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-13922/UKB-b-13922_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13922/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:05 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13922/UKB-b-13922_data.vcf.gz ...
Read summary statistics for 3356757 SNPs.
Dropped 494 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, 824698 SNPs remain.
After merging with regression SNP LD, 824698 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0006 (0.0013)
Lambda GC: 1.1399
Mean Chi^2: 1.1457
Intercept: 1.1391 (0.0106)
Ratio: 0.9547 (0.0725)
Analysis finished at Thu Oct 17 14:43:47 2019
Total time elapsed: 42.64s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8426,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 1.8919e-06,
    "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": 26906,
    "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": 824698,
    "ldsc_nsnp_merge_regression_ld": 824698,
    "ldsc_observed_scale_h2_beta": 0.0006,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.1391,
    "ldsc_intercept_se": 0.0106,
    "ldsc_lambda_gc": 1.1399,
    "ldsc_mean_chisq": 1.1457,
    "ldsc_ratio": 0.9547
}

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 1.0000000 3 58 0 3356266 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 3356757 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 8.664016e+00 5.773693e+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 7.854443e+07 5.672914e+07 828.0000000 3.157552e+07 6.891830e+07 1.147683e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.900000e-06 1.697000e-04 -0.0008739 -1.110000e-04 1.400000e-06 1.144000e-04 1.004800e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.580000e-04 1.510000e-05 0.0001366 1.448000e-04 1.533000e-04 1.686000e-04 3.379000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.793773e-01 2.943045e-01 0.0000001 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.793793e-01 2.942799e-01 0.0000001 2.186794e-01 4.725107e-01 7.338888e-01 9.999998e-01 ▇▇▇▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.210402e-01 1.900317e-01 0.1621880 2.544450e-01 3.845960e-01 5.669570e-01 8.378120e-01 ▇▆▅▃▂
numeric AF_reference 26906 0.9919845 NA NA NA NA NA NA NA 4.067355e-01 2.013386e-01 0.0000000 2.432110e-01 3.773960e-01 5.541130e-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 -0.0001190 0.0002514 0.6400000 0.6360705 0.623772 0.7821490 NA
1 54676 rs2462492 C T -0.0001306 0.0002490 0.5999997 0.5999344 0.400405 NA NA
1 91536 rs6702460 G T -0.0002231 0.0002452 0.3599996 0.3630159 0.456839 0.4207270 NA
1 534192 rs6680723 C T -0.0003244 0.0002801 0.2500000 0.2467002 0.240960 NA NA
1 706368 rs55727773 A G 0.0002500 0.0001739 0.1499999 0.1504031 0.515617 0.2751600 NA
1 763394 rs369924889 G A 0.0001549 0.0002039 0.4500005 0.4473815 0.706739 0.6176120 NA
1 768253 rs2977608 A C -0.0000057 0.0001664 0.9699999 0.9724853 0.761285 0.4894170 NA
1 776546 rs12124819 A G -0.0000614 0.0001859 0.7400005 0.7411765 0.265361 0.0756789 NA
1 798400 rs10900604 A G 0.0001120 0.0001775 0.5300002 0.5282177 0.206583 0.4105430 NA
1 798959 rs11240777 G A 0.0001145 0.0001776 0.5199996 0.5192252 0.206412 0.4099440 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51182485 rs6009961 A G -0.0002283 0.0001642 0.1600000 0.1644589 0.715485 0.6383790 NA
22 51186143 rs2879914 T C 0.0000545 0.0001523 0.7199992 0.7202934 0.381783 0.2733630 NA
22 51186228 rs3865766 C T -0.0001006 0.0001484 0.5000000 0.4979785 0.451013 0.4532750 NA
22 51192586 rs5771006 G A -0.0002219 0.0002000 0.2700001 0.2670930 0.167599 0.0848642 NA
22 51193227 rs34608236 T G 0.0000207 0.0002044 0.9199999 0.9194428 0.168508 0.0692891 NA
22 51197266 rs61290853 A G -0.0002515 0.0001532 0.1000000 0.1006952 0.386292 0.4229230 NA
22 51198027 rs34939255 A G -0.0001747 0.0001734 0.3100002 0.3137551 0.254601 0.0984425 NA
22 51211106 rs9628250 T C -0.0001390 0.0001720 0.4199997 0.4190085 0.271576 0.1671330 NA
22 51212875 rs2238837 A C 0.0000199 0.0001634 0.9000000 0.9029418 0.331412 0.3724040 NA
22 51237063 rs3896457 T C -0.0001325 0.0001673 0.4299995 0.4281625 0.297937 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623772 ES:SE:LP:AF:ID  -0.000118962:0.000251399:0.19382:0.623772:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400405 ES:SE:LP:AF:ID  -0.000130616:0.000249032:0.221849:0.400405:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456839 ES:SE:LP:AF:ID  -0.000223053:0.000245212:0.443698:0.456839:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  -0.000324437:0.000280073:0.60206:0.24096:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515617 ES:SE:LP:AF:ID  0.000250044:0.00017387:0.823909:0.515617:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706739 ES:SE:LP:AF:ID  0.000154885:0.000203853:0.346787:0.706739:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761285 ES:SE:LP:AF:ID  -5.73843e-06:0.000166373:0.0132283:0.761285:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265361 ES:SE:LP:AF:ID  -6.13891e-05:0.000185861:0.130768:0.265361:rs12124819
1   798400  rs10900604  A   G   .   PASS    AF=0.206583 ES:SE:LP:AF:ID  0.00011195:0.000177493:0.275724:0.206583:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206412 ES:SE:LP:AF:ID  0.000114451:0.00017757:0.283997:0.206412:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772615 ES:SE:LP:AF:ID  -4.58402e-05:0.000168918:0.102373:0.772615:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772842 ES:SE:LP:AF:ID  -4.06721e-05:0.000169203:0.091515:0.772842:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340376 ES:SE:LP:AF:ID  -0.000133206:0.000238431:0.236572:0.340376:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697202 ES:SE:LP:AF:ID  3.72017e-05:0.000159501:0.0861861:0.697202:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705361 ES:SE:LP:AF:ID  -0.000119393:0.00015662:0.346787:0.705361:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705405 ES:SE:LP:AF:ID  -0.000118799:0.000156615:0.346787:0.705405:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705591 ES:SE:LP:AF:ID  -0.000115895:0.000156622:0.337242:0.705591:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.70562  ES:SE:LP:AF:ID  -0.000117268:0.000156638:0.346787:0.70562:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730091 ES:SE:LP:AF:ID  -4.01594e-05:0.000160904:0.09691:0.730091:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294413 ES:SE:LP:AF:ID  0.00012074:0.000156631:0.356547:0.294413:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236715 ES:SE:LP:AF:ID  0.000118827:0.000166755:0.318759:0.236715:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236704 ES:SE:LP:AF:ID  0.000113075:0.000166757:0.30103:0.236704:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239764 ES:SE:LP:AF:ID  0.000107146:0.000166223:0.283997:0.239764:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236705 ES:SE:LP:AF:ID  0.000112934:0.000166755:0.30103:0.236705:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212435 ES:SE:LP:AF:ID  3.10128e-05:0.000173322:0.0655015:0.212435:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212331 ES:SE:LP:AF:ID  3.18221e-05:0.000173352:0.0705811:0.212331:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237188 ES:SE:LP:AF:ID  0.000108223:0.000166628:0.283997:0.237188:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.212974 ES:SE:LP:AF:ID  3.00722e-05:0.000173105:0.0655015:0.212974:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212935 ES:SE:LP:AF:ID  3.11386e-05:0.00017314:0.0655015:0.212935:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241177 ES:SE:LP:AF:ID  3.76299e-05:0.000165462:0.0861861:0.241177:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213554 ES:SE:LP:AF:ID  3.35821e-05:0.000172886:0.0705811:0.213554:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.26951  ES:SE:LP:AF:ID  2.73262e-05:0.000159662:0.0655015:0.26951:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213524 ES:SE:LP:AF:ID  3.08161e-05:0.000172908:0.0655015:0.213524:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214596 ES:SE:LP:AF:ID  1.48525e-05:0.000172574:0.0315171:0.214596:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246204 ES:SE:LP:AF:ID  -5.77062e-05:0.00016433:0.136677:0.246204:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270019 ES:SE:LP:AF:ID  1.86738e-05:0.000159775:0.0409586:0.270019:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400161 ES:SE:LP:AF:ID  9.72877e-05:0.000144467:0.30103:0.400161:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237104 ES:SE:LP:AF:ID  -0.000114277:0.000167805:0.30103:0.237104:rs1574243
1   842013  rs7419119   T   G   .   PASS    AF=0.215403 ES:SE:LP:AF:ID  1.09242e-05:0.000172689:0.0222764:0.215403:rs7419119
1   842362  rs28540380  C   T   .   PASS    AF=0.235334 ES:SE:LP:AF:ID  4.92364e-05:0.00017032:0.113509:0.235334:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362584 ES:SE:LP:AF:ID  0.000322896:0.00017934:1.14267:0.362584:rs11516185
1   844300  rs61769713  C   G   .   PASS    AF=0.818766 ES:SE:LP:AF:ID  -9.78696e-05:0.000184308:0.221849:0.818766:rs61769713
1   845283  rs7366404   G   T   .   PASS    AF=0.814453 ES:SE:LP:AF:ID  -8.55515e-05:0.000182684:0.19382:0.814453:rs7366404
1   845635  rs117086422 C   T   .   PASS    AF=0.205421 ES:SE:LP:AF:ID  4.28806e-05:0.000175639:0.091515:0.205421:rs117086422
1   845938  rs57760052  G   A   .   PASS    AF=0.210859 ES:SE:LP:AF:ID  4.96583e-05:0.000173947:0.107905:0.210859:rs57760052
1   846078  rs28612348  C   T   .   PASS    AF=0.196779 ES:SE:LP:AF:ID  4.49078e-05:0.000178327:0.09691:0.196779:rs28612348
1   846338  rs4970334   A   G   .   PASS    AF=0.813783 ES:SE:LP:AF:ID  -7.22193e-05:0.000182528:0.161151:0.813783:rs4970334
1   846398  rs58781670  G   A   .   PASS    AF=0.204446 ES:SE:LP:AF:ID  2.98925e-05:0.000176236:0.0604807:0.204446:rs58781670
1   846489  rs4970333   T   C   .   PASS    AF=0.813876 ES:SE:LP:AF:ID  -6.76323e-05:0.000182654:0.148742:0.813876:rs4970333
1   846808  rs4475691   C   T   .   PASS    AF=0.198373 ES:SE:LP:AF:ID  6.02116e-05:0.000177821:0.136677:0.198373:rs4475691