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/ieu-a-import/processed/ieu-a-25/ieu-a-25.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/ieu-a-import/processed/ieu-a-25/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  5 11:42:09 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-25/ieu-a-25.vcf.gz ...
Read summary statistics for 42089 SNPs.
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, 5149 SNPs remain.
After merging with regression SNP LD, 5149 SNPs remain.
WARNING: number of SNPs less than 200k; this is almost always bad.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 5.5793 (1.1749)
Lambda GC: 5.3016
Mean Chi^2: 8.949
Intercept: 1.4518 (0.2706)
Ratio: 0.0568 (0.034)
Analysis finished at Wed Feb  5 11:42:18 2020
Total time elapsed: 8.82s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9473,
    "inflation_factor": 2.2655,
    "mean_EFFECT": 0.0024,
    "n": 73903.1,
    "n_snps": 42089,
    "n_clumped_hits": 27,
    "n_p_sig": 1384,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 31,
    "n_miss_AF_reference": 1052,
    "n_est": 72930.6204,
    "ratio_se_n": 0.9934,
    "mean_diff": -0.0012,
    "ratio_diff": 4.9088,
    "sd_y_est1": 2.4804,
    "sd_y_est2": 2.464,
    "r2_sum1": 0.1591,
    "r2_sum2": 0.0259,
    "r2_sum3": 0.0262,
    "r2_sum4": 0.0269,
    "ldsc_nsnp_merge_refpanel_ld": 5149,
    "ldsc_nsnp_merge_regression_ld": 5149,
    "ldsc_observed_scale_h2_beta": 5.5793,
    "ldsc_observed_scale_h2_se": 1.1749,
    "ldsc_intercept_beta": 1.4518,
    "ldsc_intercept_se": 0.2706,
    "ldsc_lambda_gc": 5.3016,
    "ldsc_mean_chisq": 8.949,
    "ldsc_ratio": 0.0568
}
 

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 5 58 0 42089 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.947231e+00 5.387551e+00 1.000000e+00 4.000000e+00 7.000000e+00 1.200000e+01 2.000000e+01 ▇▇▇▃▃
numeric POS 0 1.0000000 NA NA NA NA NA 4.920317e+07 4.677479e+07 2.443938e+06 1.726418e+07 2.821981e+07 6.233321e+07 2.271907e+08 ▇▃▂▁▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.436300e-03 8.674340e-02 -7.390760e-01 -3.536710e-02 1.998000e-03 4.018180e-02 9.050280e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 5.759650e-02 5.740080e-02 1.242220e-02 1.580560e-02 3.218140e-02 7.917560e-02 4.256580e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 3.680900e-01 3.186724e-01 0.000000e+00 5.399950e-02 3.100002e-01 6.400000e-01 1.000000e+00 ▇▃▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 3.681309e-01 3.187322e-01 0.000000e+00 5.430650e-02 3.067689e-01 6.438721e-01 1.000000e+00 ▇▃▃▃▃
numeric AF 31 0.9992635 NA NA NA NA NA 1.677616e-01 2.341735e-01 1.000000e-03 8.000000e-03 4.500000e-02 2.560000e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 1052 0.9750053 NA NA NA NA NA 1.814399e-01 2.401072e-01 0.000000e+00 5.990400e-03 6.549520e-02 2.815500e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 7.238018e+04 3.396033e+03 5.912810e+04 7.340060e+04 7.390220e+04 7.390230e+04 7.390310e+04 ▁▁▁▁▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 120437718 rs2793823 G A 0.0592119 0.0185129 0.0014000 0.0013819 0.132 0.3306710 73902.3
1 120437884 rs2641348 A G 0.0648510 0.0200746 0.0011000 0.0012357 0.110 0.1958870 73902.3
1 120438577 rs147294252 G A 0.1239860 0.1084960 0.2500000 0.2531340 0.006 0.0013978 67530.5
1 120439109 rs6668119 G C 0.0685928 0.0202474 0.0007300 0.0007047 0.106 0.1930910 73902.3
1 120440029 rs2027447 T C 0.0676586 0.0200183 0.0006800 0.0007253 0.110 0.1958870 73902.3
1 120441885 rs76686822 C T 0.0119286 0.0733156 0.8700001 0.8707530 0.010 0.0143770 73902.4
1 120441998 rs2487568 A G 0.0601539 0.0184955 0.0012000 0.0011445 0.133 0.3955670 73902.3
1 120442257 rs2487569 A T 0.0573251 0.0238317 0.0160000 0.0161542 0.088 0.2799520 73901.9
1 120443424 rs180671497 C A 0.0601539 0.0998053 0.5500004 0.5467000 0.006 0.0011981 68337.2
1 120443540 rs2641346 C T 0.0667236 0.0200370 0.0008400 0.0008684 0.110 0.1950880 73902.3
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
20 43056149 rs6031598 G T 0.0089597 0.0128905 0.4799997 0.4870143 0.610 0.4670530 73902.3
20 43056562 rs3212208 T C -0.0285875 0.0225638 0.2099999 0.2051685 0.088 0.1591450 73902.3
20 43056584 rs181422893 G A -0.0148886 0.0973840 0.8800001 0.8784886 0.005 0.0057907 72055.1
20 43056732 rs6031600 A G 0.3729420 0.1667590 0.0250000 0.0253247 0.002 0.0057907 61986.2
20 43057480 rs3818247 G T -0.0324672 0.0133385 0.0150000 0.0149290 0.348 0.4934110 73902.3
20 43057820 rs6031601 C A -0.0009995 0.0129935 0.9500000 0.9386847 0.611 0.5087860 73902.3
20 43057831 rs112600410 A G -0.3611650 0.1746860 0.0389996 0.0386862 0.003 0.0085863 61574.2
20 43058012 rs74173201 A C -0.0207825 0.0249810 0.4100001 0.4054472 0.069 0.0597045 73902.3
20 43058018 rs3746574 T C 0.0039920 0.0127069 0.7499995 0.7533983 0.517 0.3801920 73901.3
20 43058096 rs3746575 C G -0.0009995 0.0129935 0.9199999 0.9386847 0.607 0.4988020 73901.4

bcf preview

1   120437718   rs2793823   G   A   .   PASS    AF=0.132    ES:SE:LP:AF:SS:ID   0.0592119:0.0185129:2.85387:0.132:73902.3:rs2793823
1   120437884   rs2641348   A   G   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   0.064851:0.0200746:2.95861:0.11:73902.3:rs2641348
1   120438577   rs147294252 G   A   .   PASS    AF=0.006    ES:SE:LP:AF:SS:ID   0.123986:0.108496:0.60206:0.006:67530.5:rs147294252
1   120439109   rs6668119   G   C   .   PASS    AF=0.106    ES:SE:LP:AF:SS:ID   0.0685928:0.0202474:3.13668:0.106:73902.3:rs6668119
1   120440029   rs2027447   T   C   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   0.0676586:0.0200183:3.16749:0.11:73902.3:rs2027447
1   120441885   rs76686822  C   T   .   PASS    AF=0.01 ES:SE:LP:AF:SS:ID   0.0119286:0.0733156:0.0604807:0.01:73902.4:rs76686822
1   120441998   rs2487568   A   G   .   PASS    AF=0.133    ES:SE:LP:AF:SS:ID   0.0601539:0.0184955:2.92082:0.133:73902.3:rs2487568
1   120442257   rs2487569   A   T   .   PASS    AF=0.088    ES:SE:LP:AF:SS:ID   0.0573251:0.0238317:1.79588:0.088:73901.9:rs2487569
1   120443424   rs180671497 C   A   .   PASS    AF=0.006    ES:SE:LP:AF:SS:ID   0.0601539:0.0998053:0.259637:0.006:68337.2:rs180671497
1   120443540   rs2641346   C   T   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   0.0667236:0.020037:3.07572:0.11:73902.3:rs2641346
1   120443702   rs2793826   G   A   .   PASS    AF=0.133    ES:SE:LP:AF:SS:ID   0.0544882:0.0183502:2.50864:0.133:73902.3:rs2793826
1   120444009   rs115640286 C   T   .   PASS    AF=0.04 ES:SE:LP:AF:SS:ID   -0.0246926:0.0385181:0.283997:0.04:73902.2:rs115640286
1   120444402   rs78188788  A   G   .   PASS    AF=0.008    ES:SE:LP:AF:SS:ID   0.0353671:0.0799261:0.187087:0.008:69643.2:rs78188788
1   120444648   rs112142442 T   C   .   PASS    AF=0.004    ES:SE:LP:AF:SS:ID   0.160417:0.106363:0.886057:0.004:69375.4:rs112142442
1   120445032   rs74115387  A   G   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   0.00299551:0.0437226:0.0222764:0.021:73902:rs74115387
1   120445902   rs7517669   A   G   .   PASS    AF=0.002    ES:SE:LP:AF:SS:ID   0.116004:0.178911:0.283997:0.002:59522.4:rs7517669
1   120446063   rs2641352   T   C   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   0.0676586:0.019789:3.11919:0.11:73902.3:rs2641352
1   120446201   rs74115388  T   C   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   -0.00796817:0.0442459:0.0655015:0.021:73902.3:rs74115388
1   120446294   rs115764389 C   G   .   PASS    AF=0.142    ES:SE:LP:AF:SS:ID   -0.0237165:0.0181848:0.721246:0.142:73902.3:rs115764389
1   120447463   rs2493398   G   A   .   PASS    AF=0.131    ES:SE:LP:AF:SS:ID   0.0573251:0.0187801:2.69897:0.131:73902.3:rs2493398
1   120448697   rs12071541  A   G   .   PASS    AF=0.002    ES:SE:LP:AF:SS:ID   -0.0382587:0.179254:0.0809219:0.002:64213.2:rs12071541
1   120448749   rs2641338   G   A   .   PASS    AF=0.13 ES:SE:LP:AF:SS:ID   0.0573251:0.0185479:2.65758:0.13:73902.5:rs2641338
1   120448805   rs2793827   A   T   .   PASS    AF=0.129    ES:SE:LP:AF:SS:ID   0.0563803:0.0187979:2.56864:0.129:73902.1:rs2793827
1   120450282   rs74115390  G   T   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   0.0009995:0.0435324:0.00436481:0.021:73902.1:rs74115390
1   120451190   rs3897478   T   C   .   PASS    AF=0.108    ES:SE:LP:AF:SS:ID   0.0657877:0.0200558:3:0.108:73902.3:rs3897478
1   120451209   rs74115392  T   C   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   0.0009995:0.0438101:0.00436481:0.021:73902.2:rs74115392
1   120451352   rs947273    C   A   .   PASS    AF=0.131    ES:SE:LP:AF:SS:ID   0.0573251:0.0187801:2.69897:0.131:73902.3:rs947273
1   120452676   rs17024486  G   C   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   0.0009995:0.0438101:0.00436481:0.021:73902.3:rs17024486
1   120453618   rs74115396  G   A   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   0.0009995:0.0435324:0.00436481:0.021:73902.3:rs74115396
1   120454086   rs17024487  A   G   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   -0.00399202:0.0441453:0.0315171:0.021:73902.3:rs17024487
1   120455095   rs1043964   T   C   .   PASS    AF=0.022    ES:SE:LP:AF:SS:ID   0.00697561:0.0435053:0.0655015:0.022:73902.3:rs1043964
1   120455310   rs699779    A   G   .   PASS    AF=0.108    ES:SE:LP:AF:SS:ID   0.0667236:0.0202853:3.01773:0.108:73902.3:rs699779
1   120455441   rs699780    A   G   .   PASS    AF=0.131    ES:SE:LP:AF:SS:ID   0.0573251:0.0185479:2.69897:0.131:73902.3:rs699780
1   120455586   rs835576    T   C   .   PASS    AF=0.108    ES:SE:LP:AF:SS:ID   0.0657877:0.0200558:3:0.108:73902.3:rs835576
1   120456563   rs835575    G   T   .   PASS    AF=0.108    ES:SE:LP:AF:SS:ID   0.0676586:0.0202663:3.08092:0.108:73902.3:rs835575
1   120457501   rs7527186   C   T   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   -0.00299551:0.0439561:0.0222764:0.021:73902.2:rs7527186
1   120458004   rs6685892   A   T   .   PASS    AF=0.108    ES:SE:LP:AF:SS:ID   0.064851:0.0203233:2.88606:0.108:73902.3:rs6685892
1   120458924   rs3795666   G   A   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   -0.00598207:0.044334:0.0457575:0.021:73902.3:rs3795666
1   120459433   rs41277624  G   A   .   PASS    AF=0.051    ES:SE:LP:AF:SS:ID   0.0344014:0.0283327:0.638272:0.051:73902.3:rs41277624
1   120459721   rs144654514 G   A   .   PASS    AF=0.004    ES:SE:LP:AF:SS:ID   -0.225541:0.141874:0.958607:0.004:60163.4:rs144654514
1   120460634   rs3897840   A   G   .   PASS    AF=0.002    ES:SE:LP:AF:SS:ID   0.0353671:0.178738:0.0757207:0.002:59522.3:rs3897840
1   120460916   rs10494233  A   C   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   -0.00399202:0.0441453:0.0315171:0.021:73902.3:rs10494233
1   120461253   rs2793829   C   T   .   PASS    AF=0.107    ES:SE:LP:AF:SS:ID   0.0685928:0.0202474:3.14874:0.107:73902.3:rs2793829
1   120461536   rs17258558  T   A   .   PASS    AF=0.029    ES:SE:LP:AF:SS:ID   -0.0256677:0.03825:0.30103:0.029:73902.3:rs17258558
1   120461629   rs17024508  G   A   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   -0.00399202:0.0439122:0.0315171:0.021:73902.3:rs17024508
1   120462468   rs56342935  C   T   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   -0.00299551:0.0441894:0.0268721:0.021:73902.2:rs56342935
1   120463044   rs41306195  C   T   .   PASS    AF=0.079    ES:SE:LP:AF:SS:ID   -0.0478373:0.0240588:1.35655:0.079:73902.3:rs41306195
1   120463230   rs835574    C   T   .   PASS    AF=0.131    ES:SE:LP:AF:SS:ID   0.0592119:0.0185129:2.79588:0.131:73902.3:rs835574
1   120463398   rs12117337  C   T   .   PASS    AF=0.021    ES:SE:LP:AF:SS:ID   -0.0639133:0.0516246:0.657577:0.021:72853.7:rs12117337
1   120464165   rs835573    C   T   .   PASS    AF=0.129    ES:SE:LP:AF:SS:ID   0.0592119:0.0187447:2.85387:0.129:73902.3:rs835573