Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_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 /data/cromwell-executions/qc/856cd9a5-6e8d-4d98-a910-8ca3be84f6a5/call-ldsc/inputs/562856289/ieu-b-69.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-69/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Sat Oct 24 02:28:49 2020
Reading summary statistics from /data/cromwell-executions/qc/856cd9a5-6e8d-4d98-a910-8ca3be84f6a5/call-ldsc/inputs/562856289/ieu-b-69.vcf.gz ...
Read summary statistics for 12320830 SNPs.
Dropped 206220 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1220578 SNPs remain.
After merging with regression SNP LD, 1220578 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0031 (0.001)
Lambda GC: 1.0524
Mean Chi^2: 1.0554
Intercept: 1.0271 (0.0063)
Ratio: 0.4882 (0.1142)
Analysis finished at Sat Oct 24 02:30:46 2020
Total time elapsed: 1.0m:57.41s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9503,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -0.0004,
    "n": 462918,
    "n_snps": 12321875,
    "n_clumped_hits": 3,
    "n_p_sig": 44,
    "n_mono": 0,
    "n_ns": 1293897,
    "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": 1423040,
    "n_est": 453783.1795,
    "ratio_se_n": 0.9901,
    "mean_diff": 0.0003,
    "ratio_diff": 491.7691,
    "sd_y_est1": 6.9266,
    "sd_y_est2": 6.8579,
    "r2_sum1": 0.0068,
    "r2_sum2": 0.0001,
    "r2_sum3": 0.0001,
    "r2_sum4": 0.0001,
    "ldsc_nsnp_merge_refpanel_ld": 1220578,
    "ldsc_nsnp_merge_regression_ld": 1220578,
    "ldsc_observed_scale_h2_beta": 0.0031,
    "ldsc_observed_scale_h2_se": 0.001,
    "ldsc_intercept_beta": 1.0271,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0524,
    "ldsc_mean_chisq": 1.0554,
    "ldsc_ratio": 0.4892
}

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 675 0.9999452 3 58 0 12276232 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 17566 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 71704 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.757492e+00 5.885387e+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 7.871202e+07 5.622121e+07 3.02000e+02 3.252510e+07 6.928045e+07 1.144492e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.579000e-04 6.583790e-02 -8.54186e-01 -2.022380e-02 -2.101000e-04 1.942550e-02 1.031360e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 4.710660e-02 4.521050e-02 1.16975e-02 1.649840e-02 2.649140e-02 6.113090e-02 7.197060e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.798240e-01 2.941117e-01 0.00000e+00 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.926279e-01 2.908792e-01 0.00000e+00 2.388543e-01 4.906620e-01 7.444869e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.594005e-01 3.020419e-01 9.98000e-04 1.660000e-02 1.145680e-01 4.379330e-01 9.990010e-01 ▇▂▁▁▁
numeric AF_reference 1423040 0.8845111 NA NA NA NA NA 2.132160e-01 2.513550e-01 0.00000e+00 1.218050e-02 1.056310e-01 3.376600e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 4.629180e+05 0.000000e+00 4.62918e+05 4.629180e+05 4.629180e+05 4.629180e+05 4.629180e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10177 rs1264289758 AC A -0.0544556 0.0211765 0.0109999 0.0101256 0.601092 NA 462918
1 10352 rs1557426776 TA T -0.0202888 0.0218019 0.3100002 0.3520617 0.606764 NA 462918
1 11008 rs575272151 C G -0.0571311 0.0362502 0.1100001 0.1150208 0.086225 0.0880591 462918
1 11012 rs544419019 C G -0.0571311 0.0362502 0.1100001 0.1150208 0.086225 0.0880591 462918
1 13110 rs540538026 G A -0.0221827 0.0482193 0.6800001 0.6454891 0.058685 0.0267572 462918
1 13116 rs62635286 T G 0.0392616 0.0285349 0.1400000 0.1688479 0.189177 0.0970447 462918
1 13118 rs200579949 A G 0.0392616 0.0285349 0.1400000 0.1688479 0.189177 0.0970447 462918
1 13273 rs531730856 G C -0.0067195 0.0333976 0.8700001 0.8405442 0.134135 0.0950479 462918
1 14464 rs546169444 A T -0.0334549 0.0304135 0.3100002 0.2713314 0.156897 0.0958466 462918
1 14599 rs531646671 T A 0.0462138 0.0276762 0.0959997 0.0949584 0.191556 0.1475640 462918
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G -0.0343440 0.0136093 0.0077999 0.0116170 0.751936 0.643179 462918
23 154901964 rs697726 G A -0.0268850 0.0143523 0.0599998 0.0610382 0.347899 0.117616 462918
23 154902105 rs696316 G T -0.0343258 0.0136084 0.0077999 0.0116558 0.751891 0.636026 462918
23 154902889 rs697725 A T -0.0341137 0.0136040 0.0083000 0.0121546 0.751565 0.584106 462918
23 154903118 rs479770 G A -0.0345594 0.0136107 0.0074000 0.0111127 0.751980 0.643444 462918
23 154903224 rs480725 A T -0.0345593 0.0136107 0.0074000 0.0111129 0.751983 0.643444 462918
23 154903937 rs674707 G A -0.0345762 0.0136110 0.0074000 0.0110753 0.751993 0.643444 462918
23 154909055 rs473529 C G 0.0222583 0.0128128 0.0510000 0.0823532 0.304737 0.463046 462918
23 154918266 rs642043 C T 0.0214103 0.0128541 0.0610000 0.0957852 0.302582 0.478675 462918
23 154927581 rs644138 G A 0.0214964 0.0128564 0.0599998 0.0945167 0.302456 0.463576 462918

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601092 ES:SE:LP:AF:SS:NC:ID    -0.0544556:0.0211765:1.95861:0.601092:462918:10154:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.606764 ES:SE:LP:AF:SS:NC:ID    -0.0202888:0.0218019:0.508638:0.606764:462918:10154:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086225 ES:SE:LP:AF:SS:NC:ID    -0.0571311:0.0362502:0.958607:0.086225:462918:10154:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086225 ES:SE:LP:AF:SS:NC:ID    -0.0571311:0.0362502:0.958607:0.086225:462918:10154:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058685 ES:SE:LP:AF:SS:NC:ID    -0.0221827:0.0482193:0.167491:0.058685:462918:10154:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189177 ES:SE:LP:AF:SS:NC:ID    0.0392616:0.0285349:0.853872:0.189177:462918:10154:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189177 ES:SE:LP:AF:SS:NC:ID    0.0392616:0.0285349:0.853872:0.189177:462918:10154:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.134135 ES:SE:LP:AF:SS:NC:ID    -0.00671951:0.0333976:0.0604807:0.134135:462918:10154:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.156897 ES:SE:LP:AF:SS:NC:ID    -0.0334549:0.0304135:0.508638:0.156897:462918:10154:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191556 ES:SE:LP:AF:SS:NC:ID    0.0462138:0.0276762:1.01773:0.191556:462918:10154:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191556 ES:SE:LP:AF:SS:NC:ID    0.0462138:0.0276762:1.01773:0.191556:462918:10154:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473818 ES:SE:LP:AF:SS:NC:ID    0.0144811:0.0214717:0.200659:0.473818:462918:10154:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.045079 ES:SE:LP:AF:SS:NC:ID    -0.0672166:0.0527845:0.568636:0.045079:462918:10154:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741354 ES:SE:LP:AF:SS:NC:ID    0.0355785:0.0248264:0.886057:0.741354:462918:10154:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275123 ES:SE:LP:AF:SS:NC:ID    0.0189251:0.0254697:0.318759:0.275123:462918:10154:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581159 ES:SE:LP:AF:SS:NC:ID    0.0199688:0.0209886:0.508638:0.581159:462918:10154:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956571 ES:SE:LP:AF:SS:NC:ID    0.0282366:0.0597945:0.148742:0.956571:462918:10154:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910221 ES:SE:LP:AF:SS:NC:ID    -0.0106034:0.0396432:0.0809219:0.910221:462918:10154:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062712 ES:SE:LP:AF:SS:NC:ID    -0.0484114:0.0452519:0.619789:0.062712:462918:10154:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623767 ES:SE:LP:AF:SS:NC:ID    -0.0140799:0.0251883:0.30103:0.623767:462918:10154:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092954 ES:SE:LP:AF:SS:NC:ID    -0.0405436:0.0387755:0.552842:0.092954:462918:10154:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.21326  ES:SE:LP:AF:SS:NC:ID    -0.0190214:0.0269534:0.309804:0.21326:462918:10154:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154391 ES:SE:LP:AF:SS:NC:ID    0.0212653:0.0302809:0.327902:0.154391:462918:10154:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400395 ES:SE:LP:AF:SS:NC:ID    0.0295479:0.024954:0.721246:0.400395:462918:10154:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414731 ES:SE:LP:AF:SS:NC:ID    -0.0425065:0.0197372:1.69897:0.414731:462918:10154:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.41737  ES:SE:LP:AF:SS:NC:ID    0.0144357:0.0227894:0.376751:0.41737:462918:10154:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253776 ES:SE:LP:AF:SS:NC:ID    -0.0310878:0.0256407:0.60206:0.253776:462918:10154:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.089998 ES:SE:LP:AF:SS:NC:ID    -0.0154393:0.039082:0.130768:0.089998:462918:10154:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.088788 ES:SE:LP:AF:SS:NC:ID    -0.0447783:0.0392418:0.552842:0.088788:462918:10154:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.080983 ES:SE:LP:AF:SS:NC:ID    -0.0313277:0.0406985:0.30103:0.080983:462918:10154:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438272 ES:SE:LP:AF:SS:NC:ID    0.0222327:0.0216555:0.69897:0.438272:462918:10154:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382184 ES:SE:LP:AF:SS:NC:ID    -0.00547324:0.0232819:0.00877392:0.382184:462918:10154:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158758 ES:SE:LP:AF:SS:NC:ID    -0.0407963:0.0296555:0.677781:0.158758:462918:10154:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.684027 ES:SE:LP:AF:SS:NC:ID    0.0466093:0.02309:1.50864:0.684027:462918:10154:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079579 ES:SE:LP:AF:SS:NC:ID    -0.0284222:0.0412001:0.259637:0.079579:462918:10154:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070781 ES:SE:LP:AF:SS:NC:ID    0.0629455:0.0417172:0.886057:0.070781:462918:10154:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032919 ES:SE:LP:AF:SS:NC:ID    0.0488738:0.0631073:0.431798:0.032919:462918:10154:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073875 ES:SE:LP:AF:SS:NC:ID    0.0530031:0.0410633:0.721246:0.073875:462918:10154:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751221 ES:SE:LP:AF:SS:NC:ID    0.0395457:0.0261555:0.958607:0.751221:462918:10154:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034093 ES:SE:LP:AF:SS:NC:ID    -0.0788813:0.0599633:0.920819:0.034093:462918:10154:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034093 ES:SE:LP:AF:SS:NC:ID    -0.0788813:0.0599633:0.920819:0.034093:462918:10154:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077135 ES:SE:LP:AF:SS:NC:ID    -0.0668283:0.0419852:0.920819:0.077135:462918:10154:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077503 ES:SE:LP:AF:SS:NC:ID    -0.0164139:0.0404797:0.207608:0.077503:462918:10154:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.07694  ES:SE:LP:AF:SS:NC:ID    -0.0660811:0.0419954:0.920819:0.07694:462918:10154:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.07694  ES:SE:LP:AF:SS:NC:ID    -0.0660811:0.0419954:0.920819:0.07694:462918:10154:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041463 ES:SE:LP:AF:SS:NC:ID    0.0559798:0.0585551:0.481486:0.041463:462918:10154:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.060944 ES:SE:LP:AF:SS:NC:ID    0.0410711:0.0444624:0.443698:0.060944:462918:10154:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075448 ES:SE:LP:AF:SS:NC:ID    -0.0233536:0.0410025:0.29243:0.075448:462918:10154:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075475 ES:SE:LP:AF:SS:NC:ID    -0.0233635:0.0409934:0.29243:0.075475:462918:10154:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352797 ES:SE:LP:AF:SS:NC:ID    0.0134847:0.0234536:0.236572:0.352797:462918:10154:rs201754587