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/abd53c8f-1b4b-43ed-8ce6-0ac835200e7b/call-ldsc/inputs/-261044543/ieu-b-4810.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4810/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Dec 17 19:13:22 2021
Reading summary statistics from /data/cromwell-executions/qc/abd53c8f-1b4b-43ed-8ce6-0ac835200e7b/call-ldsc/inputs/-261044543/ieu-b-4810.vcf.gz ...
Read summary statistics for 12320809 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: 0.0333 (0.0037)
Lambda GC: 1.099
Mean Chi^2: 1.1587
Intercept: 1.0218 (0.0079)
Ratio: 0.1376 (0.0497)
Analysis finished at Fri Dec 17 19:15:38 2021
Total time elapsed: 2.0m:15.61s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9503,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 12321854,
    "n_clumped_hits": 34,
    "n_p_sig": 2458,
    "n_mono": 0,
    "n_ns": 1293895,
    "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": 1423035,
    "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": 1220578,
    "ldsc_nsnp_merge_regression_ld": 1220578,
    "ldsc_observed_scale_h2_beta": 0.0333,
    "ldsc_observed_scale_h2_se": 0.0037,
    "ldsc_intercept_beta": 1.0218,
    "ldsc_intercept_se": 0.0079,
    "ldsc_lambda_gc": 1.099,
    "ldsc_mean_chisq": 1.1587,
    "ldsc_ratio": 0.1374
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
n_p_sig TRUE
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 675 0.9999452 3 58 0 12276211 0 NA NA 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 NA NA
character ALT 0 1.0000000 1 662 0 71704 0 NA NA NA NA NA NA NA NA NA NA
logical N 12321854 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 8.757494e+00 5.885390e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.871199e+07 5.622120e+07 302.0000000 3.252510e+07 6.928041e+07 1.144490e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.240000e-05 3.499600e-03 -0.0555959 -1.089000e-03 -1.090000e-05 1.058000e-03 1.286150e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.511600e-03 2.407500e-03 0.0007289 8.805000e-04 1.412700e-03 3.259100e-03 3.852100e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.889565e-01 2.923501e-01 0.0000000 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 4.889568e-01 2.923258e-01 0.0000000 2.327097e-01 4.857512e-01 7.422028e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.594017e-01 3.020360e-01 0.0009020 1.660200e-02 1.145685e-01 4.379318e-01 9.990770e-01 ▇▂▁▁▁
numeric AF_reference 1423035 0.8845113 NA NA NA NA NA NA NA 2.132163e-01 2.513550e-01 0.0000000 1.218050e-02 1.056310e-01 3.376600e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 10177 rs1264289758 AC A -0.0006678 0.0011275 0.5500004 0.5536297 0.601714 NA NA
1 10352 rs1557426776 TA T -0.0015840 0.0011601 0.1700000 0.1721241 0.606580 NA NA
1 11008 rs575272151 C G 0.0013588 0.0019372 0.4799997 0.4830396 0.085916 0.0880591 NA
1 11012 rs544419019 C G 0.0013588 0.0019372 0.4799997 0.4830396 0.085916 0.0880591 NA
1 13110 rs540538026 G A -0.0033317 0.0025687 0.1900002 0.1946187 0.058550 0.0267572 NA
1 13116 rs62635286 T G -0.0015287 0.0015188 0.3100002 0.3141600 0.189260 0.0970447 NA
1 13118 rs200579949 A G -0.0015287 0.0015188 0.3100002 0.3141600 0.189260 0.0970447 NA
1 13273 rs531730856 G C 0.0019937 0.0017778 0.2599998 0.2620988 0.133918 0.0950479 NA
1 14464 rs546169444 A T -0.0010862 0.0016152 0.5000000 0.5012939 0.157218 0.0958466 NA
1 14599 rs531646671 T A -0.0010361 0.0014750 0.4799997 0.4823815 0.191181 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G -0.0008357 0.0008748 0.3400001 0.3393814 0.751167 0.643179 NA
23 154901964 rs697726 G A -0.0026750 0.0009252 0.0038000 0.0038363 0.346592 0.117616 NA
23 154902105 rs696316 G T -0.0008204 0.0008747 0.3500000 0.3482355 0.751099 0.636026 NA
23 154902889 rs697725 A T -0.0008000 0.0008744 0.3599996 0.3602620 0.750742 0.584106 NA
23 154903118 rs479770 G A -0.0008384 0.0008749 0.3400001 0.3379278 0.751221 0.643444 NA
23 154903224 rs480725 A T -0.0008379 0.0008749 0.3400001 0.3381871 0.751225 0.643444 NA
23 154903937 rs674707 G A -0.0008362 0.0008749 0.3400001 0.3392353 0.751239 0.643444 NA
23 154909055 rs473529 C G 0.0004458 0.0008245 0.5900000 0.5887073 0.305764 0.463046 NA
23 154918266 rs642043 C T 0.0004310 0.0008271 0.5999997 0.6023567 0.303587 0.478675 NA
23 154927581 rs644138 G A 0.0004279 0.0008273 0.6100002 0.6050015 0.303437 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601714 ES:SE:LP:AF:SI:ID   -0.000667846:0.00112749:0.259637:0.601714:0.466089:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.60658  ES:SE:LP:AF:SI:ID   -0.00158404:0.00116012:0.769551:0.60658:0.44449:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.085916 ES:SE:LP:AF:SI:ID   0.00135883:0.00193725:0.318759:0.085916:0.486664:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.085916 ES:SE:LP:AF:SI:ID   0.00135883:0.00193725:0.318759:0.085916:0.486664:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.05855  ES:SE:LP:AF:SI:ID   -0.00333171:0.00256871:0.721246:0.05855:0.39209:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.18926  ES:SE:LP:AF:SI:ID   -0.00152873:0.00151881:0.508638:0.18926:0.404681:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.18926  ES:SE:LP:AF:SI:ID   -0.00152873:0.00151881:0.508638:0.18926:0.404681:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.133918 ES:SE:LP:AF:SI:ID   0.00199367:0.00177777:0.585027:0.133918:0.390731:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157218 ES:SE:LP:AF:SI:ID   -0.00108617:0.00161523:0.30103:0.157218:0.410824:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.191181 ES:SE:LP:AF:SI:ID   -0.00103614:0.00147498:0.318759:0.191181:0.424479:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.191181 ES:SE:LP:AF:SI:ID   -0.00103614:0.00147498:0.318759:0.191181:0.424479:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473705 ES:SE:LP:AF:SI:ID   -0.000579789:0.00114247:0.21467:0.473705:0.437191:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.044962 ES:SE:LP:AF:SI:ID   0.0042318:0.00281608:0.886057:0.044962:0.420325:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.7413   ES:SE:LP:AF:SI:ID   5.5111e-05:0.00132097:0.0132283:0.7413:0.425958:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275344 ES:SE:LP:AF:SI:ID   0.00215677:0.00135696:0.958607:0.275344:0.388846:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.581084 ES:SE:LP:AF:SI:ID   0.000753371:0.00111744:0.30103:0.581084:0.465698:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.9566   ES:SE:LP:AF:SI:ID   0.000138341:0.00318349:0.0132283:0.9566:0.339465:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910149 ES:SE:LP:AF:SI:ID   0.000221488:0.0021074:0.0362122:0.910149:0.391908:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062823 ES:SE:LP:AF:SI:ID   0.00425875:0.00240809:1.11351:0.062823:0.418452:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.623136 ES:SE:LP:AF:SI:ID   0.000297831:0.00134283:0.0861861:0.623136:0.338912:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.093088 ES:SE:LP:AF:SI:ID   0.00024256:0.00206084:0.0409586:0.093088:0.397311:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213428 ES:SE:LP:AF:SI:ID   -0.00194686:0.00143521:0.769551:0.213428:0.412646:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154444 ES:SE:LP:AF:SI:ID   -0.000556534:0.0016122:0.136677:0.154444:0.420773:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.40114  ES:SE:LP:AF:SI:ID   0.000745901:0.00132685:0.244125:0.40114:0.337096:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.414857 ES:SE:LP:AF:SI:ID   0.000996766:0.00105136:0.468521:0.414857:0.532876:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417185 ES:SE:LP:AF:SI:ID   0.00114818:0.00121381:0.468521:0.417185:0.39825:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253905 ES:SE:LP:AF:SI:ID   -0.000577053:0.00136589:0.173925:0.253905:0.404049:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090251 ES:SE:LP:AF:SI:ID   -0.00132215:0.00207723:0.283997:0.090251:0.402912:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.089004 ES:SE:LP:AF:SI:ID   -0.00138392:0.00208642:0.29243:0.089004:0.404541:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.081187 ES:SE:LP:AF:SI:ID   -0.000750999:0.00216304:0.136677:0.081187:0.408796:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438336 ES:SE:LP:AF:SI:ID   -0.00108784:0.00115514:0.455932:0.438336:0.435397:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.3824   ES:SE:LP:AF:SI:ID   -0.000565231:0.0012399:0.187087:0.3824:0.39221:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.159206 ES:SE:LP:AF:SI:ID   -0.00103136:0.00157912:0.29243:0.159206:0.429054:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.684153 ES:SE:LP:AF:SI:ID   -0.00206014:0.00122887:1.02687:0.684153:0.43843:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079837 ES:SE:LP:AF:SI:ID   -0.00110889:0.00218766:0.21467:0.079837:0.405239:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.070872 ES:SE:LP:AF:SI:ID   0.00374669:0.00222078:1.03621:0.070872:0.439754:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.033023 ES:SE:LP:AF:SI:ID   0.00949641:0.00334478:2.34679:0.033023:0.39852:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073984 ES:SE:LP:AF:SI:ID   0.00273063:0.0021849:0.677781:0.073984:0.436196:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.750816 ES:SE:LP:AF:SI:ID   -0.000200046:0.00139214:0.05061:0.750816:0.393859:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.033985 ES:SE:LP:AF:SI:ID   -0.00336027:0.00321126:0.522879:0.033985:0.425973:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.033985 ES:SE:LP:AF:SI:ID   -0.00336027:0.00321126:0.522879:0.033985:0.425973:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.077258 ES:SE:LP:AF:SI:ID   -0.00137184:0.00223239:0.267606:0.077258:0.401276:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.07739  ES:SE:LP:AF:SI:ID   0.00237161:0.00215922:0.568636:0.07739:0.430178:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.077063 ES:SE:LP:AF:SI:ID   -0.00130437:0.00223309:0.251812:0.077063:0.40201:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.077063 ES:SE:LP:AF:SI:ID   -0.00130437:0.00223309:0.251812:0.077063:0.40201:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041422 ES:SE:LP:AF:SI:ID   -0.000102485:0.00312802:0.0132283:0.041422:0.370765:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.061105 ES:SE:LP:AF:SI:ID   0.00331182:0.00236268:0.79588:0.061105:0.444727:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075385 ES:SE:LP:AF:SI:ID   0.00179709:0.00218581:0.387216:0.075385:0.429704:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075416 ES:SE:LP:AF:SI:ID   0.00178193:0.00218527:0.387216:0.075416:0.429781:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352644 ES:SE:LP:AF:SI:ID   -0.000735094:0.00125022:0.251812:0.352644:0.399395:rs201754587