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/dev/ukb-d-import/processed/ukb-d-22630_0/ukb-d-22630_0.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22630_0/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 16:50:30 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22630_0/ukb-d-22630_0.vcf.gz ...
Read summary statistics for 10231690 SNPs.
Dropped 8014 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1279545 SNPs remain.
After merging with regression SNP LD, 1279545 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0145 (0.0169)
Lambda GC: 1.0064
Mean Chi^2: 1.0042
Intercept: 0.9967 (0.006)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:52:12 2019
Total time elapsed: 1.0m:41.5s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9427,
    "inflation_factor": 1.0095,
    "mean_EFFECT": -9.4224e-06,
    "n": 25697,
    "n_snps": 10231690,
    "n_clumped_hits": 1,
    "n_p_sig": 3,
    "n_mono": 0,
    "n_ns": 1096764,
    "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": 201480,
    "n_est": 25784.3885,
    "ratio_se_n": 1.0017,
    "mean_diff": -0,
    "ratio_diff": 13.688,
    "sd_y_est1": 0.2531,
    "sd_y_est2": 0.2535,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0012,
    "r2_sum3": 0.0012,
    "r2_sum4": 0.0012,
    "ldsc_nsnp_merge_refpanel_ld": 1279545,
    "ldsc_nsnp_merge_regression_ld": 1279545,
    "ldsc_observed_scale_h2_beta": 0.0145,
    "ldsc_observed_scale_h2_se": 0.0169,
    "ldsc_intercept_beta": 0.9967,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0064,
    "ldsc_mean_chisq": 1.0042,
    "ldsc_ratio": -0.7857
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 10224237 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 48930 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30443 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.079055e+00 6.178286e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.876843e+07 5.606242e+07 3.02000e+02 3.252290e+07 6.968552e+07 1.147246e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -9.400000e-06 5.687000e-03 -5.38219e-02 -2.572400e-03 -2.490000e-05 2.493200e-03 6.680850e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 4.800600e-03 3.050200e-03 1.78900e-03 2.471100e-03 3.414800e-03 6.254400e-03 1.724810e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.987625e-01 2.884870e-01 0.00000e+00 2.487797e-01 4.979813e-01 7.488244e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.987563e-01 2.884907e-01 0.00000e+00 2.487696e-01 4.979752e-01 7.488216e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.493164e-01 2.628784e-01 7.11850e-03 3.472340e-02 1.416910e-01 3.983960e-01 9.928800e-01 ▇▂▂▁▁
numeric AF_reference 201480 0.9803082 NA NA NA NA NA 2.490724e-01 2.537495e-01 0.00000e+00 3.761590e-02 1.581470e-01 3.949680e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.569700e+04 0.000000e+00 2.56970e+04 2.569700e+04 2.569700e+04 2.569700e+04 2.569700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0003832 0.0038866 0.9214590 0.9214579 0.1121430 0.1894970 25697
1 693731 rs12238997 A G -0.0002894 0.0037116 0.9378500 0.9378489 0.1165660 0.1417730 25697
1 707522 rs371890604 G C 0.0008737 0.0041784 0.8343810 0.8343800 0.0975760 0.1293930 25697
1 717587 rs144155419 G A 0.0114403 0.0098473 0.2453409 0.2453293 0.0160183 0.0045926 25697
1 730087 rs148120343 T C -0.0029743 0.0050978 0.5595952 0.5595898 0.0579332 0.0127796 25697
1 731718 rs142557973 T C 0.0001303 0.0035175 0.9704400 0.9704399 0.1229090 0.1543530 25697
1 732032 rs61770163 A C -0.0017390 0.0037475 0.6426270 0.6426236 0.1227700 0.1555510 25697
1 734349 rs141242758 T C -0.0000535 0.0035196 0.9878830 0.9878831 0.1221900 0.1525560 25697
1 749963 rs529266287 T TAA -0.0005224 0.0034550 0.8798250 0.8798233 0.8679320 0.7641770 25697
1 751343 rs28544273 T A 0.0001301 0.0034271 0.9697101 0.9697101 0.1244600 0.2426120 25697
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0007314 0.0039252 0.8521840 0.8521830 0.0569276 0.0309934 25697
23 154923374 rs111332691 T A -0.0009082 0.0043477 0.8345410 0.8345397 0.0445188 0.0116556 25697
23 154925045 rs509981 C T -0.0022464 0.0021072 0.2864099 0.2863996 0.2412010 0.3634440 25697
23 154925895 rs538470 C T -0.0020450 0.0021535 0.3422969 0.3422884 0.2377450 0.3634440 25697
23 154927581 rs644138 G A -0.0021984 0.0019744 0.2655162 0.2655070 0.2986200 0.4635760 25697
23 154929412 rs557132 C T -0.0021969 0.0021082 0.2973850 0.2973753 0.2409870 0.3568210 25697
23 154929637 rs35185538 CT C -0.0025509 0.0021967 0.2455540 0.2455424 0.2268160 0.3011920 25697
23 154929952 rs4012982 CAA C -0.0016008 0.0022192 0.4706987 0.4706934 0.2348550 0.3165560 25697
23 154930230 rs781880 A G -0.0020889 0.0021068 0.3214549 0.3214466 0.2415200 0.3618540 25697
23 154930487 rs781879 T A -0.0006999 0.0073110 0.9237361 0.9237350 0.0189835 0.1263580 25697

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112143 ES:SE:LP:AF:SS:ID   0.000383211:0.00388662:0.035524:0.112143:25697:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116566 ES:SE:LP:AF:SS:ID   -0.00028941:0.00371163:0.0278666:0.116566:25697:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097576 ES:SE:LP:AF:SS:ID   0.000873651:0.0041784:0.0786356:0.097576:25697:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0160183    ES:SE:LP:AF:SS:ID   0.0114403:0.00984731:0.61023:0.0160183:25697:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0579332    ES:SE:LP:AF:SS:ID   -0.00297431:0.00509779:0.252126:0.0579332:25697:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122909 ES:SE:LP:AF:SS:ID   0.000130348:0.00351754:0.0130313:0.122909:25697:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12277  ES:SE:LP:AF:SS:ID   -0.00173898:0.00374753:0.192041:0.12277:25697:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12219  ES:SE:LP:AF:SS:ID   -5.34518e-05:0.0035196:0.00529449:0.12219:25697:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.867932 ES:SE:LP:AF:SS:ID   -0.000522365:0.00345495:0.0556037:0.867932:25697:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.12446  ES:SE:LP:AF:SS:ID   0.000130135:0.00342714:0.0133581:0.12446:25697:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143673 ES:SE:LP:AF:SS:ID   0.00040446:0.00339761:0.0432348:0.143673:25697:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124586 ES:SE:LP:AF:SS:ID   1.6183e-05:0.00342283:0.00164126:0.124586:25697:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869298 ES:SE:LP:AF:SS:ID   0.000650927:0.00333926:0.0729131:0.869298:25697:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873888 ES:SE:LP:AF:SS:ID   -0.000675863:0.00339099:0.0746771:0.873888:25697:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130223 ES:SE:LP:AF:SS:ID   -0.000702433:0.00334953:0.0788886:0.130223:25697:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0356073    ES:SE:LP:AF:SS:ID   -0.0133965:0.00612422:1.54184:0.0356073:25697:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86893  ES:SE:LP:AF:SS:ID   0.000520019:0.00333684:0.0574171:0.86893:25697:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869072 ES:SE:LP:AF:SS:ID   0.000600951:0.00333874:0.0669386:0.869072:25697:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868931 ES:SE:LP:AF:SS:ID   0.000527283:0.00333673:0.0582705:0.868931:25697:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.868988 ES:SE:LP:AF:SS:ID   0.000892748:0.00333018:0.103121:0.868988:25697:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127576 ES:SE:LP:AF:SS:ID   -0.000652034:0.00339623:0.0717302:0.127576:25697:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868487 ES:SE:LP:AF:SS:ID   0.00109067:0.00332152:0.129223:0.868487:25697:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867984 ES:SE:LP:AF:SS:ID   0.00103918:0.0033213:0.122414:0.867984:25697:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868672 ES:SE:LP:AF:SS:ID   0.00105803:0.00332413:0.124782:0.868672:25697:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868677 ES:SE:LP:AF:SS:ID   0.00105989:0.00332432:0.12502:0.868677:25697:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868677 ES:SE:LP:AF:SS:ID   0.00106678:0.00332432:0.125931:0.868677:25697:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86918  ES:SE:LP:AF:SS:ID   0.000825665:0.00333421:0.0945177:0.86918:25697:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.09951  ES:SE:LP:AF:SS:ID   0.000940262:0.00388518:0.0921734:0.09951:25697:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873078 ES:SE:LP:AF:SS:ID   -0.000695464:0.00338092:0.0772616:0.873078:25697:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862503 ES:SE:LP:AF:SS:ID   0.00110549:0.00331727:0.131387:0.862503:25697:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867879 ES:SE:LP:AF:SS:ID   0.000758831:0.00334945:0.0857769:0.867879:25697:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86493  ES:SE:LP:AF:SS:ID   0.000206464:0.00335315:0.0218638:0.86493:25697:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0994497    ES:SE:LP:AF:SS:ID   0.00276759:0.00401721:0.309033:0.0994497:25697:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870274 ES:SE:LP:AF:SS:ID   -0.000422382:0.00339138:0.0453311:0.870274:25697:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870274 ES:SE:LP:AF:SS:ID   -0.000422379:0.00339138:0.0453306:0.870274:25697:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870271 ES:SE:LP:AF:SS:ID   -0.000421301:0.00339139:0.0452092:0.870271:25697:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870593 ES:SE:LP:AF:SS:ID   -0.000265542:0.00339209:0.0279805:0.870593:25697:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12718  ES:SE:LP:AF:SS:ID   -0.000216428:0.00339282:0.0226706:0.12718:25697:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106621 ES:SE:LP:AF:SS:ID   -0.00197807:0.00368823:0.227868:0.106621:25697:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853855 ES:SE:LP:AF:SS:ID   0.0018202:0.00330705:0.23504:0.853855:25697:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838998 ES:SE:LP:AF:SS:ID   0.00151699:0.00327764:0.191458:0.838998:25697:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763662 ES:SE:LP:AF:SS:ID   0.00236698:0.0026366:0.432583:0.763662:25697:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.104137 ES:SE:LP:AF:SS:ID   -0.00281007:0.00364123:0.356275:0.104137:25697:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00725285   ES:SE:LP:AF:SS:ID   0.0128567:0.0138975:0.44987:0.00725285:25697:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.13049  ES:SE:LP:AF:SS:ID   -0.00094648:0.00334646:0.109406:0.13049:25697:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.130167 ES:SE:LP:AF:SS:ID   -0.000983741:0.00334308:0.114322:0.130167:25697:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.10345  ES:SE:LP:AF:SS:ID   -0.00302:0.00366771:0.386913:0.10345:25697:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.0091149    ES:SE:LP:AF:SS:ID   -0.0181852:0.0128295:0.805863:0.0091149:25697:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.0072604    ES:SE:LP:AF:SS:ID   0.0146565:0.0139672:0.531613:0.0072604:25697:rs112563271
1   770886  rs371458725 G   A   .   PASS    AF=0.102438 ES:SE:LP:AF:SS:ID   -0.00306775:0.00369893:0.390505:0.102438:25697:rs371458725