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-30820_irnt/ukb-d-30820_irnt.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-30820_irnt/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 14:55:02 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30820_irnt/ukb-d-30820_irnt.vcf.gz ...
Read summary statistics for 13538538 SNPs.
Dropped 12654 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, 1283491 SNPs remain.
After merging with regression SNP LD, 1283491 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0149 (0.0139)
Lambda GC: 1.0115
Mean Chi^2: 1.0025
Intercept: 0.9934 (0.0064)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 14:57:46 2019
Total time elapsed: 2.0m:43.9s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0087,
    "mean_EFFECT": 0.0001,
    "n": 30565,
    "n_snps": 13538538,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1250119,
    "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": 557298,
    "n_est": 30709.5083,
    "ratio_se_n": 1.0024,
    "mean_diff": -2.1177e-06,
    "ratio_diff": 1.1919,
    "sd_y_est1": 1,
    "sd_y_est2": 1.0024,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283491,
    "ldsc_nsnp_merge_regression_ld": 1283491,
    "ldsc_observed_scale_h2_beta": 0.0149,
    "ldsc_observed_scale_h2_se": 0.0139,
    "ldsc_intercept_beta": 0.9934,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0115,
    "ldsc_mean_chisq": 1.0025,
    "ldsc_ratio": -2.64
}

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 13526548 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56986 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33310 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051983e+00 6.184866e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902126e+07 5.591650e+07 3.0200e+02 3.292405e+07 7.013014e+07 1.148544e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.443000e-04 4.679160e-02 -5.6705e-01 -1.237500e-02 2.410000e-05 1.248000e-02 6.487800e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.366980e-02 3.240870e-02 6.6816e-03 9.665800e-03 1.772300e-02 4.832000e-02 1.696300e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.987900e-01 2.886870e-01 0.0000e+00 2.487001e-01 4.981498e-01 7.488192e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.987848e-01 2.886901e-01 0.0000e+00 2.486945e-01 4.981488e-01 7.488222e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.914357e-01 2.545549e-01 1.0001e-03 7.590000e-03 6.076400e-02 2.965200e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 557298 0.9588362 NA NA NA NA NA 1.968017e-01 2.471982e-01 0.0000e+00 5.790700e-03 8.486420e-02 3.091050e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.056500e+04 0.000000e+00 3.0565e+04 3.056500e+04 3.056500e+04 3.056500e+04 3.056500e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0164320 0.014195 0.2470302 0.2470311 0.1106500 0.1894970 30565
1 693731 rs12238997 A G 0.0020163 0.013404 0.8804299 0.8804291 0.1163200 0.1417730 30565
1 707522 rs371890604 G C 0.0042260 0.015004 0.7781996 0.7782056 0.0982750 0.1293930 30565
1 717587 rs144155419 G A -0.0144350 0.036133 0.6895297 0.6895275 0.0155890 0.0045926 30565
1 723329 rs189787166 A T 0.0604790 0.106530 0.5702496 0.5702265 0.0017197 0.0003994 30565
1 730087 rs148120343 T C 0.0027365 0.018726 0.8838100 0.8838158 0.0566190 0.0127796 30565
1 731718 rs142557973 T C 0.0022474 0.012688 0.8594100 0.8594079 0.1225600 0.1543530 30565
1 732032 rs61770163 A C 0.0018699 0.013529 0.8900701 0.8900711 0.1220300 0.1555510 30565
1 734349 rs141242758 T C 0.0015565 0.012702 0.9024701 0.9024716 0.1216700 0.1525560 30565
1 740284 rs61770167 C T 0.0305160 0.056726 0.5906103 0.5906085 0.0060361 0.0023962 30565
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0050606 0.0148170 0.7327098 0.7326970 0.055553 0.0309934 30565
23 154923374 rs111332691 T A 0.0018266 0.0159790 0.9089900 0.9089900 0.045984 0.0116556 30565
23 154925045 rs509981 C T -0.0068965 0.0078056 0.3769502 0.3769487 0.246160 0.3634440 30565
23 154925895 rs538470 C T -0.0088463 0.0079708 0.2670798 0.2670687 0.242980 0.3634440 30565
23 154927581 rs644138 G A -0.0076892 0.0073458 0.2952202 0.2952159 0.302160 0.4635760 30565
23 154929412 rs557132 C T -0.0068863 0.0078070 0.3777496 0.3777404 0.246080 0.3568210 30565
23 154929637 rs35185538 CT C -0.0062651 0.0081424 0.4416396 0.4416313 0.230580 0.3011920 30565
23 154929952 rs4012982 CAA C -0.0080856 0.0082195 0.3252603 0.3252584 0.239600 0.3165560 30565
23 154930230 rs781880 A G -0.0076141 0.0078060 0.3293601 0.3293538 0.246470 0.3618540 30565
23 154930487 rs781879 T A -0.0011038 0.0259640 0.9660900 0.9660900 0.020469 0.1263580 30565

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11065  ES:SE:LP:AF:SS:ID   0.016432:0.014195:0.60725:0.11065:30565:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11632  ES:SE:LP:AF:SS:ID   0.0020163:0.013404:0.0553052:0.11632:30565:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098275 ES:SE:LP:AF:SS:ID   0.004226:0.015004:0.108909:0.098275:30565:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015589 ES:SE:LP:AF:SS:ID   -0.014435:0.036133:0.161447:0.015589:30565:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017197    ES:SE:LP:AF:SS:ID   0.060479:0.10653:0.243935:0.0017197:30565:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056619 ES:SE:LP:AF:SS:ID   0.0027365:0.018726:0.0536411:0.056619:30565:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12256  ES:SE:LP:AF:SS:ID   0.0022474:0.012688:0.0657996:0.12256:30565:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12203  ES:SE:LP:AF:SS:ID   0.0018699:0.013529:0.0505758:0.12203:30565:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12167  ES:SE:LP:AF:SS:ID   0.0015565:0.012702:0.0445672:0.12167:30565:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0060361    ES:SE:LP:AF:SS:ID   0.030516:0.056726:0.228699:0.0060361:30565:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0019601    ES:SE:LP:AF:SS:ID   0.097224:0.1072:0.438362:0.0019601:30565:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86841  ES:SE:LP:AF:SS:ID   -0.009145:0.012514:0.33264:0.86841:30565:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015706    ES:SE:LP:AF:SS:ID   -0.035516:0.11127:0.125176:0.0015706:30565:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12378  ES:SE:LP:AF:SS:ID   0.005335:0.012399:0.175874:0.12378:30565:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14346  ES:SE:LP:AF:SS:ID   0.0048223:0.012258:0.158634:0.14346:30565:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12388  ES:SE:LP:AF:SS:ID   0.0050114:0.012383:0.16386:0.12388:30565:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87018  ES:SE:LP:AF:SS:ID   -0.0070019:0.012069:0.250403:0.87018:30565:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87446  ES:SE:LP:AF:SS:ID   -0.0058297:0.012269:0.197459:0.87446:30565:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12923  ES:SE:LP:AF:SS:ID   0.0051206:0.012113:0.172314:0.12923:30565:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.034386 ES:SE:LP:AF:SS:ID   0.0060615:0.022501:0.103678:0.034386:30565:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86979  ES:SE:LP:AF:SS:ID   -0.005916:0.012062:0.204941:0.86979:30565:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86983  ES:SE:LP:AF:SS:ID   -0.006031:0.012064:0.209616:0.86983:30565:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8698   ES:SE:LP:AF:SS:ID   -0.0062206:0.012062:0.217484:0.8698:30565:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0048753    ES:SE:LP:AF:SS:ID   -0.081218:0.063414:0.698341:0.0048753:30565:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0048355    ES:SE:LP:AF:SS:ID   -0.080782:0.063585:0.690498:0.0048355:30565:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0054876    ES:SE:LP:AF:SS:ID   -0.011709:0.060098:0.0728761:0.0054876:30565:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.86981  ES:SE:LP:AF:SS:ID   -0.0059274:0.012032:0.206014:0.86981:30565:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12673  ES:SE:LP:AF:SS:ID   0.0057046:0.012276:0.192364:0.12673:30565:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86931  ES:SE:LP:AF:SS:ID   -0.0066864:0.012001:0.238501:0.86931:30565:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8687   ES:SE:LP:AF:SS:ID   -0.0062465:0.011999:0.219928:0.8687:30565:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86957  ES:SE:LP:AF:SS:ID   -0.0060609:0.012015:0.211874:0.86957:30565:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86958  ES:SE:LP:AF:SS:ID   -0.0060602:0.012016:0.211825:0.86958:30565:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86958  ES:SE:LP:AF:SS:ID   -0.0060462:0.012016:0.211238:0.86958:30565:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86997  ES:SE:LP:AF:SS:ID   -0.0062133:0.012044:0.217585:0.86997:30565:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.099936 ES:SE:LP:AF:SS:ID   0.0084818:0.01397:0.264593:0.099936:30565:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0062753    ES:SE:LP:AF:SS:ID   0.0064477:0.054704:0.0427903:0.0062753:30565:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.8736   ES:SE:LP:AF:SS:ID   -0.0064171:0.012216:0.222298:0.8736:30565:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86341  ES:SE:LP:AF:SS:ID   -0.0058447:0.011979:0.203696:0.86341:30565:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86864  ES:SE:LP:AF:SS:ID   -0.0060565:0.012099:0.209947:0.86864:30565:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86542  ES:SE:LP:AF:SS:ID   -0.0045646:0.012093:0.1513:0.86542:30565:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.099302 ES:SE:LP:AF:SS:ID   0.0098544:0.014505:0.303731:0.099302:30565:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87051  ES:SE:LP:AF:SS:ID   -0.0052331:0.012232:0.174704:0.87051:30565:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87051  ES:SE:LP:AF:SS:ID   -0.0052335:0.012232:0.174723:0.87051:30565:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.8705   ES:SE:LP:AF:SS:ID   -0.0052355:0.012232:0.174801:0.8705:30565:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87085  ES:SE:LP:AF:SS:ID   -0.0048241:0.012237:0.159004:0.87085:30565:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12628  ES:SE:LP:AF:SS:ID   0.0049935:0.012263:0.165033:0.12628:30565:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10647  ES:SE:LP:AF:SS:ID   0.011522:0.013334:0.411683:0.10647:30565:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85441  ES:SE:LP:AF:SS:ID   -0.0045013:0.011977:0.150556:0.85441:30565:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016764    ES:SE:LP:AF:SS:ID   0.033733:0.10564:0.12524:0.0016764:30565:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83986  ES:SE:LP:AF:SS:ID   0.0073526:0.011834:0.272142:0.83986:30565:rs376645387