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-1018/ieu-a-1018.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-1018/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 09:21:15 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1018/ieu-a-1018.vcf.gz ...
Read summary statistics for 2263928 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, 1105888 SNPs remain.
After merging with regression SNP LD, 1105888 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0377 (0.0032)
Lambda GC: 1.1301
Mean Chi^2: 1.149
Intercept: 1.0038 (0.0075)
Ratio: 0.0256 (0.0503)
Analysis finished at Wed Feb 5 09:21:41 2020
Total time elapsed: 25.77sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9183,
"inflation_factor": 1.1391,
"mean_EFFECT": -0,
"n": 197164,
"n_snps": 2263928,
"n_clumped_hits": 1,
"n_p_sig": 14,
"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": 15037,
"n_est": 195588.0655,
"ratio_se_n": 0.996,
"mean_diff": -4.6801e-07,
"ratio_diff": 0.5335,
"sd_y_est1": 1.0196,
"sd_y_est2": 1.0155,
"r2_sum1": 0.0002,
"r2_sum2": 0.0002,
"r2_sum3": 0.0002,
"r2_sum4": 0.0002,
"ldsc_nsnp_merge_refpanel_ld": 1105888,
"ldsc_nsnp_merge_regression_ld": 1105888,
"ldsc_observed_scale_h2_beta": 0.0377,
"ldsc_observed_scale_h2_se": 0.0032,
"ldsc_intercept_beta": 1.0038,
"ldsc_intercept_se": 0.0075,
"ldsc_lambda_gc": 1.1301,
"ldsc_mean_chisq": 1.149,
"ldsc_ratio": 0.0255
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | FALSE |
| 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 | 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 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 | 1.000000 | 3 | 34 | 0 | 2263928 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.000000 | NA | NA | NA | NA | NA | 8.623502e+00 | 5.658804e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.200000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.000000 | NA | NA | NA | NA | NA | 7.883976e+07 | 5.560505e+07 | 1.15230e+04 | 3.280921e+07 | 7.041973e+07 | 1.144224e+08 | 2.492107e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.000000 | NA | NA | NA | NA | NA | -2.670000e-05 | 5.068700e-03 | -4.95650e-02 | -3.052100e-03 | -2.130000e-05 | 2.983400e-03 | 4.987180e-02 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.000000 | NA | NA | NA | NA | NA | 4.497300e-03 | 1.608400e-03 | 3.18500e-03 | 3.382700e-03 | 3.843800e-03 | 4.971500e-03 | 1.285000e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.000000 | NA | NA | NA | NA | NA | 4.785754e-01 | 2.943086e-01 | 0.00000e+00 | 2.184002e-01 | 4.716002e-01 | 7.333005e-01 | 1.000000e+00 | ▇▇▇▆▆ |
| numeric | PVAL_ztest | 0 | 1.000000 | NA | NA | NA | NA | NA | 4.785708e-01 | 2.943082e-01 | 0.00000e+00 | 2.183231e-01 | 4.715251e-01 | 7.331038e-01 | 1.000000e+00 | ▇▇▆▆▆ |
| numeric | AF | 0 | 1.000000 | NA | NA | NA | NA | NA | 3.723611e-01 | 2.602597e-01 | 3.11000e-02 | 1.462000e-01 | 3.131000e-01 | 5.650000e-01 | 9.685000e-01 | ▇▅▃▃▂ |
| numeric | AF_reference | 15037 | 0.993358 | NA | NA | NA | NA | NA | 3.729425e-01 | 2.479638e-01 | 1.99700e-04 | 1.649360e-01 | 3.168930e-01 | 5.539140e-01 | 9.956070e-01 | ▇▇▅▃▂ |
| numeric | N | 0 | 1.000000 | NA | NA | NA | NA | NA | 1.858425e+05 | 1.536059e+04 | 1.00005e+05 | 1.828150e+05 | 1.911720e+05 | 1.963770e+05 | 1.971640e+05 | ▁▁▁▁▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 752566 | rs3094315 | G | A | -0.0010416 | 0.0052876 | 0.8438000 | 0.8438274 | 0.8357 | 0.7182510 | 130248 |
| 1 | 754192 | rs3131968 | A | G | -0.0057597 | 0.0054337 | 0.2891998 | 0.2891449 | 0.8609 | 0.6785140 | 141415 |
| 1 | 777122 | rs2980319 | A | T | 0.0045673 | 0.0057162 | 0.4240001 | 0.4242904 | 0.8661 | 0.7472040 | 131948 |
| 1 | 779322 | rs4040617 | A | G | -0.0050763 | 0.0059722 | 0.3953002 | 0.3953247 | 0.1326 | 0.2264380 | 121883 |
| 1 | 780785 | rs2977612 | T | A | 0.0031168 | 0.0056362 | 0.5803995 | 0.5802635 | 0.8614 | 0.6693290 | 131833 |
| 1 | 785989 | rs2980300 | T | C | 0.0040114 | 0.0055560 | 0.4702004 | 0.4702949 | 0.8565 | 0.6269970 | 131784 |
| 1 | 798801 | rs12132517 | G | A | 0.0175438 | 0.0075849 | 0.0207300 | 0.0207225 | 0.0861 | 0.0740815 | 110452 |
| 1 | 798959 | rs11240777 | G | A | 0.0138124 | 0.0048652 | 0.0045300 | 0.0045254 | 0.2099 | 0.4099440 | 127371 |
| 1 | 846864 | rs950122 | G | C | -0.0064969 | 0.0055625 | 0.2429003 | 0.2428070 | 0.1870 | 0.2228430 | 106293 |
| 1 | 882033 | rs2272756 | G | A | -0.0058095 | 0.0050386 | 0.2491002 | 0.2489110 | 0.2460 | 0.1367810 | 106180 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51162059 | rs10451 | G | A | 0.0007307 | 0.0036175 | 0.8400000 | 0.8399167 | 0.3076 | 0.3865810 | 179391 |
| 22 | 51163138 | rs715586 | C | T | -0.0047492 | 0.0049113 | 0.3335001 | 0.3335447 | 0.1466 | 0.0902556 | 165686 |
| 22 | 51165664 | rs8137951 | G | A | -0.0000477 | 0.0036718 | 0.9895000 | 0.9896278 | 0.3065 | 0.4063500 | 174472 |
| 22 | 51171497 | rs2301584 | G | A | -0.0120105 | 0.0046953 | 0.0105300 | 0.0105279 | 0.1743 | 0.2533950 | 157589 |
| 22 | 51171693 | rs756638 | G | A | 0.0025076 | 0.0041516 | 0.5457001 | 0.5458434 | 0.2672 | 0.3049120 | 148154 |
| 22 | 51173542 | rs4824147 | T | C | -0.0005823 | 0.0097055 | 0.9522001 | 0.9521556 | 0.9484 | 0.9812300 | 108466 |
| 22 | 51175626 | rs3810648 | A | G | 0.0104493 | 0.0075500 | 0.1664999 | 0.1663572 | 0.0580 | 0.1084270 | 160543 |
| 22 | 51178090 | rs2285395 | G | A | 0.0152591 | 0.0080269 | 0.0573099 | 0.0573023 | 0.0542 | 0.0666933 | 151383 |
| 22 | 51196164 | rs8136603 | A | T | 0.0121166 | 0.0083390 | 0.1461999 | 0.1462236 | 0.0564 | 0.1427720 | 135105 |
| 22 | 51212875 | rs2238837 | A | C | -0.0022357 | 0.0042184 | 0.5959996 | 0.5961122 | 0.3486 | 0.3724040 | 123738 |
bcf preview
1 752566 rs3094315 G A . PASS AF=0.8357 ES:SE:LP:AF:SS:ID -0.00104165:0.00528756:0.0737605:0.8357:130248:rs3094315
1 754192 rs3131968 A G . PASS AF=0.8609 ES:SE:LP:AF:SS:ID -0.00575974:0.00543372:0.538802:0.8609:141415:rs3131968
1 777122 rs2980319 A T . PASS AF=0.8661 ES:SE:LP:AF:SS:ID 0.00456726:0.00571622:0.372634:0.8661:131948:rs2980319
1 779322 rs4040617 A G . PASS AF=0.1326 ES:SE:LP:AF:SS:ID -0.00507634:0.00597216:0.403073:0.1326:121883:rs4040617
1 780785 rs2977612 T A . PASS AF=0.8614 ES:SE:LP:AF:SS:ID 0.00311684:0.00563624:0.236273:0.8614:131833:rs2977612
1 785989 rs2980300 T C . PASS AF=0.8565 ES:SE:LP:AF:SS:ID 0.00401145:0.00555603:0.327717:0.8565:131784:rs2980300
1 798801 rs12132517 G A . PASS AF=0.0861 ES:SE:LP:AF:SS:ID 0.0175438:0.00758486:1.6834:0.0861:110452:rs12132517
1 798959 rs11240777 G A . PASS AF=0.2099 ES:SE:LP:AF:SS:ID 0.0138124:0.00486522:2.3439:0.2099:127371:rs11240777
1 846864 rs950122 G C . PASS AF=0.187 ES:SE:LP:AF:SS:ID -0.00649695:0.00556246:0.614572:0.187:106293:rs950122
1 882033 rs2272756 G A . PASS AF=0.246 ES:SE:LP:AF:SS:ID -0.00580951:0.00503861:0.603626:0.246:106180:rs2272756
1 962210 rs3128126 A G . PASS AF=0.4092 ES:SE:LP:AF:SS:ID -0.00376451:0.00398783:0.461929:0.4092:130053:rs3128126
1 990380 rs3121561 C T . PASS AF=0.2912 ES:SE:LP:AF:SS:ID -0.00459273:0.00415256:0.570894:0.2912:140483:rs3121561
1 998501 rs3813193 G C . PASS AF=0.1654 ES:SE:LP:AF:SS:ID 0.00374415:0.00481253:0.360016:0.1654:156390:rs3813193
1 1003629 rs4075116 C T . PASS AF=0.7284 ES:SE:LP:AF:SS:ID 0.00386263:0.0039135:0.489723:0.7284:165021:rs4075116
1 1005806 rs3934834 C T . PASS AF=0.1531 ES:SE:LP:AF:SS:ID 0.00101884:0.00478328:0.080399:0.1531:168543:rs3934834
1 1017170 rs3766193 C G . PASS AF=0.5513 ES:SE:LP:AF:SS:ID 0.00450661:0.00357951:0.681728:0.5513:157753:rs3766193
1 1017197 rs3766192 C T . PASS AF=0.5525 ES:SE:LP:AF:SS:ID 0.00406391:0.0035711:0.59329:0.5525:158577:rs3766192
1 1017587 rs3766191 C T . PASS AF=0.148 ES:SE:LP:AF:SS:ID 0.000194562:0.00498877:0.0136762:0.148:159324:rs3766191
1 1018562 rs9442371 C T . PASS AF=0.5635 ES:SE:LP:AF:SS:ID 0.00369679:0.00342613:0.552222:0.5635:173175:rs9442371
1 1018704 rs9442372 A G . PASS AF=0.5658 ES:SE:LP:AF:SS:ID 0.00388866:0.00342915:0.590574:0.5658:173079:rs9442372
1 1021346 rs10907177 A G . PASS AF=0.1534 ES:SE:LP:AF:SS:ID -5.2977e-05:0.00481609:0.00375109:0.1534:165988:rs10907177
1 1021415 rs3737728 A G . PASS AF=0.7195 ES:SE:LP:AF:SS:ID 0.00360317:0.00386192:0.455064:0.7195:166112:rs3737728
1 1021695 rs9442398 A G . PASS AF=0.7219 ES:SE:LP:AF:SS:ID 0.00439015:0.00382751:0.599462:0.7219:170004:rs9442398
1 1022037 rs6701114 C T . PASS AF=0.5603 ES:SE:LP:AF:SS:ID 0.0043551:0.00355518:0.656198:0.5603:160572:rs6701114
1 1026707 rs4074137 C A . PASS AF=0.6021 ES:SE:LP:AF:SS:ID 0.00766495:0.003739:1.39383:0.6021:149285:rs4074137
1 1030565 rs6687776 C T . PASS AF=0.1596 ES:SE:LP:AF:SS:ID -0.00421784:0.00460463:0.44418:0.1596:175817:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.1587 ES:SE:LP:AF:SS:ID -0.00503298:0.00477512:0.534766:0.1587:164238:rs6678318
1 1031540 rs9651273 A G . PASS AF=0.728 ES:SE:LP:AF:SS:ID -0.00111962:0.00419333:0.102483:0.728:143599:rs9651273
1 1036959 rs11579015 T C . PASS AF=0.1081 ES:SE:LP:AF:SS:ID -0.00979313:0.00546492:1.13602:0.1081:173644:rs11579015
1 1040026 rs6671356 T C . PASS AF=0.1367 ES:SE:LP:AF:SS:ID -0.00404548:0.00497599:0.380698:0.1367:171112:rs6671356
1 1046164 rs6666280 C T . PASS AF=0.1343 ES:SE:LP:AF:SS:ID -0.00417709:0.00489121:0.405718:0.1343:179760:rs6666280
1 1048955 rs4970405 A G . PASS AF=0.1041 ES:SE:LP:AF:SS:ID -0.00952975:0.00534478:1.12761:0.1041:187672:rs4970405
1 1049950 rs12726255 A G . PASS AF=0.1356 ES:SE:LP:AF:SS:ID -0.00524057:0.0048167:0.557991:0.1356:183864:rs12726255
1 1053452 rs4970409 G A . PASS AF=0.1079 ES:SE:LP:AF:SS:ID -0.010525:0.00534807:1.30892:0.1079:181610:rs4970409
1 1060174 rs7548798 C T . PASS AF=0.2918 ES:SE:LP:AF:SS:ID 0.00205312:0.00397122:0.218101:0.2918:153419:rs7548798
1 1060608 rs17160824 G A . PASS AF=0.1125 ES:SE:LP:AF:SS:ID -0.0111909:0.00528372:1.46674:0.1125:179378:rs17160824
1 1061115 rs17160826 T C . PASS AF=0.1084 ES:SE:LP:AF:SS:ID -0.0106096:0.00533684:1.32938:0.1084:181636:rs17160826
1 1061166 rs11807848 T C . PASS AF=0.4019 ES:SE:LP:AF:SS:ID -0.00360699:0.00364711:0.49147:0.4019:156379:rs11807848
1 1062638 rs9442373 C A . PASS AF=0.5523 ES:SE:LP:AF:SS:ID 0.00377828:0.00361212:0.52959:0.5523:154983:rs9442373
1 1064535 rs6682475 G C . PASS AF=0.7351 ES:SE:LP:AF:SS:ID 0.000406865:0.00419448:0.0347983:0.7351:145944:rs6682475
1 1064979 rs2298217 C T . PASS AF=0.1477 ES:SE:LP:AF:SS:ID -0.00870289:0.00480292:1.15459:0.1477:172181:rs2298217
1 1066029 rs12145826 G A . PASS AF=0.0686 ES:SE:LP:AF:SS:ID -0.0074276:0.00834562:0.427593:0.0686:112355:rs12145826
1 1066403 rs10907182 T C . PASS AF=0.5945 ES:SE:LP:AF:SS:ID 0.00599046:0.00385734:0.919013:0.5945:139396:rs10907182
1 1071118 rs10907183 G C . PASS AF=0.6063 ES:SE:LP:AF:SS:ID 0.00500114:0.00387686:0.705313:0.6063:139366:rs10907183
1 1077064 rs4970357 C A . PASS AF=0.9092 ES:SE:LP:AF:SS:ID 0.00266982:0.00662487:0.162917:0.9092:137997:rs4970357
1 1079198 rs11260603 T C . PASS AF=0.2544 ES:SE:LP:AF:SS:ID 0.000479354:0.00479354:0.0361178:0.2544:114719:rs11260603
1 1087683 rs9442380 T C . PASS AF=0.9237 ES:SE:LP:AF:SS:ID -0.000628838:0.00668976:0.0336705:0.9237:158523:rs9442380
1 1089262 rs4970358 A G . PASS AF=0.9578 ES:SE:LP:AF:SS:ID -0.0134005:0.0106522:0.680894:0.9578:109019:rs4970358
1 1094738 rs4970362 A G . PASS AF=0.6359 ES:SE:LP:AF:SS:ID 0.00135093:0.00420851:0.126215:0.6359:121928:rs4970362
1 1097335 rs9442385 T G . PASS AF=0.9308 ES:SE:LP:AF:SS:ID -0.00530626:0.00675097:0.364617:0.9308:170324:rs9442385