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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"Gwas2VCF_command": "--data /data/cromwell-executions/qc/f75eb69c-5714-45cb-8cdc-8f7a1fc584c5/call-vcf/inputs/-261044511/upload.txt.gz --id ieu-b-4821 --json /data/cromwell-executions/qc/f75eb69c-5714-45cb-8cdc-8f7a1fc584c5/call-vcf/inputs/-261044511/ieu-b-4821_data.json --ref /data/cromwell-executions/qc/f75eb69c-5714-45cb-8cdc-8f7a1fc584c5/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/f75eb69c-5714-45cb-8cdc-8f7a1fc584c5/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4821/ieu-b-4821.vcf.gz --alias alias.txt; 1.3.0",
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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 /data/cromwell-executions/qc/f75eb69c-5714-45cb-8cdc-8f7a1fc584c5/call-ldsc/inputs/-261044511/ieu-b-4821.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4821/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Wed Jan 5 05:48:11 2022
Reading summary statistics from /data/cromwell-executions/qc/f75eb69c-5714-45cb-8cdc-8f7a1fc584c5/call-ldsc/inputs/-261044511/ieu-b-4821.vcf.gz ...
Read summary statistics for 7890197 SNPs.
Dropped 38628 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1196285 SNPs remain.
After merging with regression SNP LD, 1196285 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1895 (0.0416)
Lambda GC: 1.0624
Mean Chi^2: 1.0658
Intercept: 1.0219 (0.007)
Ratio: 0.3336 (0.1063)
Analysis finished at Wed Jan 5 05:49:51 2022
Total time elapsed: 1.0m:40.39sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.0567,
"mean_EFFECT": -0.0002,
"n": 12136,
"n_snps": 7890254,
"n_clumped_hits": 1,
"n_p_sig": 71,
"n_mono": 0,
"n_ns": 284990,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 7890254,
"n_miss_AF_reference": 160925,
"n_est": "NA",
"ratio_se_n": "NA",
"mean_diff": "NaN",
"ratio_diff": "NaN",
"sd_y_est1": "NaN",
"sd_y_est2": "NA",
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1196285,
"ldsc_nsnp_merge_regression_ld": 1196285,
"ldsc_observed_scale_h2_beta": 0.1895,
"ldsc_observed_scale_h2_se": 0.0416,
"ldsc_intercept_beta": 1.0219,
"ldsc_intercept_se": 0.007,
"ldsc_lambda_gc": 1.0624,
"ldsc_mean_chisq": 1.0658,
"ldsc_ratio": 0.3328
}
Flags
| name | value |
|---|---|
| af_correlation | NA |
| 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 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 | logical.mean | logical.count | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 13 | 0.9999984 | 3 | 58 | 0 | 7890130 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 43 | 0 | 16632 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 44 | 0 | 6006 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | AF | 7890254 | 0.0000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.639684e+00 | 5.750321e+00 | 1.000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.897225e+07 | 5.633700e+07 | 3.020e+02 | 3.265911e+07 | 6.965296e+07 | 1.147221e+08 | 2.492223e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.684000e-04 | 4.321760e-02 | -4.623e-01 | -2.120000e-02 | -1.000000e-04 | 2.090000e-02 | 4.164000e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.698570e-02 | 2.101350e-02 | 1.510e-02 | 2.120000e-02 | 2.750000e-02 | 4.680000e-02 | 1.347000e-01 | ▇▂▂▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.914507e-01 | 2.903844e-01 | 0.000e+00 | 2.382001e-01 | 4.881002e-01 | 7.424992e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.914507e-01 | 2.903856e-01 | 0.000e+00 | 2.381626e-01 | 4.880609e-01 | 7.425747e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF_reference | 160925 | 0.9796046 | NA | NA | NA | NA | NA | NA | NA | 2.654996e-01 | 2.521312e-01 | 1.997e-04 | 5.810700e-02 | 1.803120e-01 | 4.145370e-01 | 1.000000e+00 | ▇▃▂▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.113844e+04 | 1.002539e+03 | 7.229e+03 | 1.026100e+04 | 1.132600e+04 | 1.213600e+04 | 1.213600e+04 | ▁▁▃▂▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 797440 | rs58013264 | T | C | -0.0637 | 0.0315 | 0.0434300 | 0.0431534 | NA | 0.189497 | 10249 |
| 1 | 798400 | rs10900604 | A | G | -0.0413 | 0.0266 | 0.1208999 | 0.1205112 | NA | 0.410543 | 10249 |
| 1 | 798959 | rs11240777 | G | A | -0.0419 | 0.0266 | 0.1156999 | 0.1152131 | NA | 0.409944 | 10249 |
| 1 | 801467 | rs61768212 | G | C | -0.0656 | 0.0315 | 0.0372100 | 0.0372932 | NA | 0.193091 | 10249 |
| 1 | 804759 | rs7526310 | C | T | -0.0678 | 0.0315 | 0.0315697 | 0.0313674 | NA | 0.193890 | 10249 |
| 1 | 808223 | rs4951933 | G | C | 0.0315 | 0.0261 | 0.2282002 | 0.2274720 | NA | 0.452077 | 9653 |
| 1 | 808631 | rs11240779 | G | A | 0.0498 | 0.0254 | 0.0502898 | 0.0499222 | NA | 0.453474 | 10249 |
| 1 | 808928 | rs11240780 | C | T | 0.0507 | 0.0254 | 0.0459600 | 0.0459271 | NA | 0.452276 | 10249 |
| 1 | 845274 | rs112856858 | G | T | 0.0611 | 0.0271 | 0.0241002 | 0.0241577 | NA | 0.374002 | 9653 |
| 1 | 845635 | rs117086422 | C | T | 0.0545 | 0.0262 | 0.0377503 | 0.0375115 | NA | 0.158546 | 10249 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51177257 | rs73174437 | C | T | 0.0120 | 0.0593 | 0.8398001 | 0.8396346 | NA | 0.0091853 | 9653 |
| 22 | 51178607 | rs6010067 | G | C | 0.1160 | 0.0714 | 0.1043999 | 0.1042372 | NA | 0.0814696 | 9653 |
| 22 | 51180878 | rs6010069 | A | G | 0.0193 | 0.0276 | 0.4850003 | 0.4843800 | NA | 0.1589460 | 9653 |
| 22 | 51180959 | rs6010070 | A | G | 0.0205 | 0.0276 | 0.4578002 | 0.4576309 | NA | 0.2056710 | 9653 |
| 22 | 51181685 | rs34756634 | G | A | -0.0309 | 0.0307 | 0.3142997 | 0.3141681 | NA | 0.7118610 | 9653 |
| 22 | 51181687 | rs9616955 | A | T | 0.0459 | 0.0432 | 0.2878001 | 0.2880088 | NA | 0.0485224 | 9653 |
| 22 | 51181759 | rs13056621 | A | G | 0.0223 | 0.0308 | 0.4693005 | 0.4690498 | NA | 0.6761180 | 10122 |
| 22 | 51182090 | rs28516879 | G | A | 0.0226 | 0.0385 | 0.5576003 | 0.5571950 | NA | 0.0467252 | 10718 |
| 22 | 51185848 | rs3865764 | G | A | 0.0291 | 0.0524 | 0.5781000 | 0.5786597 | NA | 0.9776360 | 9653 |
| 22 | 51188319 | rs139620215 | T | C | 0.0386 | 0.0976 | 0.6928002 | 0.6924800 | NA | 0.0037939 | 9653 |
bcf preview
1 797440 rs58013264 T C . PASS . ES:SE:LP:SS:ID -0.0637:0.0315:1.36221:10249:rs58013264
1 798400 rs10900604 A G . PASS . ES:SE:LP:SS:ID -0.0413:0.0266:0.917574:10249:rs10900604
1 798959 rs11240777 G A . PASS . ES:SE:LP:SS:ID -0.0419:0.0266:0.936667:10249:rs11240777
1 801467 rs61768212 G C . PASS . ES:SE:LP:SS:ID -0.0656:0.0315:1.42934:10249:rs61768212
1 804759 rs7526310 C T . PASS . ES:SE:LP:SS:ID -0.0678:0.0315:1.50073:10249:rs7526310
1 808223 rs1557576983 G C . PASS . ES:SE:LP:SS:ID 0.0315:0.0261:0.641684:9653:rs1557576983
1 808631 rs11240779 G A . PASS . ES:SE:LP:SS:ID 0.0498:0.0254:1.29852:10249:rs11240779
1 808928 rs1247187939 C T . PASS . ES:SE:LP:SS:ID 0.0507:0.0254:1.33762:10249:rs1247187939
1 845274 rs1324283754 G T . PASS . ES:SE:LP:SS:ID 0.0611:0.0271:1.61798:9653:rs1324283754
1 845635 rs117086422 C T . PASS . ES:SE:LP:SS:ID 0.0545:0.0262:1.42308:10249:rs117086422
1 845938 rs57760052 G A . PASS . ES:SE:LP:SS:ID 0.0534:0.0261:1.38669:10249:rs57760052
1 846078 rs778265812 C T . PASS . ES:SE:LP:SS:ID 0.0636:0.0267:1.75746:10249:rs778265812
1 846398 rs58781670 G A . PASS . ES:SE:LP:SS:ID 0.0548:0.0265:1.41669:10249:rs58781670
1 846465 rs60454217 C T . PASS . ES:SE:LP:SS:ID -0.048:0.0811:0.25649:9653:rs60454217
1 846543 rs79396034 G T . PASS . ES:SE:LP:SS:ID -0.0508:0.0838:0.263922:9653:rs79396034
1 846808 rs4475691 C T . PASS . ES:SE:LP:SS:ID 0.0625:0.0266:1.72423:10249:rs4475691
1 846864 rs1269142199 G C . PASS . ES:SE:LP:SS:ID 0.0658:0.0267:1.86201:10249:rs1269142199
1 847228 rs3905286 C T . PASS . ES:SE:LP:SS:ID 0.0555:0.0261:1.47405:10249:rs3905286
1 847491 rs1158719307 G A . PASS . ES:SE:LP:SS:ID 0.0445:0.0256:1.08492:10249:rs1158719307
1 848090 rs4246505 G A . PASS . ES:SE:LP:SS:ID 0.0464:0.0258:1.14243:10249:rs4246505
1 848445 rs1156895099 G A . PASS . ES:SE:LP:SS:ID 0.0419:0.0258:0.981716:10249:rs1156895099
1 848456 rs11507767 A G . PASS . ES:SE:LP:SS:ID 0.0421:0.0258:0.988853:10249:rs11507767
1 848738 rs3829741 C T . PASS . ES:SE:LP:SS:ID 0.0462:0.0258:1.1365:10249:rs3829741
1 850062 rs28723578 A T . PASS . ES:SE:LP:SS:ID 0.0442:0.0256:1.07248:10249:rs28723578
1 850123 rs28622257 C T . PASS . ES:SE:LP:SS:ID 0.0463:0.0258:1.1405:10249:rs28622257
1 851190 rs28609852 G A . PASS . ES:SE:LP:SS:ID 0.0448:0.0256:1.09453:10249:rs28609852
1 851204 rs28552953 G C . PASS . ES:SE:LP:SS:ID 0.0353:0.0254:0.784362:10249:rs28552953
1 852664 rs28605311 C T . PASS . ES:SE:LP:SS:ID 0.041:0.026:0.938925:10249:rs28605311
1 852758 rs4970462 G C . PASS . ES:SE:LP:SS:ID 0.04:0.026:0.905878:10249:rs4970462
1 853239 rs4970380 A G . PASS . ES:SE:LP:SS:ID 0.0407:0.026:0.930702:10249:rs4970380
1 853805 rs3748591 C T . PASS . ES:SE:LP:SS:ID 0.0139:0.0721:0.0722191:9653:rs3748591
1 854250 rs7537756 A G . PASS . ES:SE:LP:SS:ID 0.04:0.0259:0.913284:10249:rs7537756
1 854429 rs72902552 G A . PASS . ES:SE:LP:SS:ID 0.014:0.0722:0.0727837:9653:rs72902552
1 856436 rs34105146 TG T . PASS . ES:SE:LP:SS:ID 0.0631:0.0273:1.68403:9653:rs34105146
1 856476 rs4040605 A G . PASS . ES:SE:LP:SS:ID 0.0005:0.0219:0.008641:10249:rs4040605
1 857177 rs386627408 T C . PASS . ES:SE:LP:SS:ID 0.0091:0.0716:0.0465303:9653:rs386627408
1 858040 rs4970460 C A . PASS . ES:SE:LP:SS:ID 0.0432:0.0254:1.04939:10249:rs4970460
1 858051 rs4970459 C T . PASS . ES:SE:LP:SS:ID 0.0446:0.0254:1.098:10249:rs4970459
1 858801 rs7418179 A G . PASS . ES:SE:LP:SS:ID -0.0404:0.0248:0.987163:10249:rs7418179
1 859404 rs71509444 C G . PASS . ES:SE:LP:SS:ID 0.0034:0.0712:0.0169152:9653:rs71509444
1 859685 rs111572704 G A . PASS . ES:SE:LP:SS:ID 0.047:0.0265:1.11719:9653:rs111572704
1 859690 rs71509445 C G . PASS . ES:SE:LP:SS:ID 0.0079:0.0765:0.03711:9653:rs71509445
1 859701 rs71509446 C G . PASS . ES:SE:LP:SS:ID 0.0079:0.0765:0.03711:9653:rs71509446
1 859913 rs1187056171 A G . PASS . ES:SE:LP:SS:ID 0.0023:0.0772:0.0103278:9653:rs1187056171
1 860416 rs61464428 G A . PASS . ES:SE:LP:SS:ID -0.0395:0.0248:0.953505:10249:rs61464428
1 860461 rs57465118 G A . PASS . ES:SE:LP:SS:ID -0.0318:0.0697:0.188693:9653:rs57465118
1 860521 rs57924093 C A . PASS . ES:SE:LP:SS:ID -0.0318:0.0697:0.188693:9653:rs57924093
1 860688 rs60837925 G A . PASS . ES:SE:LP:SS:ID -0.0409:0.0248:1.00458:10249:rs60837925
1 860854 rs57816555 T C . PASS . ES:SE:LP:SS:ID 0.0621:0.0836:0.339609:9653:rs57816555
1 861008 rs28521172 G C . PASS . ES:SE:LP:SS:ID -0.0318:0.0697:0.188492:9653:rs28521172