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-K56/ukb-d-K56.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-K56/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 17:45:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-K56/ukb-d-K56.vcf.gz ...
Read summary statistics for 10525331 SNPs.
Dropped 8418 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, 1280795 SNPs remain.
After merging with regression SNP LD, 1280795 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 8.3054e-05 (0.0012)
Lambda GC: 1.0036
Mean Chi^2: 1.0005
Intercept: 0.9999 (0.0065)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:46:54 2019
Total time elapsed: 1.0m:44.65s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9441,
    "inflation_factor": 1.0012,
    "mean_EFFECT": -9.9572e-07,
    "n": 361194,
    "n_snps": 10525331,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1113225,
    "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": 207086,
    "n_est": 361369.6606,
    "ratio_se_n": 1.0002,
    "mean_diff": -0,
    "ratio_diff": 25.8521,
    "sd_y_est1": 0.0761,
    "sd_y_est2": 0.0761,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1280795,
    "ldsc_nsnp_merge_regression_ld": 1280795,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 0.9999,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0036,
    "ldsc_mean_chisq": 1.0005,
    "ldsc_ratio": -0.2
}

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 1.000000 3 94 0 10517481 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 49791 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 30776 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.075747e+00 6.178402e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.879524e+07 5.605035e+07 3.02000e+02 3.256150e+07 6.974149e+07 1.147418e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA -1.000000e-06 4.896000e-04 -4.68630e-03 -2.107000e-04 -2.600000e-06 2.045000e-04 5.309200e-03 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 4.064000e-04 2.721000e-04 1.47300e-04 1.994000e-04 2.813000e-04 5.346000e-04 1.523300e-03 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.999115e-01 2.885921e-01 1.00000e-07 2.499850e-01 4.997422e-01 7.495766e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.999110e-01 2.885923e-01 1.00000e-07 2.499843e-01 4.997416e-01 7.495757e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 2.428868e-01 2.625832e-01 5.97510e-03 3.038590e-02 1.325110e-01 3.886780e-01 9.940250e-01 ▇▂▂▁▁
numeric AF_reference 207086 0.980325 NA NA NA NA NA 2.427914e-01 2.535334e-01 0.00000e+00 3.154950e-02 1.493610e-01 3.857830e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.000000 NA NA NA NA NA 3.611940e+05 0.000000e+00 3.61194e+05 3.611940e+05 3.611940e+05 3.611940e+05 3.611940e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0002646 0.0003138 0.3991251 0.3991238 0.1106400 0.1894970 361194
1 693731 rs12238997 A G 0.0004541 0.0002965 0.1256690 0.1256688 0.1158300 0.1417730 361194
1 707522 rs371890604 G C 0.0004434 0.0003334 0.1834649 0.1834643 0.0973034 0.1293930 361194
1 717587 rs144155419 G A 0.0002595 0.0007955 0.7442280 0.7442274 0.0156880 0.0045926 361194
1 730087 rs148120343 T C 0.0003205 0.0004131 0.4378194 0.4378195 0.0564602 0.0127796 361194
1 731718 rs142557973 T C 0.0003835 0.0002812 0.1727050 0.1727037 0.1217380 0.1543530 361194
1 732032 rs61770163 A C 0.0005551 0.0003000 0.0642614 0.0642597 0.1211710 0.1555510 361194
1 734349 rs141242758 T C 0.0003775 0.0002814 0.1797500 0.1797493 0.1209650 0.1525560 361194
1 749963 rs529266287 T TAA -0.0002874 0.0002774 0.3001276 0.3001275 0.8697420 0.7641770 361194
1 751343 rs28544273 T A 0.0003908 0.0002747 0.1549341 0.1549326 0.1229160 0.2426120 361194
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0001295 0.0003249 0.6901603 0.6901601 0.0561667 0.0309934 361194
23 154923374 rs111332691 T A 0.0006867 0.0003571 0.0544628 0.0544628 0.0447862 0.0116556 361194
23 154925045 rs509981 C T -0.0003534 0.0001718 0.0396689 0.0396684 0.2456060 0.3634440 361194
23 154925895 rs538470 C T -0.0003434 0.0001758 0.0506886 0.0506881 0.2419150 0.3634440 361194
23 154927581 rs644138 G A -0.0003376 0.0001616 0.0366741 0.0366737 0.3021620 0.4635760 361194
23 154929412 rs557132 C T -0.0003505 0.0001719 0.0413990 0.0413975 0.2454590 0.3568210 361194
23 154929637 rs35185538 CT C -0.0002393 0.0001794 0.1821030 0.1821020 0.2296970 0.3011920 361194
23 154929952 rs4012982 CAA C -0.0003294 0.0001808 0.0684164 0.0684152 0.2394250 0.3165560 361194
23 154930230 rs781880 A G -0.0003596 0.0001718 0.0363614 0.0363607 0.2458690 0.3618540 361194
23 154930487 rs781879 T A -0.0003827 0.0005895 0.5161655 0.5161651 0.0195623 0.1263580 361194

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11064  ES:SE:LP:AF:SS:ID   0.000264625:0.000313839:0.398891:0.11064:361194:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11583  ES:SE:LP:AF:SS:ID   0.000454122:0.000296539:0.900772:0.11583:361194:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973034    ES:SE:LP:AF:SS:ID   0.000443438:0.000333371:0.736447:0.0973034:361194:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015688 ES:SE:LP:AF:SS:ID   0.000259543:0.000795509:0.128294:0.015688:361194:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0564602    ES:SE:LP:AF:SS:ID   0.000320531:0.000413119:0.358705:0.0564602:361194:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121738 ES:SE:LP:AF:SS:ID   0.000383487:0.000281238:0.762695:0.121738:361194:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121171 ES:SE:LP:AF:SS:ID   0.000555101:0.000299994:1.19205:0.121171:361194:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120965 ES:SE:LP:AF:SS:ID   0.000377491:0.000281389:0.745331:0.120965:361194:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.869742 ES:SE:LP:AF:SS:ID   -0.000287437:0.000277406:0.522694:0.869742:361194:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.122916 ES:SE:LP:AF:SS:ID   0.000390759:0.000274733:0.809853:0.122916:361194:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142712 ES:SE:LP:AF:SS:ID   0.000295986:0.000271559:0.559507:0.142712:361194:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123031 ES:SE:LP:AF:SS:ID   0.000392458:0.000274351:0.816514:0.123031:361194:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87089  ES:SE:LP:AF:SS:ID   -0.000299368:0.000267346:0.580358:0.87089:361194:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875472 ES:SE:LP:AF:SS:ID   -0.000399138:0.000271776:0.847911:0.875472:361194:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128631 ES:SE:LP:AF:SS:ID   0.000329607:0.000268017:0.660008:0.128631:361194:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363613    ES:SE:LP:AF:SS:ID   -0.000889636:0.000486243:1.17193:0.0363613:361194:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870484 ES:SE:LP:AF:SS:ID   -0.000304776:0.000267068:0.595522:0.870484:361194:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870589 ES:SE:LP:AF:SS:ID   -0.000310376:0.00026719:0.61015:0.870589:361194:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870481 ES:SE:LP:AF:SS:ID   -0.000304:0.000267058:0.593485:0.870481:361194:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.870563 ES:SE:LP:AF:SS:ID   -0.000302196:0.000266588:0.590106:0.870563:361194:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125985 ES:SE:LP:AF:SS:ID   0.000353633:0.000272018:0.713117:0.125985:361194:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870127 ES:SE:LP:AF:SS:ID   -0.000284262:0.000265947:0.544959:0.870127:361194:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869414 ES:SE:LP:AF:SS:ID   -0.000276184:0.000265704:0.524909:0.869414:361194:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870281 ES:SE:LP:AF:SS:ID   -0.000291485:0.000266176:0.563074:0.870281:361194:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870287 ES:SE:LP:AF:SS:ID   -0.000291202:0.000266195:0.562281:0.870287:361194:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870295 ES:SE:LP:AF:SS:ID   -0.000291875:0.000266203:0.564014:0.870295:361194:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870739 ES:SE:LP:AF:SS:ID   -0.000295279:0.000266881:0.570973:0.870739:361194:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988442    ES:SE:LP:AF:SS:ID   0.000427315:0.000310131:0.774042:0.0988442:361194:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647588   ES:SE:LP:AF:SS:ID   0.000777284:0.00119961:0.286494:0.00647588:361194:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874635 ES:SE:LP:AF:SS:ID   -0.000363691:0.000270858:0.746279:0.874635:361194:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864027 ES:SE:LP:AF:SS:ID   -0.000218405:0.000265617:0.386229:0.864027:361194:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869425 ES:SE:LP:AF:SS:ID   -0.000340967:0.000268195:0.691203:0.869425:361194:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866371 ES:SE:LP:AF:SS:ID   -0.000316341:0.00026825:0.622898:0.866371:361194:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987831    ES:SE:LP:AF:SS:ID   0.000611466:0.000321144:1.24483:0.0987831:361194:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871556 ES:SE:LP:AF:SS:ID   -0.000350475:0.000271306:0.706803:0.871556:361194:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871556 ES:SE:LP:AF:SS:ID   -0.000350472:0.000271306:0.706797:0.871556:361194:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871555 ES:SE:LP:AF:SS:ID   -0.000350452:0.000271311:0.706719:0.871555:361194:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871929 ES:SE:LP:AF:SS:ID   -0.000340408:0.000271466:0.678079:0.871929:361194:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125562 ES:SE:LP:AF:SS:ID   0.000363797:0.00027168:0.7434:0.125562:361194:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105428 ES:SE:LP:AF:SS:ID   0.000388909:0.000295761:0.72462:0.105428:361194:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855376 ES:SE:LP:AF:SS:ID   -0.000350232:0.000265517:0.727808:0.855376:361194:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838358 ES:SE:LP:AF:SS:ID   7.17238e-05:0.000261582:0.105719:0.838358:361194:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763351 ES:SE:LP:AF:SS:ID   -6.0962e-05:0.000210525:0.112302:0.763351:361194:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105921 ES:SE:LP:AF:SS:ID   -0.00022651:0.000290052:0.361667:0.105921:361194:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00768395   ES:SE:LP:AF:SS:ID   0.000867029:0.00107767:0.375628:0.00768395:361194:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.128938 ES:SE:LP:AF:SS:ID   0.000305118:0.00026788:0.593973:0.128938:361194:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.128608 ES:SE:LP:AF:SS:ID   0.000306918:0.000267632:0.599516:0.128608:361194:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.105213 ES:SE:LP:AF:SS:ID   -0.000247877:0.000292242:0.401939:0.105213:361194:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.009077 ES:SE:LP:AF:SS:ID   0.000540504:0.00103029:0.221957:0.009077:361194:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00769858   ES:SE:LP:AF:SS:ID   0.000869165:0.00108246:0.374688:0.00769858:361194:rs112563271