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-975/ieu-a-975.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-975/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 13:23:08 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-975/ieu-a-975.vcf.gz ...
Read summary statistics for 2476247 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, 1149625 SNPs remain.
After merging with regression SNP LD, 1149625 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.4461 (0.1527)
Lambda GC: 1.0536
Mean Chi^2: 1.0533
Intercept: 1.0231 (0.0072)
Ratio: 0.4337 (0.1353)
Analysis finished at Wed Feb 5 13:23:37 2020
Total time elapsed: 28.8sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9231,
"inflation_factor": 1.0536,
"mean_EFFECT": -0.0176,
"n": 3440,
"n_snps": 2476247,
"n_clumped_hits": 5,
"n_p_sig": 37,
"n_mono": 0,
"n_ns": 0,
"n_mac": 3060,
"is_snpid_unique": true,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 21816,
"n_est": 3301.0532,
"ratio_se_n": 0.9796,
"mean_diff": 0.0179,
"ratio_diff": 2.4201,
"sd_y_est1": 2.5248,
"sd_y_est2": 2.4733,
"r2_sum1": 0.5814,
"r2_sum2": 0.0912,
"r2_sum3": 0.095,
"r2_sum4": 0.0911,
"ldsc_nsnp_merge_refpanel_ld": 1149625,
"ldsc_nsnp_merge_regression_ld": 1149625,
"ldsc_observed_scale_h2_beta": 0.4461,
"ldsc_observed_scale_h2_se": 0.1527,
"ldsc_intercept_beta": 1.0231,
"ldsc_intercept_se": 0.0072,
"ldsc_lambda_gc": 1.0536,
"ldsc_mean_chisq": 1.0533,
"ldsc_ratio": 0.4334
}
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 | FALSE |
| ldsc_intercept_beta | FALSE |
| n_clumped_hits | FALSE |
| r2_sum1 | TRUE |
| 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 | 2476247 | 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 | 8.584600e+00 | 5.657027e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.200000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.884028e+07 | 5.562474e+07 | 1.15230e+04 | 3.273665e+07 | 7.026486e+07 | 1.142718e+08 | 2.492190e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -1.758630e-02 | 2.662777e+00 | -1.18439e+03 | -5.808790e-02 | -5.961000e-04 | 5.723560e-02 | 5.039100e+02 | ▁▁▁▇▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.315430e-01 | 3.529911e+00 | 5.64327e-02 | 6.309140e-02 | 7.437970e-02 | 1.040970e-01 | 1.656080e+03 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.920437e-01 | 2.904509e-01 | 0.00000e+00 | 2.387011e-01 | 4.887199e-01 | 7.432279e-01 | 9.999995e-01 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.920437e-01 | 2.904509e-01 | 0.00000e+00 | 2.387010e-01 | 4.887204e-01 | 7.432271e-01 | 9.999995e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.559136e-01 | 2.743192e-01 | 7.40000e-05 | 1.193410e-01 | 2.905950e-01 | 5.550965e-01 | 9.998370e-01 | ▇▅▃▂▂ |
| numeric | AF_reference | 21816 | 0.9911899 | NA | NA | NA | NA | NA | 3.594016e-01 | 2.569564e-01 | 0.00000e+00 | 1.433710e-01 | 2.965260e-01 | 5.441290e-01 | 1.000000e+00 | ▇▆▃▃▂ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.440000e+03 | 0.000000e+00 | 3.44000e+03 | 3.440000e+03 | 3.440000e+03 | 3.440000e+03 | 3.440000e+03 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 990380 | rs3121561 | C | T | 0.0816460 | 0.1104030 | 0.4595873 | 0.4595870 | 0.262664 | 0.343450 | 3440 |
| 1 | 998501 | rs3813193 | G | C | 0.0645522 | 0.1064640 | 0.5442958 | 0.5442964 | 0.146845 | 0.206669 | 3440 |
| 1 | 1003629 | rs4075116 | C | T | 0.0725206 | 0.0887344 | 0.4137700 | 0.4137700 | 0.739102 | 0.720647 | 3440 |
| 1 | 1005806 | rs3934834 | C | T | 0.0804861 | 0.1011320 | 0.4261181 | 0.4261181 | 0.118590 | 0.223442 | 3440 |
| 1 | 1017170 | rs3766193 | C | G | 0.0378451 | 0.0830196 | 0.6484926 | 0.6484925 | 0.579002 | 0.575479 | 3440 |
| 1 | 1017197 | rs3766192 | C | T | 0.0061301 | 0.0779217 | 0.9372950 | 0.9372949 | 0.591508 | 0.511182 | 3440 |
| 1 | 1017587 | rs3766191 | C | T | 0.0943685 | 0.1035170 | 0.3619670 | 0.3619671 | 0.119725 | 0.171126 | 3440 |
| 1 | 1018562 | rs9442371 | C | T | 0.0070513 | 0.0760054 | 0.9260832 | 0.9260832 | 0.600375 | 0.530152 | 3440 |
| 1 | 1018704 | rs9442372 | A | G | 0.0071790 | 0.0758893 | 0.9246334 | 0.9246334 | 0.600449 | 0.611022 | 3440 |
| 1 | 1021346 | rs10907177 | A | G | 0.1011160 | 0.1049230 | 0.3351884 | 0.3351882 | 0.124165 | 0.178914 | 3440 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51217134 | rs117417021 | A | G | -0.0154340 | 0.0963451 | 0.8727276 | 0.8727275 | 0.4318760 | 0.2671730 | 3440 |
| 22 | 51222100 | rs114553188 | G | T | -0.0715586 | 0.1622750 | 0.6592346 | 0.6592339 | 0.0557900 | 0.0880591 | 3440 |
| 22 | 51223637 | rs375798137 | G | A | -0.0712887 | 0.1626140 | 0.6611013 | 0.6611020 | 0.0557943 | 0.0788738 | 3440 |
| 22 | 51229805 | rs9616985 | T | C | 0.1370370 | 0.1764430 | 0.4373569 | 0.4373568 | 0.0977022 | 0.0730831 | 3440 |
| 23 | 35921591 | rs2204667 | C | G | -0.0649111 | 0.0812655 | 0.4244338 | 0.4244334 | 0.1600480 | NA | 3440 |
| 23 | 51666786 | rs14115 | A | G | -0.1747920 | 0.1475510 | 0.2361674 | 0.2361674 | 0.0455450 | NA | 3440 |
| 23 | 70163799 | rs1626496 | A | C | -0.1428860 | 0.1145820 | 0.2123905 | 0.2123903 | 0.0796844 | NA | 3440 |
| 23 | 74963352 | rs1053838 | T | G | 1.2609800 | 0.6947310 | 0.0695136 | 0.0695143 | 0.9938960 | NA | 3440 |
| 23 | 91415872 | rs6562597 | G | A | 0.2175080 | 0.1949890 | 0.2646409 | 0.2646411 | 0.0231880 | 0.0021192 | 3440 |
| 23 | 118495837 | rs12882977 | G | A | 0.0808755 | 0.0597397 | 0.1758009 | 0.1758008 | 0.5000910 | 0.2307280 | 3440 |
bcf preview
1 990380 rs3121561 C T . PASS AF=0.262664 ES:SE:LP:AF:SS:ID 0.081646:0.110403:0.337632:0.262664:3440:rs3121561
1 998501 rs3813193 G C . PASS AF=0.146845 ES:SE:LP:AF:SS:ID 0.0645522:0.106464:0.264165:0.146845:3440:rs3813193
1 1003629 rs4075116 C T . PASS AF=0.739102 ES:SE:LP:AF:SS:ID 0.0725206:0.0887344:0.383241:0.739102:3440:rs4075116
1 1005806 rs3934834 C T . PASS AF=0.11859 ES:SE:LP:AF:SS:ID 0.0804861:0.101132:0.37047:0.11859:3440:rs3934834
1 1017170 rs3766193 C G . PASS AF=0.579002 ES:SE:LP:AF:SS:ID 0.0378451:0.0830196:0.188095:0.579002:3440:rs3766193
1 1017197 rs3766192 C T . PASS AF=0.591508 ES:SE:LP:AF:SS:ID 0.00613012:0.0779217:0.0281237:0.591508:3440:rs3766192
1 1017587 rs3766191 C T . PASS AF=0.119725 ES:SE:LP:AF:SS:ID 0.0943685:0.103517:0.441331:0.119725:3440:rs3766191
1 1018562 rs9442371 C T . PASS AF=0.600375 ES:SE:LP:AF:SS:ID 0.00705132:0.0760054:0.03335:0.600375:3440:rs9442371
1 1018704 rs9442372 A G . PASS AF=0.600449 ES:SE:LP:AF:SS:ID 0.00717905:0.0758893:0.0340304:0.600449:3440:rs9442372
1 1021346 rs10907177 A G . PASS AF=0.124165 ES:SE:LP:AF:SS:ID 0.101116:0.104923:0.474711:0.124165:3440:rs10907177
1 1021415 rs3737728 A G . PASS AF=0.727737 ES:SE:LP:AF:SS:ID 0.0638627:0.068247:0.45668:0.727737:3440:rs3737728
1 1021583 rs10907178 A C . PASS AF=0.123991 ES:SE:LP:AF:SS:ID 0.101849:0.105057:0.478452:0.123991:3440:rs10907178
1 1021695 rs9442398 A G . PASS AF=0.732802 ES:SE:LP:AF:SS:ID 0.0743434:0.0721022:0.519272:0.732802:3440:rs9442398
1 1022037 rs6701114 C T . PASS AF=0.571694 ES:SE:LP:AF:SS:ID 0.0449646:0.0709219:0.278948:0.571694:3440:rs6701114
1 1026707 rs4074137 C A . PASS AF=0.601282 ES:SE:LP:AF:SS:ID 0.0872499:0.0641778:0.759482:0.601282:3440:rs4074137
1 1030565 rs6687776 C T . PASS AF=0.152328 ES:SE:LP:AF:SS:ID 0.0719889:0.0825132:0.416845:0.152328:3440:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.152323 ES:SE:LP:AF:SS:ID 0.0719706:0.0825506:0.416464:0.152323:3440:rs6678318
1 1031540 rs9651273 A G . PASS AF=0.717223 ES:SE:LP:AF:SS:ID 0.116564:0.0671409:1.08331:0.717223:3440:rs9651273
1 1036959 rs11579015 T C . PASS AF=0.100754 ES:SE:LP:AF:SS:ID -0.0156522:0.0997855:0.0578151:0.100754:3440:rs11579015
1 1040026 rs6671356 T C . PASS AF=0.132136 ES:SE:LP:AF:SS:ID -0.030453:0.0933615:0.128261:0.132136:3440:rs6671356
1 1046164 rs6666280 C T . PASS AF=0.124374 ES:SE:LP:AF:SS:ID -0.0315123:0.0924464:0.134777:0.124374:3440:rs6666280
1 1048955 rs4970405 A G . PASS AF=0.100755 ES:SE:LP:AF:SS:ID -0.0162991:0.0996749:0.0604274:0.100755:3440:rs4970405
1 1049950 rs12726255 A G . PASS AF=0.128893 ES:SE:LP:AF:SS:ID -0.000423253:0.0893431:0.00164469:0.128893:3440:rs12726255
1 1053452 rs4970409 G A . PASS AF=0.105209 ES:SE:LP:AF:SS:ID 0.0291477:0.0976168:0.116196:0.105209:3440:rs4970409
1 1060174 rs7548798 C T . PASS AF=0.34541 ES:SE:LP:AF:SS:ID -0.10353:0.0860037:0.640786:0.34541:3440:rs7548798
1 1060235 rs7540009 G A . PASS AF=0.0234057 ES:SE:LP:AF:SS:ID -0.137959:0.218853:0.276996:0.0234057:3440:rs7540009
1 1060608 rs17160824 G A . PASS AF=0.114485 ES:SE:LP:AF:SS:ID 0.0359432:0.0977418:0.146868:0.114485:3440:rs17160824
1 1061115 rs17160826 T C . PASS AF=0.104984 ES:SE:LP:AF:SS:ID 0.031501:0.0978332:0.12641:0.104984:3440:rs17160826
1 1061152 rs12748370 T C . PASS AF=0.102919 ES:SE:LP:AF:SS:ID 0.0541785:0.0988467:0.233871:0.102919:3440:rs12748370
1 1061166 rs11807848 T C . PASS AF=0.432344 ES:SE:LP:AF:SS:ID -0.070977:0.0772865:0.445597:0.432344:3440:rs11807848
1 1062015 rs9659914 C T . PASS AF=0.02217 ES:SE:LP:AF:SS:ID -0.180195:0.234924:0.353537:0.02217:3440:rs9659914
1 1062638 rs9442373 C A . PASS AF=0.522643 ES:SE:LP:AF:SS:ID 0.00839321:0.073931:0.0411437:0.522643:3440:rs9442373
1 1064535 rs6682475 G C . PASS AF=0.722851 ES:SE:LP:AF:SS:ID -0.115208:0.0906393:0.690993:0.722851:3440:rs6682475
1 1064979 rs2298217 C T . PASS AF=0.142078 ES:SE:LP:AF:SS:ID 0.118882:0.0832168:0.814955:0.142078:3440:rs2298217
1 1066403 rs10907182 T C . PASS AF=0.623929 ES:SE:LP:AF:SS:ID 0.0337957:0.0746169:0.186683:0.623929:3440:rs10907182
1 1071118 rs10907183 G C . PASS AF=0.638753 ES:SE:LP:AF:SS:ID 0.0456219:0.0780827:0.252562:0.638753:3440:rs10907183
1 1077064 rs4970357 C A . PASS AF=0.920661 ES:SE:LP:AF:SS:ID -0.233598:0.142857:0.991358:0.920661:3440:rs4970357
1 1079198 rs11260603 T C . PASS AF=0.227765 ES:SE:LP:AF:SS:ID -0.180568:0.0893498:1.36362:0.227765:3440:rs11260603
1 1087683 rs9442380 T C . PASS AF=0.903566 ES:SE:LP:AF:SS:ID -0.159323:0.120855:0.727222:0.903566:3440:rs9442380
1 1089262 rs4970358 A G . PASS AF=0.952334 ES:SE:LP:AF:SS:ID -0.224386:0.152095:0.853464:0.952334:3440:rs4970358
1 1094738 rs4970362 A G . PASS AF=0.645268 ES:SE:LP:AF:SS:ID 0.0638415:0.061141:0.528111:0.645268:3440:rs4970362
1 1097335 rs9442385 T G . PASS AF=0.933709 ES:SE:LP:AF:SS:ID -0.14891:0.116185:0.699055:0.933709:3440:rs9442385
1 1099342 rs9660710 A C . PASS AF=0.934349 ES:SE:LP:AF:SS:ID -0.149312:0.115093:0.71103:0.934349:3440:rs9660710
1 1100217 rs1891905 C T . PASS AF=0.957777 ES:SE:LP:AF:SS:ID -0.0740144:0.180484:0.166381:0.957777:3440:rs1891905
1 1106473 rs4970420 G A . PASS AF=0.135621 ES:SE:LP:AF:SS:ID -0.0742715:0.11426:0.287621:0.135621:3440:rs4970420
1 1119858 rs1320565 C T . PASS AF=0.075663 ES:SE:LP:AF:SS:ID -0.0126246:0.11282:0.0405282:0.075663:3440:rs1320565
1 1120431 rs1320571 G A . PASS AF=0.0329327 ES:SE:LP:AF:SS:ID 0.17923:0.187016:0.471241:0.0329327:3440:rs1320571
1 1121014 rs3813204 G A . PASS AF=0.105349 ES:SE:LP:AF:SS:ID -0.105423:0.101892:0.521678:0.105349:3440:rs3813204
1 1121794 rs11260549 G A . PASS AF=0.112683 ES:SE:LP:AF:SS:ID -0.119494:0.0956967:0.674106:0.112683:3440:rs11260549
1 1124663 rs6684820 G A . PASS AF=0.250425 ES:SE:LP:AF:SS:ID 0.00197936:0.0682056:0.0101729:0.250425:3440:rs6684820