806,
    "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": 1104568,
    "ldsc_nsnp_merge_regression_ld": 1104568,
    "ldsc_observed_scale_h2_beta": 0.001,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0197,
    "ldsc_intercept_se": 0.0082,
    "ldsc_lambda_gc": 1.0202,
    "ldsc_mean_chisq": 1.0292,
    "ldsc_ratio": 0.6747
}
 

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 TRUE
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 1.000000 3 58 0 4917587 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 4918936 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.666351e+00 5.766169e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.858827e+07 5.666114e+07 828.0000000 3.187337e+07 6.896078e+07 1.146551e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA -1.000000e-07 2.982000e-04 -0.0026044 -1.902000e-04 -1.200000e-06 1.897000e-04 1.984500e-03 ▁▁▇▃▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 2.876000e-04 6.190000e-05 0.0002169 2.350000e-04 2.656000e-04 3.275000e-04 8.242000e-04 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.958038e-01 2.901370e-01 0.0000001 2.399999e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.958036e-01 2.901114e-01 0.0000001 2.432817e-01 4.952206e-01 7.468457e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 3.552104e-01 2.367051e-01 0.0693620 1.510490e-01 2.911520e-01 5.215730e-01 9.306380e-01 ▇▅▃▂▂
numeric AF_reference 41806 0.991501 NA NA NA NA NA NA NA 3.482451e-01 2.339021e-01 0.0000000 1.551520e-01 2.927320e-01 5.105830e-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 0.0005215 0.0003991 0.1900002 0.1913575 0.623739 0.7821490 NA
1 54676 rs2462492 C T -0.0008799 0.0003955 0.0259998 0.0260941 0.400429 NA NA
1 86028 rs114608975 T C 0.0006436 0.0006322 0.3100002 0.3086544 0.103545 0.0277556 NA
1 91536 rs6702460 G T -0.0007249 0.0003893 0.0629999 0.0626123 0.456855 0.4207270 NA
1 234313 rs8179466 C T 0.0007378 0.0007681 0.3400001 0.3367417 0.074449 NA NA
1 534192 rs6680723 C T -0.0000016 0.0004448 1.0000000 0.9971139 0.240913 NA NA
1 546697 rs12025928 A G -0.0000235 0.0005549 0.9699999 0.9662615 0.913480 NA NA
1 693731 rs12238997 A G 0.0000486 0.0003728 0.9000000 0.8963096 0.116344 0.1417730 NA
1 706368 rs55727773 A G 0.0001420 0.0002762 0.6100002 0.6071095 0.515724 0.2751600 NA
1 722670 rs116030099 T C -0.0006126 0.0004556 0.1800002 0.1787014 0.101240 0.0413339 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51213613 rs34726907 C T 0.0003264 0.0003416 0.3400001 0.3393914 0.127905 0.1727240 NA
22 51216564 rs9616970 T C 0.0003127 0.0003402 0.3599996 0.3579629 0.128427 0.1563500 NA
22 51217954 rs9616974 G A 0.0004696 0.0004316 0.2800000 0.2765621 0.073362 0.0621006 NA
22 51218224 rs9616975 C A 0.0004671 0.0004318 0.2800000 0.2792877 0.073383 0.0619010 NA
22 51218377 rs2519461 G C 0.0004285 0.0004313 0.3200000 0.3203724 0.073664 0.0826677 NA
22 51219006 rs28729663 G A 0.0002397 0.0003330 0.4700002 0.4715274 0.138031 0.2052720 NA
22 51219387 rs9616832 T C 0.0004285 0.0004321 0.3200000 0.3213760 0.073792 0.0654952 NA
22 51221731 rs115055839 T C 0.0004566 0.0004324 0.2900000 0.2909926 0.073288 0.0625000 NA
22 51229805 rs9616985 T C 0.0004829 0.0004340 0.2700001 0.2658492 0.073124 0.0730831 NA
22 51237063 rs3896457 T C 0.0000923 0.0002655 0.7300002 0.7282829 0.298133 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623739 ES:SE:LP:AF:ID  0.000521502:0.000399137:0.721246:0.623739:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400429 ES:SE:LP:AF:ID  -0.000879856:0.000395475:1.58503:0.400429:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103545 ES:SE:LP:AF:ID  0.000643618:0.000632207:0.508638:0.103545:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456855 ES:SE:LP:AF:ID  -0.000724894:0.000389323:1.20066:0.456855:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074449 ES:SE:LP:AF:ID  0.000737821:0.000768065:0.468521:0.074449:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240913 ES:SE:LP:AF:ID  -1.60903e-06:0.000444831:-0:0.240913:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91348  ES:SE:LP:AF:ID  -2.34708e-05:0.000554897:0.0132283:0.91348:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116344 ES:SE:LP:AF:ID  4.8591e-05:0.000372846:0.0457575:0.116344:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515724 ES:SE:LP:AF:ID  0.000142002:0.000276159:0.21467:0.515724:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.10124  ES:SE:LP:AF:ID  -0.000612614:0.000455555:0.744727:0.10124:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.843143 ES:SE:LP:AF:ID  0.000181553:0.000323083:0.244125:0.843143:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122332 ES:SE:LP:AF:ID  9.39331e-06:0.00035364:0.00877392:0.122332:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121574 ES:SE:LP:AF:ID  9.55607e-06:0.000353787:0.00877392:0.121574:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132399 ES:SE:LP:AF:ID  -7.4868e-05:0.00034863:0.0809219:0.132399:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838835 ES:SE:LP:AF:ID  0.000266161:0.000312809:0.408935:0.838835:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838456 ES:SE:LP:AF:ID  0.000264894:0.000312459:0.39794:0.838456:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869721 ES:SE:LP:AF:ID  6.69158e-05:0.000335316:0.0757207:0.869721:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129944 ES:SE:LP:AF:ID  -2.59062e-05:0.000335983:0.0268721:0.129944:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.86906  ES:SE:LP:AF:ID  6.49871e-05:0.000334649:0.0705811:0.86906:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869161 ES:SE:LP:AF:ID  6.41249e-05:0.000334785:0.0705811:0.869161:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869064 ES:SE:LP:AF:ID  5.57233e-05:0.000334643:0.0604807:0.869064:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837906 ES:SE:LP:AF:ID  0.000278201:0.000311591:0.431798:0.837906:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838538 ES:SE:LP:AF:ID  0.000266825:0.000312467:0.408935:0.838538:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83966  ES:SE:LP:AF:ID  0.000268297:0.000316715:0.39794:0.83966:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869349 ES:SE:LP:AF:ID  5.51155e-05:0.000334274:0.0604807:0.869349:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868902 ES:SE:LP:AF:ID  7.41564e-05:0.000333449:0.0861861:0.868902:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867845 ES:SE:LP:AF:ID  7.92025e-05:0.000332789:0.091515:0.867845:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86904  ES:SE:LP:AF:ID  7.17582e-05:0.000333715:0.0809219:0.86904:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869049 ES:SE:LP:AF:ID  7.11769e-05:0.000333741:0.0809219:0.869049:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869057 ES:SE:LP:AF:ID  7.19381e-05:0.000333749:0.0809219:0.869057:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869532 ES:SE:LP:AF:ID  5.84657e-05:0.000334653:0.0655015:0.869532:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838195 ES:SE:LP:AF:ID  0.000267915:0.000311017:0.408935:0.838195:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838314 ES:SE:LP:AF:ID  0.000268824:0.000311237:0.408935:0.838314:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862199 ES:SE:LP:AF:ID  7.91846e-05:0.000332552:0.091515:0.862199:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706677 ES:SE:LP:AF:ID  0.000318513:0.000323742:0.481486:0.706677:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105153 ES:SE:LP:AF:ID  0.000254748:0.000372981:0.309804:0.105153:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761341 ES:SE:LP:AF:ID  -0.00011691:0.000264348:0.180456:0.761341:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106407 ES:SE:LP:AF:ID  0.000268778:0.00036438:0.337242:0.106407:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129633 ES:SE:LP:AF:ID  -4.33068e-05:0.000335822:0.0457575:0.129633:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868863 ES:SE:LP:AF:ID  5.93639e-05:0.000334032:0.0655015:0.868863:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129732 ES:SE:LP:AF:ID  -1.58698e-05:0.000335605:0.0177288:0.129732:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868873 ES:SE:LP:AF:ID  6.94856e-05:0.000334039:0.0757207:0.868873:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265292 ES:SE:LP:AF:ID  -0.000139314:0.000295217:0.19382:0.265292:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870019 ES:SE:LP:AF:ID  8.52592e-05:0.000334743:0.09691:0.870019:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095095 ES:SE:LP:AF:ID  0.000418713:0.000388058:0.552842:0.095095:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128601 ES:SE:LP:AF:ID  -4.67978e-05:0.000336065:0.05061:0.128601:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128897 ES:SE:LP:AF:ID  -4.06878e-05:0.0003355:0.0457575:0.128897:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868758 ES:SE:LP:AF:ID  6.84145e-05:0.000333852:0.0757207:0.868758:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.101856 ES:SE:LP:AF:ID  0.000244764:0.000378339:0.283997:0.101856:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.129546 ES:SE:LP:AF:ID  -2.32849e-05:0.000335388:0.0268721:0.129546:rs6594026