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-7385/UKB-b-7385_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7385/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7385/UKB-b-7385_data.vcf.gz ...
Read summary statistics for 3599366 SNPs.
Dropped 582 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, 874971 SNPs remain.
After merging with regression SNP LD, 874971 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0045 (0.0012)
Lambda GC: 1.0662
Mean Chi^2: 1.0582
Intercept: 1.0122 (0.0087)
Ratio: 0.2098 (0.15)
Analysis finished at Thu Oct 17 14:40:58 2019
Total time elapsed: 38.91s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8569,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 7.5991e-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": 29032,
    "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": 874971,
    "ldsc_nsnp_merge_regression_ld": 874971,
    "ldsc_observed_scale_h2_beta": 0.0045,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0122,
    "ldsc_intercept_se": 0.0087,
    "ldsc_lambda_gc": 1.0662,
    "ldsc_mean_chisq": 1.0582,
    "ldsc_ratio": 0.2096
}
 

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 3598787 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 3599366 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 8.661964e+00 5.771678e+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 7.854336e+07 5.674740e+07 828.0000000 3.157781e+07 6.889952e+07 1.147300e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 8.000000e-07 1.764000e-04 -0.0009467 -1.170000e-04 7.000000e-07 1.183000e-04 9.591000e-04 ▁▂▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.702000e-04 1.870000e-05 0.0001447 1.539000e-04 1.642000e-04 1.833000e-04 5.293000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.895849e-01 2.915639e-01 0.0000022 2.300001e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.895853e-01 2.915373e-01 0.0000022 2.340556e-01 4.855794e-01 7.424238e-01 9.999996e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.109865e-01 1.991810e-01 0.1444500 2.366110e-01 3.702320e-01 5.618548e-01 8.555480e-01 ▇▅▃▃▂
numeric AF_reference 29032 0.9919341 NA NA NA NA NA NA NA 3.978640e-01 2.075830e-01 0.0000000 2.280350e-01 3.646170e-01 5.493210e-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 0.0001491 0.0002664 0.5800000 0.5757040 0.623763 0.782149 NA
1 54676 rs2462492 C T -0.0001864 0.0002639 0.4799997 0.4800294 0.400401 NA NA
1 91536 rs6702460 G T 0.0002401 0.0002598 0.3599996 0.3554259 0.456851 0.420727 NA
1 534192 rs6680723 C T 0.0002053 0.0002968 0.4899999 0.4890848 0.240960 NA NA
1 706368 rs55727773 A G -0.0000879 0.0001842 0.6300007 0.6331824 0.515650 0.275160 NA
1 729679 rs4951859 C G 0.0000056 0.0002155 0.9800000 0.9793938 0.843212 0.639976 NA
1 752566 rs3094315 G A -0.0000314 0.0002087 0.8800001 0.8802412 0.838951 0.718251 NA
1 752721 rs3131972 A G -0.0000424 0.0002085 0.8400000 0.8389732 0.838580 0.653355 NA
1 754503 rs3115859 G A -0.0000203 0.0002079 0.9199999 0.9222169 0.838033 0.663938 NA
1 754964 rs3131966 C T -0.0000108 0.0002085 0.9599999 0.9587350 0.838664 0.663339 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51182485 rs6009961 A G 0.0000505 0.0001739 0.7700005 0.7714177 0.715505 0.6383790 NA
22 51186143 rs2879914 T C -0.0000743 0.0001613 0.6400000 0.6448892 0.381826 0.2733630 NA
22 51186228 rs3865766 C T -0.0001864 0.0001572 0.2399999 0.2358593 0.451063 0.4532750 NA
22 51192586 rs5771006 G A -0.0003179 0.0002118 0.1299999 0.1334017 0.167620 0.0848642 NA
22 51193227 rs34608236 T G 0.0001652 0.0002165 0.4500005 0.4455708 0.168489 0.0692891 NA
22 51197266 rs61290853 A G -0.0003028 0.0001623 0.0619998 0.0620819 0.386333 0.4229230 NA
22 51198027 rs34939255 A G 0.0001955 0.0001837 0.2900000 0.2873020 0.254557 0.0984425 NA
22 51211106 rs9628250 T C 0.0001731 0.0001822 0.3400001 0.3420644 0.271547 0.1671330 NA
22 51212875 rs2238837 A C -0.0001892 0.0001731 0.2700001 0.2742423 0.331455 0.3724040 NA
22 51237063 rs3896457 T C -0.0001416 0.0001772 0.4199997 0.4241661 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  0.00014907:0.000266353:0.236572:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.000186361:0.000263872:0.318759:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  0.000240102:0.000259818:0.443698:0.456851:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  0.0002053:0.000296777:0.309804:0.24096:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -8.79266e-05:0.000184235:0.200659:0.51565:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843212 ES:SE:LP:AF:ID  5.56723e-06:0.000215543:0.00877392:0.843212:rs4951859
1   752566  rs3094315   G   A   .   PASS    AF=0.838951 ES:SE:LP:AF:ID  -3.14492e-05:0.000208738:0.0555173:0.838951:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83858  ES:SE:LP:AF:ID  -4.23713e-05:0.000208513:0.0757207:0.83858:rs3131972
1   754503  rs3115859   G   A   .   PASS    AF=0.838033 ES:SE:LP:AF:ID  -2.0303e-05:0.000207934:0.0362122:0.838033:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838664 ES:SE:LP:AF:ID  -1.0789e-05:0.000208519:0.0177288:0.838664:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  2.44959e-05:0.000211339:0.0409586:0.839777:rs3131965
1   760912  rs1048488   C   T   .   PASS    AF=0.838313 ES:SE:LP:AF:ID  1.40584e-05:0.00020754:0.0222764:0.838313:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838434 ES:SE:LP:AF:ID  1.6749e-05:0.000207686:0.0268721:0.838434:rs3115850
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -0.000127938:0.000215998:0.259637:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761304 ES:SE:LP:AF:ID  9.93491e-05:0.000176293:0.244125:0.761304:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  7.05206e-05:0.000196922:0.142668:0.26539:rs12124819
1   798400  rs10900604  A   G   .   PASS    AF=0.20658  ES:SE:LP:AF:ID  -6.86826e-05:0.000188072:0.148742:0.20658:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206409 ES:SE:LP:AF:ID  -6.77687e-05:0.000188153:0.142668:0.206409:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772626 ES:SE:LP:AF:ID  0.000168061:0.000178983:0.455932:0.772626:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772854 ES:SE:LP:AF:ID  0.000173939:0.000179285:0.481486:0.772854:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340397 ES:SE:LP:AF:ID  0.00030645:0.000252623:0.638272:0.340397:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697259 ES:SE:LP:AF:ID  -4.91668e-05:0.000169012:0.113509:0.697259:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705403 ES:SE:LP:AF:ID  -0.000146782:0.000165954:0.420216:0.705403:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705448 ES:SE:LP:AF:ID  -0.000148135:0.000165949:0.431798:0.705448:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705634 ES:SE:LP:AF:ID  -0.000151185:0.000165956:0.443698:0.705634:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705662 ES:SE:LP:AF:ID  -0.000149354:0.000165974:0.431798:0.705662:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730134 ES:SE:LP:AF:ID  -5.74426e-05:0.000170496:0.130768:0.730134:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294371 ES:SE:LP:AF:ID  0.000148165:0.000165966:0.431798:0.294371:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236696 ES:SE:LP:AF:ID  0.000228328:0.000176697:0.69897:0.236696:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236684 ES:SE:LP:AF:ID  0.000228705:0.000176699:0.69897:0.236684:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239743 ES:SE:LP:AF:ID  0.000195713:0.000176133:0.568636:0.239743:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236686 ES:SE:LP:AF:ID  0.000228547:0.000176698:0.69897:0.236686:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212416 ES:SE:LP:AF:ID  0.000138001:0.000183653:0.346787:0.212416:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212311 ES:SE:LP:AF:ID  0.00012747:0.000183685:0.309804:0.212311:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237171 ES:SE:LP:AF:ID  0.000230477:0.000176562:0.721246:0.237171:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.212956 ES:SE:LP:AF:ID  0.000138474:0.000183424:0.346787:0.212956:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212918 ES:SE:LP:AF:ID  0.000131899:0.000183462:0.327902:0.212918:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241155 ES:SE:LP:AF:ID  0.000259831:0.00017533:0.853872:0.241155:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213538 ES:SE:LP:AF:ID  0.000144459:0.000183191:0.366532:0.213538:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269503 ES:SE:LP:AF:ID  0.00016979:0.00016918:0.49485:0.269503:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213508 ES:SE:LP:AF:ID  0.000136224:0.000183214:0.337242:0.213508:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214583 ES:SE:LP:AF:ID  0.000137273:0.000182861:0.346787:0.214583:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246197 ES:SE:LP:AF:ID  7.96282e-05:0.000174125:0.187087:0.246197:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.27001  ES:SE:LP:AF:ID  0.000175215:0.0001693:0.522879:0.27001:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400106 ES:SE:LP:AF:ID  0.000207545:0.000153079:0.744727:0.400106:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237094 ES:SE:LP:AF:ID  7.39421e-05:0.000177808:0.167491:0.237094:rs1574243
1   842013  rs7419119   T   G   .   PASS    AF=0.215384 ES:SE:LP:AF:ID  0.000136816:0.000182983:0.346787:0.215384:rs7419119
1   842362  rs28540380  C   T   .   PASS    AF=0.235321 ES:SE:LP:AF:ID  9.49949e-05:0.000180468:0.221849:0.235321:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362599 ES:SE:LP:AF:ID  8.2e-06:0.000190031:0.0132283:0.362599:rs11516185
1   844300  rs61769713  C   G   .   PASS    AF=0.818815 ES:SE:LP:AF:ID  -0.000171735:0.000195299:0.420216:0.818815:rs61769713