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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1022/ieu-a-1022.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-1022/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Tue Feb 4 16:49:28 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1022/ieu-a-1022.vcf.gz ...
Read summary statistics for 2384143 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, 1164758 SNPs remain.
After merging with regression SNP LD, 1164758 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0824 (0.1943)
Lambda GC: 0.9974
Mean Chi^2: 0.9997
Intercept: 0.9956 (0.0064)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Tue Feb 4 16:49:58 2020
Total time elapsed: 29.85sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9245,
"inflation_factor": 0.9973,
"mean_EFFECT": -0,
"n": 2469,
"n_snps": 2384143,
"n_clumped_hits": 0,
"n_p_sig": 0,
"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": 0,
"n_miss_AF_reference": 18971,
"n_est": 2451.1712,
"ratio_se_n": 0.9964,
"mean_diff": -0,
"ratio_diff": 13.0444,
"sd_y_est1": 0.6121,
"sd_y_est2": 0.6098,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1164758,
"ldsc_nsnp_merge_regression_ld": 1164758,
"ldsc_observed_scale_h2_beta": 0.0824,
"ldsc_observed_scale_h2_se": 0.1943,
"ldsc_intercept_beta": 0.9956,
"ldsc_intercept_se": 0.0064,
"ldsc_lambda_gc": 0.9974,
"ldsc_mean_chisq": 0.9997,
"ldsc_ratio": 14.6667
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| is_snpid_non_unique | FALSE |
| 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 | TRUE |
| 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 betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.n: Maximum value of reported sample size across all SNPs, \(n\).n_clumped_hits: Number of clumped hits.n_snps: Number of SNPsn_p_sig: Number of SNPs with pvalue below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations 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 expectratio_se_nto 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 ofdiffand the mean ofdiff2(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<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).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: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_mean_chisq< 0.7.n_p_sig:n_p_sig> 1000.miss_<*>:n_miss_<*>/n_snps> 0.01.ldsc_ratio:ldsc_ratio> 0.5ldsc_intercept_beta:ldsc_intercept_beta> 1.5n_clumped_hits:n_clumped_hits> 1000r2_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 | 42 | 0 | 2384143 | 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 | 8.530246e+00 | 5.635316e+00 | 1.0000e+00 | 4.000000e+00 | 8.000000e+00 | 1.200000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.909721e+07 | 5.561986e+07 | 6.6890e+03 | 3.297386e+07 | 7.051994e+07 | 1.144775e+08 | 2.492107e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -4.930000e-05 | 2.799890e-02 | -3.0380e-01 | -1.548600e-02 | -1.043000e-04 | 1.538800e-02 | 3.132400e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.546010e-02 | 1.162710e-02 | 1.5132e-02 | 1.817500e-02 | 2.082000e-02 | 2.774000e-02 | 1.041400e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.005438e-01 | 2.884659e-01 | 1.6000e-06 | 2.516599e-01 | 5.005806e-01 | 7.503105e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.005438e-01 | 2.884659e-01 | 1.6000e-06 | 2.516580e-01 | 5.005737e-01 | 7.503124e-01 | 9.999999e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.669931e-01 | 2.674549e-01 | 1.0001e-02 | 1.361700e-01 | 3.076400e-01 | 5.639600e-01 | 9.899970e-01 | ▇▅▃▃▂ |
| numeric | AF_reference | 18971 | 0.9920428 | NA | NA | NA | NA | NA | 3.693874e-01 | 2.519939e-01 | 1.9970e-04 | 1.563500e-01 | 3.115020e-01 | 5.531150e-01 | 1.000000e+00 | ▇▇▅▃▂ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.469000e+03 | 0.000000e+00 | 2.4690e+03 | 2.469000e+03 | 2.469000e+03 | 2.469000e+03 | 2.469000e+03 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 721290 | rs12565286 | G | C | 0.054489 | 0.038348 | 0.1553499 | 0.1553434 | 0.056538 | 0.0371406 | 2469 |
| 1 | 723819 | rs11804171 | T | A | 0.055577 | 0.038541 | 0.1493001 | 0.1492959 | 0.058873 | 0.1345850 | 2469 |
| 1 | 723891 | rs2977670 | G | C | -0.055552 | 0.038543 | 0.1494999 | 0.1495001 | 0.941096 | 0.7799520 | 2469 |
| 1 | 753541 | rs2073813 | G | A | 0.012364 | 0.024686 | 0.6164601 | 0.6164762 | 0.143960 | 0.3019170 | 2469 |
| 1 | 754192 | rs3131968 | A | G | -0.012242 | 0.024702 | 0.6201803 | 0.6201855 | 0.856120 | 0.6785140 | 2469 |
| 1 | 761732 | rs2286139 | C | T | -0.012325 | 0.024461 | 0.6143601 | 0.6143574 | 0.855130 | 0.6257990 | 2469 |
| 1 | 775659 | rs2905035 | A | G | -0.014478 | 0.024794 | 0.5592603 | 0.5592663 | 0.857630 | 0.7450080 | 2469 |
| 1 | 777122 | rs2980319 | A | T | -0.011351 | 0.024697 | 0.6457806 | 0.6457958 | 0.859790 | 0.7472040 | 2469 |
| 1 | 779322 | rs4040617 | A | G | 0.016286 | 0.024834 | 0.5119600 | 0.5119564 | 0.144460 | 0.2264380 | 2469 |
| 1 | 780785 | rs2977612 | T | A | -0.017269 | 0.024848 | 0.4870696 | 0.4870644 | 0.854070 | 0.6693290 | 2469 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51217134 | rs117417021 | A | G | -0.0442130 | 0.018264 | 0.0154860 | 0.0154875 | 0.405890 | 0.2671730 | 2469 |
| 22 | 51219006 | rs28729663 | G | A | -0.0131850 | 0.026356 | 0.6168804 | 0.6168881 | 0.127210 | 0.2052720 | 2469 |
| 22 | 51222100 | rs114553188 | G | T | 0.0285480 | 0.040431 | 0.4801302 | 0.4801310 | 0.053706 | 0.0880591 | 2469 |
| 22 | 51223637 | rs375798137 | G | A | 0.0285880 | 0.040574 | 0.4810697 | 0.4810660 | 0.053599 | 0.0788738 | 2469 |
| 22 | 51229805 | rs9616985 | T | C | -0.0251480 | 0.036756 | 0.4938499 | 0.4938567 | 0.068942 | 0.0730831 | 2469 |
| 23 | 35921591 | rs2204667 | C | G | -0.0215260 | 0.023918 | 0.3681196 | 0.3681247 | 0.162960 | NA | 2469 |
| 23 | 51666786 | rs14115 | A | G | -0.0587830 | 0.038023 | 0.1221099 | 0.1221081 | 0.053998 | NA | 2469 |
| 23 | 70163799 | rs1626496 | A | C | -0.0040789 | 0.034357 | 0.9055001 | 0.9054963 | 0.076281 | NA | 2469 |
| 23 | 91415872 | rs6562597 | G | A | -0.0488110 | 0.068295 | 0.4748003 | 0.4747893 | 0.018714 | 0.0021192 | 2469 |
| 23 | 118495837 | rs12882977 | G | A | -0.0044951 | 0.016921 | 0.7905002 | 0.7905071 | 0.510980 | 0.2307280 | 2469 |
bcf preview
1 721290 rs12565286 G C . PASS AF=0.056538 ES:SE:LP:AF:SS:ID 0.054489:0.038348:0.808689:0.056538:2469:rs12565286
1 723819 rs11804171 T A . PASS AF=0.058873 ES:SE:LP:AF:SS:ID 0.055577:0.038541:0.82594:0.058873:2469:rs11804171
1 723891 rs2977670 G C . PASS AF=0.941096 ES:SE:LP:AF:SS:ID -0.055552:0.038543:0.825359:0.941096:2469:rs2977670
1 753541 rs2073813 G A . PASS AF=0.14396 ES:SE:LP:AF:SS:ID 0.012364:0.024686:0.210095:0.14396:2469:rs2073813
1 754192 rs3131968 A G . PASS AF=0.85612 ES:SE:LP:AF:SS:ID -0.012242:0.024702:0.207482:0.85612:2469:rs3131968
1 761732 rs2286139 C T . PASS AF=0.85513 ES:SE:LP:AF:SS:ID -0.012325:0.024461:0.211577:0.85513:2469:rs2286139
1 775659 rs2905035 A G . PASS AF=0.85763 ES:SE:LP:AF:SS:ID -0.014478:0.024794:0.252386:0.85763:2469:rs2905035
1 777122 rs2980319 A T . PASS AF=0.85979 ES:SE:LP:AF:SS:ID -0.011351:0.024697:0.189915:0.85979:2469:rs2980319
1 779322 rs4040617 A G . PASS AF=0.14446 ES:SE:LP:AF:SS:ID 0.016286:0.024834:0.290764:0.14446:2469:rs4040617
1 780785 rs2977612 T A . PASS AF=0.85407 ES:SE:LP:AF:SS:ID -0.017269:0.024848:0.312409:0.85407:2469:rs2977612
1 785050 rs2905062 G A . PASS AF=0.84977 ES:SE:LP:AF:SS:ID -0.019988:0.024778:0.376906:0.84977:2469:rs2905062
1 785989 rs2980300 T C . PASS AF=0.83656 ES:SE:LP:AF:SS:ID -0.028481:0.023553:0.644798:0.83656:2469:rs2980300
1 798959 rs11240777 G A . PASS AF=0.20078 ES:SE:LP:AF:SS:ID 0.010292:0.02133:0.201039:0.20078:2469:rs11240777
1 888659 rs3748597 T C . PASS AF=0.942387 ES:SE:LP:AF:SS:ID -0.034644:0.037286:0.452459:0.942387:2469:rs3748597
1 918573 rs2341354 A G . PASS AF=0.57202 ES:SE:LP:AF:SS:ID -0.0064156:0.017325:0.148045:0.57202:2469:rs2341354
1 926431 rs4970403 A T . PASS AF=0.952919 ES:SE:LP:AF:SS:ID -0.046474:0.040415:0.601747:0.952919:2469:rs4970403
1 947034 rs2465126 G A . PASS AF=0.946664 ES:SE:LP:AF:SS:ID -0.07589:0.037955:1.34145:0.946664:2469:rs2465126
1 949608 rs1921 G A . PASS AF=0.38946 ES:SE:LP:AF:SS:ID -0.013428:0.017971:0.342046:0.38946:2469:rs1921
1 990380 rs3121561 C T . PASS AF=0.30058 ES:SE:LP:AF:SS:ID -0.016026:0.019463:0.386909:0.30058:2469:rs3121561
1 990417 rs2465136 T C . PASS AF=0.30844 ES:SE:LP:AF:SS:ID -0.01452:0.018924:0.353665:0.30844:2469:rs2465136
1 990517 rs2710872 C T . PASS AF=0.85366 ES:SE:LP:AF:SS:ID -0.030705:0.026794:0.59891:0.85366:2469:rs2710872
1 1003629 rs4075116 C T . PASS AF=0.72056 ES:SE:LP:AF:SS:ID 0.0055593:0.019729:0.108959:0.72056:2469:rs4075116
1 1017170 rs3766193 C G . PASS AF=0.54869 ES:SE:LP:AF:SS:ID -0.0040307:0.018371:0.0828465:0.54869:2469:rs3766193
1 1017197 rs3766192 C T . PASS AF=0.54869 ES:SE:LP:AF:SS:ID -0.0040544:0.018368:0.0833882:0.54869:2469:rs3766192
1 1018562 rs9442371 C T . PASS AF=0.55711 ES:SE:LP:AF:SS:ID -0.0047948:0.017942:0.102769:0.55711:2469:rs9442371
1 1018704 rs9442372 A G . PASS AF=0.5553 ES:SE:LP:AF:SS:ID -0.003842:0.017981:0.0805035:0.5553:2469:rs9442372
1 1030565 rs6687776 C T . PASS AF=0.14928 ES:SE:LP:AF:SS:ID -0.033879:0.026842:0.684281:0.14928:2469:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.1494 ES:SE:LP:AF:SS:ID -0.033855:0.026811:0.684702:0.1494:2469:rs6678318
1 1036959 rs11579015 T C . PASS AF=0.11891 ES:SE:LP:AF:SS:ID -0.026884:0.02775:0.478012:0.11891:2469:rs11579015
1 1039098 rs11260595 C A . PASS AF=0.022821 ES:SE:LP:AF:SS:ID -0.035361:0.058431:0.263556:0.022821:2469:rs11260595
1 1040026 rs6671356 T C . PASS AF=0.14687 ES:SE:LP:AF:SS:ID -0.032432:0.026138:0.668229:0.14687:2469:rs6671356
1 1041700 rs6604968 A G . PASS AF=0.14858 ES:SE:LP:AF:SS:ID -0.039799:0.024627:0.974366:0.14858:2469:rs6604968
1 1046164 rs6666280 C T . PASS AF=0.13816 ES:SE:LP:AF:SS:ID -0.030875:0.025965:0.630024:0.13816:2469:rs6666280
1 1048955 rs4970405 A G . PASS AF=0.11641 ES:SE:LP:AF:SS:ID -0.022207:0.027269:0.381502:0.11641:2469:rs4970405
1 1049950 rs12726255 A G . PASS AF=0.13679 ES:SE:LP:AF:SS:ID -0.029615:0.026039:0.592762:0.13679:2469:rs12726255
1 1053452 rs4970409 G A . PASS AF=0.11622 ES:SE:LP:AF:SS:ID -0.02305:0.027593:0.394146:0.11622:2469:rs4970409
1 1060608 rs17160824 G A . PASS AF=0.12301 ES:SE:LP:AF:SS:ID -0.024306:0.028217:0.410039:0.12301:2469:rs17160824
1 1061115 rs17160826 T C . PASS AF=0.1144 ES:SE:LP:AF:SS:ID -0.023918:0.028213:0.40168:0.1144:2469:rs17160826
1 1061152 rs12748370 T C . PASS AF=0.11436 ES:SE:LP:AF:SS:ID -0.023956:0.028227:0.402239:0.11436:2469:rs12748370
1 1097335 rs9442385 T G . PASS AF=0.927939 ES:SE:LP:AF:SS:ID -0.0025978:0.034122:0.0271911:0.927939:2469:rs9442385
1 1099342 rs9660710 A C . PASS AF=0.929744 ES:SE:LP:AF:SS:ID -0.0025203:0.035641:0.0251983:0.929744:2469:rs9660710
1 1121794 rs11260549 G A . PASS AF=0.10397 ES:SE:LP:AF:SS:ID -0.035968:0.03062:0.619554:0.10397:2469:rs11260549
1 1124663 rs6684820 G A . PASS AF=0.24037 ES:SE:LP:AF:SS:ID -0.033377:0.02212:0.881636:0.24037:2469:rs6684820
1 1125553 rs10907174 A T . PASS AF=0.19271 ES:SE:LP:AF:SS:ID -0.039071:0.022395:1.09129:0.19271:2469:rs10907174
1 1129672 rs11260554 G T . PASS AF=0.1047 ES:SE:LP:AF:SS:ID -0.03512:0.028288:0.668735:0.1047:2469:rs11260554
1 1130727 rs10907175 A C . PASS AF=0.090629 ES:SE:LP:AF:SS:ID -0.035546:0.029803:0.632663:0.090629:2469:rs10907175
1 1135242 rs9729550 A C . PASS AF=0.24703 ES:SE:LP:AF:SS:ID -0.032281:0.022244:0.83354:0.24703:2469:rs9729550
1 1156131 rs2887286 T C . PASS AF=0.16132 ES:SE:LP:AF:SS:ID 0.004652:0.023737:0.0733386:0.16132:2469:rs2887286
1 1158277 rs3813199 G A . PASS AF=0.095561 ES:SE:LP:AF:SS:ID -0.039421:0.029406:0.744583:0.095561:2469:rs3813199
1 1158631 rs6603781 A G . PASS AF=0.88715 ES:SE:LP:AF:SS:ID 0.010849:0.02738:0.159938:0.88715:2469:rs6603781