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/91a9ed6f-9ed6-4d96-be2c-6022ec01048a/call-vcf/inputs/-2071043035/upload.txt.gz --id bbj-a-102 --json /data/cromwell-executions/qc/91a9ed6f-9ed6-4d96-be2c-6022ec01048a/call-vcf/inputs/-2071043035/bbj-a-102_data.json --ref /data/cromwell-executions/qc/91a9ed6f-9ed6-4d96-be2c-6022ec01048a/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/91a9ed6f-9ed6-4d96-be2c-6022ec01048a/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/bbj-a-102/bbj-a-102.vcf.gz --alias alias.txt; 1.3.0",
"file_date": "2020-11-20T17:33:22.136926",
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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/91a9ed6f-9ed6-4d96-be2c-6022ec01048a/call-ldsc/inputs/-2071043035/bbj-a-102.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/bbj-a-102/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Fri Nov 20 17:44:36 2020
Reading summary statistics from /data/cromwell-executions/qc/91a9ed6f-9ed6-4d96-be2c-6022ec01048a/call-ldsc/inputs/-2071043035/bbj-a-102.vcf.gz ...
Read summary statistics for 0 SNPs.
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.
Traceback (most recent call last):
File "./ldsc/ldsc.py", line 647, in <module>
sumstats.estimate_h2(args, log)
File "/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
args, log, args.h2)
File "/ldsc/ldscore/sumstats.py", line 252, in _read_ld_sumstats
sumstats = _merge_and_log(ref_ld, sumstats, 'reference panel LD', log)
File "/ldsc/ldscore/sumstats.py", line 238, in _merge_and_log
raise ValueError(msg.format(N=len(sumstats), F=noun))
ValueError: After merging with reference panel LD, 0 SNPs remain.
Analysis finished at Fri Nov 20 17:45:24 2020
Total time elapsed: 47.59sQC metrics
Metrics
Metrics
{
"af_correlation": 0.911,
"inflation_factor": 1.014,
"mean_EFFECT": -0.0009,
"n": "-Inf",
"n_snps": 8872152,
"n_clumped_hits": 12,
"n_p_sig": 441,
"n_mono": 0,
"n_ns": 822038,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 17303,
"n_est": "NA",
"ratio_se_n": "NA",
"mean_diff": "NaN",
"ratio_diff": "NaN",
"sd_y_est1": "NA",
"sd_y_est2": "NA",
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 0,
"ldsc_nsnp_merge_regression_ld": "NA",
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": "NA",
"ldsc_intercept_se": "NA",
"ldsc_lambda_gc": "NA",
"ldsc_mean_chisq": "NA",
"ldsc_ratio": "NA"
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | NA |
| n_p_sig | FALSE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | NA |
| ldsc_intercept_beta | NA |
| 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 | 4 | 0.9999995 | 3 | 12 | 0 | 8870975 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 99 | 0 | 37224 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 23996 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 8872152 | 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 | 8.838036e+00 | 6.011729e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.946180e+07 | 5.554818e+07 | 7914.0000000 | 3.374429e+07 | 7.079028e+07 | 1.147656e+08 | 2.492139e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -8.990000e-04 | 1.318202e-01 | -3.6282200 | -2.483430e-02 | -3.209000e-04 | 2.399190e-02 | 6.444410e+00 | ▁▇▁▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.229030e-02 | 1.142172e-01 | 0.0196819 | 2.227550e-02 | 3.037560e-02 | 6.633630e-02 | 5.165310e+00 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.971827e-01 | 2.892748e-01 | 0.0000000 | 2.467954e-01 | 4.970230e-01 | 7.473826e-01 | 9.999999e-01 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.971827e-01 | 2.892748e-01 | 0.0000000 | 2.467952e-01 | 4.970232e-01 | 7.473825e-01 | 9.999999e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.647065e-01 | 2.772434e-01 | 0.0000525 | 2.786860e-02 | 1.604160e-01 | 4.375052e-01 | 9.999480e-01 | ▇▂▂▁▁ |
| numeric | AF_reference | 17303 | 0.9980497 | NA | NA | NA | NA | NA | NA | NA | 2.525843e-01 | 2.494078e-01 | 0.0001997 | 3.833870e-02 | 1.739220e-01 | 4.057510e-01 | 9.998000e-01 | ▇▃▂▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 751343 | rs28544273 | T | A | -0.0618361 | 0.0313462 | 0.0485322 | 0.0485317 | 0.140848 | 0.242612 | NA |
| 1 | 751756 | rs143225517 | T | C | -0.0616366 | 0.0312230 | 0.0483727 | 0.0483730 | 0.140194 | 0.242212 | NA |
| 1 | 752566 | rs3094315 | G | A | 0.0518330 | 0.0270498 | 0.0553388 | 0.0553388 | 0.842147 | 0.718251 | NA |
| 1 | 752894 | rs3131971 | T | C | 0.0587491 | 0.0299330 | 0.0496833 | 0.0496826 | 0.855854 | 0.753195 | NA |
| 1 | 753405 | rs3115860 | C | A | 0.0608501 | 0.0307161 | 0.0475861 | 0.0475858 | 0.856567 | 0.751797 | NA |
| 1 | 753425 | rs3131970 | T | C | 0.0602671 | 0.0304586 | 0.0478542 | 0.0478547 | 0.855256 | 0.749002 | NA |
| 1 | 755890 | rs3115858 | A | T | 0.0619717 | 0.0311571 | 0.0467003 | 0.0467004 | 0.855710 | 0.751398 | NA |
| 1 | 756604 | rs3131962 | A | G | 0.0617065 | 0.0310743 | 0.0470587 | 0.0470586 | 0.853791 | 0.748003 | NA |
| 1 | 757734 | rs4951929 | C | T | 0.0623550 | 0.0313677 | 0.0468263 | 0.0468258 | 0.853211 | 0.748203 | NA |
| 1 | 757936 | rs4951862 | C | A | 0.0624730 | 0.0313707 | 0.0464323 | 0.0464321 | 0.853828 | 0.748802 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154789496 | rs5940513 | A | G | -0.0090115 | 0.0257963 | 0.7268403 | 0.7268402 | 0.7799050 | 0.6378810 | NA |
| 23 | 154803410 | rs368676291 | T | C | -0.0106544 | 0.0269448 | 0.6925370 | 0.6925360 | 0.7587920 | 0.5353640 | NA |
| 23 | 154803411 | rs373288103 | G | A | -0.0106365 | 0.0269528 | 0.6931129 | 0.6931128 | 0.7587980 | 0.5353640 | NA |
| 23 | 154803415 | rs112167337 | A | C | -0.0108697 | 0.0270279 | 0.6875622 | 0.6875619 | 0.7571190 | 0.5345700 | NA |
| 23 | 154803793 | rs5940526 | T | A | -0.0106061 | 0.0270694 | 0.6951956 | 0.6951976 | 0.7566730 | 0.5311260 | NA |
| 23 | 154804301 | rs5940397 | G | A | -0.0095652 | 0.0273845 | 0.7268688 | 0.7268692 | 0.7724110 | 0.6442380 | NA |
| 23 | 154805102 | rs12834147 | G | C | -0.0096639 | 0.0274965 | 0.7252454 | 0.7252446 | 0.7678120 | 0.6360260 | NA |
| 23 | 154805911 | rs2890132 | G | A | -0.0099928 | 0.0275617 | 0.7169321 | 0.7169317 | 0.7693250 | 0.6378810 | NA |
| 23 | 154812754 | rs183018361 | G | T | 0.1729140 | 0.2988040 | 0.5628012 | 0.5628004 | 0.0013019 | 0.0230464 | NA |
| 23 | 154821956 | rs5940536 | G | A | 0.1409040 | 0.2778030 | 0.6120093 | 0.6120086 | 0.0012706 | 0.0389404 | NA |
bcf preview
1 751343 rs28544273 T A . PASS AF=0.140848 ES:SE:LP:AF:ID -0.0618361:0.0313462:1.31397:0.140848:rs28544273
1 751756 rs28527770 T C . PASS AF=0.140194 ES:SE:LP:AF:ID -0.0616366:0.031223:1.3154:0.140194:rs28527770
1 752566 rs3094315 G A . PASS AF=0.842147 ES:SE:LP:AF:ID 0.051833:0.0270498:1.25697:0.842147:rs3094315
1 752894 rs3131971 T C . PASS AF=0.855854 ES:SE:LP:AF:ID 0.0587491:0.029933:1.30379:0.855854:rs3131971
1 753405 rs3115860 C A . PASS AF=0.856567 ES:SE:LP:AF:ID 0.0608501:0.0307161:1.32252:0.856567:rs3115860
1 753425 rs1431026348 T C . PASS AF=0.855256 ES:SE:LP:AF:ID 0.0602671:0.0304586:1.32008:0.855256:rs1431026348
1 755890 rs1280367067 A T . PASS AF=0.85571 ES:SE:LP:AF:ID 0.0619717:0.0311571:1.33068:0.85571:rs1280367067
1 756604 rs3131962 A G . PASS AF=0.853791 ES:SE:LP:AF:ID 0.0617065:0.0310743:1.32736:0.853791:rs3131962
1 757734 rs1557551770 C T . PASS AF=0.853211 ES:SE:LP:AF:ID 0.062355:0.0313677:1.32951:0.853211:rs1557551770
1 757936 rs1360886751 C A . PASS AF=0.853828 ES:SE:LP:AF:ID 0.062473:0.0313707:1.33318:0.853828:rs1360886751
1 758144 rs3131956 A G . PASS AF=0.848637 ES:SE:LP:AF:ID 0.0604825:0.0304582:1.32734:0.848637:rs3131956
1 758626 rs3131954 C T . PASS AF=0.854402 ES:SE:LP:AF:ID 0.0636201:0.0319052:1.33585:0.854402:rs3131954
1 759837 rs3115851 T A . PASS AF=0.854024 ES:SE:LP:AF:ID 0.064853:0.032349:1.34693:0.854024:rs3115851
1 760912 rs1048488 C T . PASS AF=0.842422 ES:SE:LP:AF:ID 0.0607806:0.0307497:1.318:0.842422:rs1048488
1 761147 rs3115850 T C . PASS AF=0.841786 ES:SE:LP:AF:ID 0.0607185:0.0307786:1.31405:0.841786:rs3115850
1 761752 rs1057213 C T . PASS AF=0.850518 ES:SE:LP:AF:ID 0.0656542:0.0326752:1.35158:0.850518:rs1057213
1 845635 rs117086422 C T . PASS AF=0.134869 ES:SE:LP:AF:ID -0.0301747:0.0318639:0.46389:0.134869:rs117086422
1 846078 rs778265812 C T . PASS AF=0.134139 ES:SE:LP:AF:ID -0.0290904:0.0313879:0.450963:0.134139:rs778265812
1 846808 rs4475691 C T . PASS AF=0.142046 ES:SE:LP:AF:ID -0.024034:0.0285629:0.39783:0.142046:rs4475691
1 846864 rs1269142199 G C . PASS AF=0.139955 ES:SE:LP:AF:ID -0.0252653:0.0292245:0.411953:0.139955:rs1269142199
1 847228 rs3905286 C T . PASS AF=0.146723 ES:SE:LP:AF:ID -0.0275764:0.0301744:0.44277:0.146723:rs3905286
1 847491 rs1158719307 G A . PASS AF=0.148421 ES:SE:LP:AF:ID -0.0276246:0.0301775:0.443724:0.148421:rs1158719307
1 848090 rs4246505 G A . PASS AF=0.135231 ES:SE:LP:AF:ID -0.0304643:0.0312178:0.482628:0.135231:rs4246505
1 848445 rs1156895099 G A . PASS AF=0.149813 ES:SE:LP:AF:ID -0.0287165:0.0304252:0.461863:0.149813:rs1156895099
1 848456 rs11507767 A G . PASS AF=0.150256 ES:SE:LP:AF:ID -0.0290933:0.0305279:0.467773:0.150256:rs11507767
1 848654 rs5772026 TG T . PASS AF=0.132458 ES:SE:LP:AF:ID -0.0305533:0.0316011:0.476744:0.132458:rs5772026
1 848738 rs3829741 C T . PASS AF=0.134758 ES:SE:LP:AF:ID -0.0298509:0.0312774:0.468668:0.134758:rs3829741
1 849440 rs79376265 C T . PASS AF=0.144737 ES:SE:LP:AF:ID 0.0482527:0.0335949:0.821268:0.144737:rs79376265
1 849863 rs61620633 G GACTGCCCAGCTC . PASS AF=0.153138 ES:SE:LP:AF:ID -0.0292861:0.0310401:0.461641:0.153138:rs61620633
1 850062 rs28723578 A T . PASS AF=0.150708 ES:SE:LP:AF:ID -0.0290447:0.0307298:0.462715:0.150708:rs28723578
1 850123 rs28622257 C T . PASS AF=0.135747 ES:SE:LP:AF:ID -0.0305208:0.0315312:0.477469:0.135747:rs28622257
1 850528 rs114889920 A G . PASS AF=0.145382 ES:SE:LP:AF:ID 0.0473804:0.0330955:0.817442:0.145382:rs114889920
1 851030 rs1284752010 G C . PASS AF=0.142079 ES:SE:LP:AF:ID 0.047943:0.0329741:0.835775:0.142079:rs1284752010
1 851190 rs28609852 G A . PASS AF=0.149116 ES:SE:LP:AF:ID -0.0303351:0.0311986:0.480316:0.149116:rs28609852
1 851204 rs28552953 G C . PASS AF=0.15968 ES:SE:LP:AF:ID -0.0312275:0.0314944:0.492915:0.15968:rs28552953
1 852664 rs28605311 C T . PASS AF=0.139485 ES:SE:LP:AF:ID -0.032442:0.0319057:0.5097:0.139485:rs28605311
1 852758 rs4970462 G C . PASS AF=0.13456 ES:SE:LP:AF:ID -0.0320822:0.0320111:0.499988:0.13456:rs4970462
1 853239 rs4970380 A G . PASS AF=0.13546 ES:SE:LP:AF:ID -0.0321793:0.0320657:0.500863:0.13546:rs4970380
1 853488 rs77644389 G A . PASS AF=0.148017 ES:SE:LP:AF:ID 0.0453702:0.0320302:0.805112:0.148017:rs77644389
1 854168 rs79188446 C T . PASS AF=0.148635 ES:SE:LP:AF:ID 0.0449389:0.0317886:0.802839:0.148635:rs79188446
1 855635 rs77712898 CCTT C . PASS AF=0.149954 ES:SE:LP:AF:ID 0.0438838:0.0312056:0.796855:0.149954:rs77712898
1 855774 rs77595185 G A . PASS AF=0.150248 ES:SE:LP:AF:ID 0.043727:0.031129:0.795583:0.150248:rs77595185
1 856436 rs34105146 TG T . PASS AF=0.118773 ES:SE:LP:AF:ID -0.037321:0.0358823:0.525353:0.118773:rs34105146
1 857177 rs386627408 T C . PASS AF=0.439536 ES:SE:LP:AF:ID 0.0338433:0.0217598:0.921282:0.439536:rs386627408
1 857318 rs144110716 G GGAGT . PASS AF=0.150605 ES:SE:LP:AF:ID 0.0425504:0.029925:0.809515:0.150605:rs144110716
1 857443 rs56663360 C T . PASS AF=0.174129 ES:SE:LP:AF:ID 0.0421327:0.0301081:0.791292:0.174129:rs56663360
1 858040 rs4970460 C A . PASS AF=0.151939 ES:SE:LP:AF:ID -0.0421813:0.033141:0.692301:0.151939:rs4970460
1 858051 rs4970459 C T . PASS AF=0.153871 ES:SE:LP:AF:ID -0.0416632:0.032836:0.6893:0.153871:rs4970459
1 858149 rs77520260 C T . PASS AF=0.150395 ES:SE:LP:AF:ID 0.0414139:0.0293671:0.800034:0.150395:rs77520260
1 858691 rs34628185 TG T . PASS AF=0.401682 ES:SE:LP:AF:ID -0.0184053:0.0221111:0.392349:0.401682:rs34628185