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-3241/UKB-b-3241_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3241/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:23 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3241/UKB-b-3241_data.vcf.gz ...
Read summary statistics for 3106819 SNPs.
Dropped 427 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, 770827 SNPs remain.
After merging with regression SNP LD, 770827 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.001 (0.0012)
Lambda GC: 1.0203
Mean Chi^2: 1.0183
Intercept: 1.0084 (0.0099)
Ratio: 0.4611 (0.5422)
Analysis finished at Thu Oct 17 14:44:04 2019
Total time elapsed: 40.1s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8252,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -6.4041e-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": 24818,
    "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": 770827,
    "ldsc_nsnp_merge_regression_ld": 770827,
    "ldsc_observed_scale_h2_beta": 0.001,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0084,
    "ldsc_intercept_se": 0.0099,
    "ldsc_lambda_gc": 1.0203,
    "ldsc_mean_chisq": 1.0183,
    "ldsc_ratio": 0.459
}
 

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 3106395 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 3106819 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 8.664737e+00 5.772514e+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 7.854851e+07 5.670614e+07 828.0000000 3.158997e+07 6.894266e+07 1.147946e+08 2.492013e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.000000e-07 1.494000e-04 -0.0008002 -1.009000e-04 -3.000000e-07 9.960000e-05 7.614000e-04 ▁▂▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.477000e-04 1.210000e-05 0.0001297 1.371000e-04 1.440000e-04 1.562000e-04 3.136000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.965048e-01 2.896488e-01 0.0000010 2.500000e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.965057e-01 2.896233e-01 0.0000010 2.451702e-01 4.944888e-01 7.472476e-01 9.999992e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.308485e-01 1.797283e-01 0.1814420 2.730560e-01 3.984770e-01 5.708360e-01 8.185580e-01 ▇▆▅▃▃
numeric AF_reference 24818 0.9920118 NA NA NA NA NA NA NA 4.153257e-01 1.944610e-01 0.0000000 2.585860e-01 3.903750e-01 5.581070e-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 -0.0000068 0.0002387 0.9800000 0.9771069 0.623778 0.7821490 NA
1 54676 rs2462492 C T 0.0001180 0.0002365 0.6200004 0.6178121 0.400403 NA NA
1 91536 rs6702460 G T -0.0000542 0.0002329 0.8200001 0.8160087 0.456860 0.4207270 NA
1 534192 rs6680723 C T 0.0003846 0.0002660 0.1499999 0.1482354 0.240946 NA NA
1 706368 rs55727773 A G -0.0000205 0.0001651 0.9000000 0.9012075 0.515668 0.2751600 NA
1 763394 rs369924889 G A -0.0003046 0.0001936 0.1199999 0.1156497 0.706759 0.6176120 NA
1 768253 rs2977608 A C -0.0002452 0.0001580 0.1199999 0.1207208 0.761336 0.4894170 NA
1 776546 rs12124819 A G 0.0001317 0.0001765 0.4600002 0.4554373 0.265365 0.0756789 NA
1 798400 rs10900604 A G 0.0000792 0.0001686 0.6400000 0.6385074 0.206550 0.4105430 NA
1 798959 rs11240777 G A 0.0000788 0.0001686 0.6400000 0.6402601 0.206379 0.4099440 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C 0.0001996 0.0001554 0.2000000 0.1989677 0.713667 0.6369810 NA
22 51181919 rs9616825 G C 0.0001536 0.0001546 0.3200000 0.3204066 0.695497 0.6194090 NA
22 51182485 rs6009961 A G 0.0001916 0.0001559 0.2200002 0.2190414 0.715512 0.6383790 NA
22 51186143 rs2879914 T C 0.0001218 0.0001445 0.4000000 0.3993670 0.381822 0.2733630 NA
22 51186228 rs3865766 C T 0.0001207 0.0001409 0.3900004 0.3915615 0.451063 0.4532750 NA
22 51197266 rs61290853 A G 0.0001049 0.0001455 0.4700002 0.4709720 0.386347 0.4229230 NA
22 51198027 rs34939255 A G 0.0000133 0.0001647 0.9400001 0.9354167 0.254571 0.0984425 NA
22 51211106 rs9628250 T C 0.0000113 0.0001633 0.9500000 0.9450083 0.271568 0.1671330 NA
22 51212875 rs2238837 A C 0.0000340 0.0001551 0.8300000 0.8266197 0.331450 0.3724040 NA
22 51237063 rs3896457 T C 0.0000410 0.0001588 0.8000000 0.7963365 0.297975 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623778 ES:SE:LP:AF:ID  -6.84965e-06:0.000238695:0.00877392:0.623778:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400403 ES:SE:LP:AF:ID  0.000118017:0.000236529:0.207608:0.400403:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.45686  ES:SE:LP:AF:ID  -5.41806e-05:0.000232853:0.0861861:0.45686:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240946 ES:SE:LP:AF:ID  0.000384562:0.000265987:0.823909:0.240946:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515668 ES:SE:LP:AF:ID  -2.04991e-05:0.000165134:0.0457575:0.515668:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706759 ES:SE:LP:AF:ID  -0.000304589:0.000193599:0.920819:0.706759:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761336 ES:SE:LP:AF:ID  -0.000245213:0.000158023:0.920819:0.761336:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265365 ES:SE:LP:AF:ID  0.000131734:0.000176497:0.337242:0.265365:rs12124819
1   798400  rs10900604  A   G   .   PASS    AF=0.20655  ES:SE:LP:AF:ID  7.91896e-05:0.000168565:0.19382:0.20655:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206379 ES:SE:LP:AF:ID  7.881e-05:0.000168637:0.19382:0.206379:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772663 ES:SE:LP:AF:ID  -5.47206e-05:0.000160421:0.136677:0.772663:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772891 ES:SE:LP:AF:ID  -5.6694e-05:0.000160689:0.142668:0.772891:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340388 ES:SE:LP:AF:ID  0.000121545:0.000226419:0.229148:0.340388:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697219 ES:SE:LP:AF:ID  -1.01419e-05:0.000151477:0.0222764:0.697219:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705359 ES:SE:LP:AF:ID  -2.64541e-05:0.000148737:0.0655015:0.705359:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705405 ES:SE:LP:AF:ID  -2.50608e-05:0.000148732:0.0604807:0.705405:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.70559  ES:SE:LP:AF:ID  -2.72403e-05:0.000148738:0.0705811:0.70559:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705618 ES:SE:LP:AF:ID  -2.76461e-05:0.000148754:0.0705811:0.705618:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730085 ES:SE:LP:AF:ID  -8.65895e-05:0.000152809:0.244125:0.730085:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294415 ES:SE:LP:AF:ID  2.60354e-05:0.000148747:0.0655015:0.294415:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236736 ES:SE:LP:AF:ID  -5.83974e-05:0.000158358:0.148742:0.236736:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236725 ES:SE:LP:AF:ID  -5.81384e-05:0.000158359:0.148742:0.236725:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239782 ES:SE:LP:AF:ID  -6.84705e-05:0.00015785:0.180456:0.239782:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236726 ES:SE:LP:AF:ID  -6.03774e-05:0.000158358:0.154902:0.236726:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212461 ES:SE:LP:AF:ID  -4.31385e-06:0.00016459:0.00877392:0.212461:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212357 ES:SE:LP:AF:ID  -1.21074e-06:0.000164619:0.00436481:0.212357:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237211 ES:SE:LP:AF:ID  -5.01464e-05:0.000158237:0.124939:0.237211:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.213002 ES:SE:LP:AF:ID  4.6969e-06:0.000164386:0.00877392:0.213002:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212964 ES:SE:LP:AF:ID  5.27299e-06:0.00016442:0.0132283:0.212964:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241194 ES:SE:LP:AF:ID  3.94167e-05:0.000157133:0.09691:0.241194:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213586 ES:SE:LP:AF:ID  3.34652e-05:0.000164177:0.0757207:0.213586:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269531 ES:SE:LP:AF:ID  -3.48693e-06:0.000151621:0.00877392:0.269531:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213555 ES:SE:LP:AF:ID  4.17472e-05:0.000164197:0.09691:0.213555:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.21463  ES:SE:LP:AF:ID  5.46386e-05:0.00016388:0.130768:0.21463:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246231 ES:SE:LP:AF:ID  8.05267e-05:0.000156053:0.21467:0.246231:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270034 ES:SE:LP:AF:ID  -1.4948e-05:0.000151728:0.0362122:0.270034:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400165 ES:SE:LP:AF:ID  -8.08814e-05:0.000137198:0.251812:0.400165:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237129 ES:SE:LP:AF:ID  9.28893e-06:0.000159355:0.0222764:0.237129:rs1574243
1   842013  rs7419119   T   G   .   PASS    AF=0.215436 ES:SE:LP:AF:ID  5.96962e-05:0.000163989:0.142668:0.215436:rs7419119
1   842362  rs28540380  C   T   .   PASS    AF=0.235373 ES:SE:LP:AF:ID  3.35568e-05:0.000161736:0.0757207:0.235373:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362584 ES:SE:LP:AF:ID  -9.48376e-05:0.000170305:0.236572:0.362584:rs11516185
1   845283  rs7366404   G   T   .   PASS    AF=0.814512 ES:SE:LP:AF:ID  0.000118481:0.000173496:0.309804:0.814512:rs7366404
1   845635  rs117086422 C   T   .   PASS    AF=0.205435 ES:SE:LP:AF:ID  0.000209698:0.000166785:0.677781:0.205435:rs117086422
1   845938  rs57760052  G   A   .   PASS    AF=0.210874 ES:SE:LP:AF:ID  0.000215069:0.000165181:0.721246:0.210874:rs57760052
1   846078  rs28612348  C   T   .   PASS    AF=0.196794 ES:SE:LP:AF:ID  0.000147403:0.000169344:0.420216:0.196794:rs28612348
1   846338  rs4970334   A   G   .   PASS    AF=0.813844 ES:SE:LP:AF:ID  0.000125242:0.000173349:0.327902:0.813844:rs4970334
1   846398  rs58781670  G   A   .   PASS    AF=0.204461 ES:SE:LP:AF:ID  0.000247528:0.000167354:0.853872:0.204461:rs58781670
1   846489  rs4970333   T   C   .   PASS    AF=0.813936 ES:SE:LP:AF:ID  0.000118262:0.000173468:0.30103:0.813936:rs4970333
1   846808  rs4475691   C   T   .   PASS    AF=0.198388 ES:SE:LP:AF:ID  0.000149105:0.000168863:0.420216:0.198388:rs4475691
1   846864  rs950122    G   C   .   PASS    AF=0.198114 ES:SE:LP:AF:ID  0.000119449:0.000168767:0.318759:0.198114:rs950122