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/38dba6c7-5762-402d-b909-a9fc8ca8f52a/call-ldsc/inputs/-261043453/ieu-b-4955.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4955/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Mar  4 05:46:53 2022
Reading summary statistics from /data/cromwell-executions/qc/38dba6c7-5762-402d-b909-a9fc8ca8f52a/call-ldsc/inputs/-261043453/ieu-b-4955.vcf.gz ...
Read summary statistics for 11077088 SNPs.
Dropped 189183 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, 1217959 SNPs remain.
After merging with regression SNP LD, 1217959 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0064 (0.0012)
Lambda GC: 1.0454
Mean Chi^2: 1.0454
Intercept: 0.9995 (0.0061)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Fri Mar  4 05:48:44 2022
Total time elapsed: 1.0m:51.32s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9468,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -5.5034e-07,
    "n": "-Inf",
    "n_snps": 11078115,
    "n_clumped_hits": 2,
    "n_p_sig": 161,
    "n_mono": 0,
    "n_ns": 1238646,
    "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": 1259640,
    "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": 1217959,
    "ldsc_nsnp_merge_regression_ld": 1217959,
    "ldsc_observed_scale_h2_beta": 0.0064,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 0.9995,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 1.0454,
    "ldsc_mean_chisq": 1.0454,
    "ldsc_ratio": -0.011
}

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 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 670 0.9999395 3 58 0 11040912 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 88 0 16745 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 662 0 68643 0 NA NA NA NA NA NA NA NA NA NA
logical N 11078115 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 8.799215e+00 5.910646e+00 1.000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.858819e+07 5.631709e+07 3.020e+02 3.232090e+07 6.905690e+07 1.144099e+08 2.492405e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.000000e-07 5.924000e-04 -6.419e-03 -2.443000e-04 -2.000000e-06 2.378000e-04 6.780500e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.764000e-04 3.381000e-04 1.598e-04 2.199000e-04 3.194000e-04 6.359000e-04 3.369400e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.925416e-01 2.908120e-01 0.000e+00 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.925414e-01 2.907869e-01 0.000e+00 2.386515e-01 4.900451e-01 7.447805e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.817505e-01 3.008694e-01 4.680e-03 2.939200e-02 1.518760e-01 4.752590e-01 9.953200e-01 ▇▂▂▁▂
numeric AF_reference 1259640 0.8862947 NA NA NA NA NA NA NA 2.329651e-01 2.537621e-01 0.000e+00 2.296330e-02 1.339860e-01 3.716050e-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 0.0000316 0.0002902 0.9100000 0.9133941 0.601344 NA NA
1 10352 rs1557426776 TA T 0.0000674 0.0002989 0.8200001 0.8217062 0.607011 NA NA
1 11008 rs575272151 C G 0.0000323 0.0004969 0.9500000 0.9481436 0.086194 0.0880591 NA
1 11012 rs544419019 C G 0.0000323 0.0004969 0.9500000 0.9481436 0.086194 0.0880591 NA
1 13110 rs540538026 G A -0.0003091 0.0006603 0.6400000 0.6396720 0.058732 0.0267572 NA
1 13116 rs62635286 T G 0.0000624 0.0003910 0.8700001 0.8732480 0.189424 0.0970447 NA
1 13118 rs200579949 A G 0.0000624 0.0003910 0.8700001 0.8732480 0.189424 0.0970447 NA
1 13273 rs531730856 G C 0.0004041 0.0004582 0.3800004 0.3778784 0.133950 0.0950479 NA
1 14464 rs546169444 A T -0.0000261 0.0004162 0.9500000 0.9499659 0.157053 0.0958466 NA
1 14599 rs531646671 T A 0.0005749 0.0003794 0.1299999 0.1296616 0.191610 0.1475640 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154901936 rs697727 A G 0.0001445 0.0001858 0.4400003 0.4367138 0.751532 0.643179 NA
23 154901964 rs697726 G A -0.0002418 0.0001961 0.2200002 0.2176050 0.347413 0.117616 NA
23 154902105 rs696316 G T 0.0001457 0.0001858 0.4299995 0.4327884 0.751485 0.636026 NA
23 154902889 rs697725 A T 0.0001442 0.0001857 0.4400003 0.4375421 0.751156 0.584106 NA
23 154903118 rs479770 G A 0.0001440 0.0001858 0.4400003 0.4385263 0.751575 0.643444 NA
23 154903224 rs480725 A T 0.0001439 0.0001858 0.4400003 0.4387458 0.751578 0.643444 NA
23 154903937 rs674707 G A 0.0001439 0.0001858 0.4400003 0.4386627 0.751587 0.643444 NA
23 154909055 rs473529 C G -0.0001232 0.0001750 0.4799997 0.4812543 0.305082 0.463046 NA
23 154918266 rs642043 C T -0.0001312 0.0001755 0.4500005 0.4546816 0.302944 0.478675 NA
23 154927581 rs644138 G A -0.0001298 0.0001756 0.4600002 0.4598490 0.302816 0.463576 NA

bcf preview

1   10177   rs1264289758    AC  A   .   PASS    AF=0.601344 ES:SE:LP:AF:ID  3.15591e-05:0.000290176:0.0409586:0.601344:rs1264289758
1   10352   rs1557426776    TA  T   .   PASS    AF=0.607011 ES:SE:LP:AF:ID  6.73581e-05:0.000298903:0.0861861:0.607011:rs1557426776
1   11008   rs575272151 C   G   .   PASS    AF=0.086194 ES:SE:LP:AF:ID  3.23158e-05:0.000496874:0.0222764:0.086194:rs575272151
1   11012   rs544419019 C   G   .   PASS    AF=0.086194 ES:SE:LP:AF:ID  3.23158e-05:0.000496874:0.0222764:0.086194:rs544419019
1   13110   rs540538026 G   A   .   PASS    AF=0.058732 ES:SE:LP:AF:ID  -0.00030913:0.000660312:0.19382:0.058732:rs540538026
1   13116   rs62635286  T   G   .   PASS    AF=0.189424 ES:SE:LP:AF:ID  6.2371e-05:0.000390957:0.0604807:0.189424:rs62635286
1   13118   rs62028691  A   G   .   PASS    AF=0.189424 ES:SE:LP:AF:ID  6.2371e-05:0.000390957:0.0604807:0.189424:rs62028691
1   13273   rs531730856 G   C   .   PASS    AF=0.13395  ES:SE:LP:AF:ID  0.000404064:0.00045822:0.420216:0.13395:rs531730856
1   14464   rs546169444 A   T   .   PASS    AF=0.157053 ES:SE:LP:AF:ID  -2.61176e-05:0.000416219:0.0222764:0.157053:rs546169444
1   14599   rs707680    T   A   .   PASS    AF=0.19161  ES:SE:LP:AF:ID  0.000574898:0.000379361:0.886057:0.19161:rs707680
1   14604   rs1418508701    A   G   .   PASS    AF=0.19161  ES:SE:LP:AF:ID  0.000574898:0.000379361:0.886057:0.19161:rs1418508701
1   14930   rs6682385   A   G   .   PASS    AF=0.473993 ES:SE:LP:AF:ID  -5.93075e-05:0.000294349:0.0757207:0.473993:rs6682385
1   14933   rs199856693 G   A   .   PASS    AF=0.044997 ES:SE:LP:AF:ID  -0.000666533:0.000724958:0.443698:0.044997:rs199856693
1   15211   rs3982632   T   G   .   PASS    AF=0.741388 ES:SE:LP:AF:ID  -0.000376839:0.000340295:0.568636:0.741388:rs3982632
1   15820   rs1316988498    G   T   .   PASS    AF=0.275232 ES:SE:LP:AF:ID  0.000213153:0.000348992:0.267606:0.275232:rs1316988498
1   15903   rs557514207 GC  G   .   PASS    AF=0.580992 ES:SE:LP:AF:ID  -0.000298403:0.000287747:0.522879:0.580992:rs557514207
1   28590   rs1344649620    T   TTGG    .   PASS    AF=0.956509 ES:SE:LP:AF:ID  0.000778786:0.000818358:0.468521:0.956509:rs1344649620
1   30923   rs1165072081    G   T   .   PASS    AF=0.910296 ES:SE:LP:AF:ID  0.000440472:0.000543485:0.376751:0.910296:rs1165072081
1   47159   rs540662756 T   C   .   PASS    AF=0.062659 ES:SE:LP:AF:ID  -0.000402784:0.000620111:0.283997:0.062659:rs540662756
1   49298   rs10399793  T   C   .   PASS    AF=0.62364  ES:SE:LP:AF:ID  5.92774e-05:0.000345286:0.0655015:0.62364:rs10399793
1   49554   rs539322794 A   G   .   PASS    AF=0.092951 ES:SE:LP:AF:ID  -0.000560182:0.000531141:0.537602:0.092951:rs539322794
1   51479   rs116400033 T   A   .   PASS    AF=0.213535 ES:SE:LP:AF:ID  0.0006152:0.000369014:1.02228:0.213535:rs116400033
1   54490   rs141149254 G   A   .   PASS    AF=0.154562 ES:SE:LP:AF:ID  0.000573996:0.000414603:0.769551:0.154562:rs141149254
1   54676   rs2462492   C   T   .   PASS    AF=0.400419 ES:SE:LP:AF:ID  -4.64906e-05:0.000342029:0.05061:0.400419:rs2462492
1   54712   rs573184866 TTTTC   T   .   PASS    AF=0.4148   ES:SE:LP:AF:ID  -0.000297614:0.00027036:0.568636:0.4148:rs573184866
1   54716   rs1166278911    C   T   .   PASS    AF=0.417195 ES:SE:LP:AF:ID  -0.000338004:0.000312289:0.552842:0.417195:rs1166278911
1   55545   rs28396308  C   T   .   PASS    AF=0.253875 ES:SE:LP:AF:ID  0.000100728:0.000351314:0.113509:0.253875:rs28396308
1   58814   rs114420996 G   A   .   PASS    AF=0.090024 ES:SE:LP:AF:ID  -0.000353569:0.000535064:0.29243:0.090024:rs114420996
1   59040   rs62637815  T   C   .   PASS    AF=0.08885  ES:SE:LP:AF:ID  -0.000679879:0.000537137:0.677781:0.08885:rs62637815
1   60351   rs62637817  A   G   .   PASS    AF=0.08101  ES:SE:LP:AF:ID  -0.000458304:0.00055715:0.387216:0.08101:rs62637817
1   62777   rs3844233   A   T   .   PASS    AF=0.438482 ES:SE:LP:AF:ID  -6.73366e-05:0.000296883:0.0861861:0.438482:rs3844233
1   63268   rs28664618  T   C   .   PASS    AF=0.382103 ES:SE:LP:AF:ID  -0.000112628:0.000319121:0.142668:0.382103:rs28664618
1   63671   rs80011619  G   A   .   PASS    AF=0.158817 ES:SE:LP:AF:ID  -0.000461723:0.000406339:0.585027:0.158817:rs80011619
1   63735   rs61158452  C   CCTA    .   PASS    AF=0.683964 ES:SE:LP:AF:ID  -0.000117392:0.000316275:0.148742:0.683964:rs61158452
1   64931   rs62639104  G   A   .   PASS    AF=0.079618 ES:SE:LP:AF:ID  -0.00046238:0.00056391:0.387216:0.079618:rs62639104
1   68082   rs367789441 T   C   .   PASS    AF=0.07076  ES:SE:LP:AF:ID  0.000119954:0.000571786:0.0809219:0.07076:rs367789441
1   69428   rs140739101 T   G   .   PASS    AF=0.032919 ES:SE:LP:AF:ID  0.00146956:0.000864827:1.05061:0.032919:rs140739101
1   69761   rs200505207 A   T   .   PASS    AF=0.073903 ES:SE:LP:AF:ID  6.97942e-05:0.000562432:0.0457575:0.073903:rs200505207
1   69897   rs200676709 T   C   .   PASS    AF=0.751182 ES:SE:LP:AF:ID  0.000362619:0.000358246:0.508638:0.751182:rs200676709
1   74790   rs13328700  C   G   .   PASS    AF=0.034046 ES:SE:LP:AF:ID  0.000186822:0.000822931:0.0861861:0.034046:rs13328700
1   74792   rs1335672253    G   A   .   PASS    AF=0.034046 ES:SE:LP:AF:ID  0.000186822:0.000822931:0.0861861:0.034046:rs1335672253
1   76838   rs563953605 T   G   .   PASS    AF=0.07718  ES:SE:LP:AF:ID  -0.000771671:0.000574718:0.744727:0.07718:rs563953605
1   76854   rs367666799 A   G   .   PASS    AF=0.077445 ES:SE:LP:AF:ID  -8.40516e-05:0.000554935:0.0555173:0.077445:rs367666799
1   77866   rs563593912 C   T   .   PASS    AF=0.076983 ES:SE:LP:AF:ID  -0.000771242:0.000574868:0.744727:0.076983:rs563593912
1   77874   rs62641297  G   A   .   PASS    AF=0.076983 ES:SE:LP:AF:ID  -0.000771242:0.000574868:0.744727:0.076983:rs62641297
1   81260   rs571136476 C   T   .   PASS    AF=0.041512 ES:SE:LP:AF:ID  -0.000785189:0.000801241:0.481486:0.041512:rs571136476
1   81587   rs536406113 C   T   .   PASS    AF=0.06097  ES:SE:LP:AF:ID  0.000201509:0.000609128:0.130768:0.06097:rs536406113
1   82163   rs139113303 G   A   .   PASS    AF=0.075406 ES:SE:LP:AF:ID  -5.62014e-05:0.000561942:0.0362122:0.075406:rs139113303
1   82609   rs149189449 C   G   .   PASS    AF=0.075432 ES:SE:LP:AF:ID  -7.90064e-05:0.000561829:0.05061:0.075432:rs149189449
1   83514   rs201754587 C   T   .   PASS    AF=0.352657 ES:SE:LP:AF:ID  -0.000356916:0.000321651:0.568636:0.352657:rs201754587