IEU GWAS information

Trait: Wellbeing.

name	value
author	Howe LJ
consortium	Within family GWAS consortium
subcategory	NA
category	NA
build	HG19/GRCh37
population	European
trait	Wellbeing
sex	Males and Females
group_name	public
year	2022
unit	SD
id	ieu-b-4851
ontology	EFO:0007869
note	Sibling estimate
sample_size	22656

Report information

name	value
gwas_id	ieu-b-4851
bcf_file	ieu-b-4851.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2022-01-05 18:34 UTC
build_version	master-74213fc-2021-03-26

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 /data/cromwell-executions/qc/46f4242e-21e7-40de-b7eb-f7a1711f61bc/call-ldsc/inputs/-261044418/ieu-b-4851.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4851/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Wed Jan  5 18:21:01 2022
Reading summary statistics from /data/cromwell-executions/qc/46f4242e-21e7-40de-b7eb-f7a1711f61bc/call-ldsc/inputs/-261044418/ieu-b-4851.vcf.gz ...
Read summary statistics for 7464957 SNPs.
Dropped 36368 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, 1191073 SNPs remain.
After merging with regression SNP LD, 1191073 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0353 (0.0211)
Lambda GC: 1.0291
Mean Chi^2: 1.0212
Intercept: 1.0058 (0.0063)
Ratio: 0.276 (0.296)
Analysis finished at Wed Jan  5 18:22:41 2022
Total time elapsed: 1.0m:40.13s

QC metrics

Metrics

{
    "af_correlation": "NA",
    "inflation_factor": 1.0326,
    "mean_EFFECT": 0,
    "n": 22656,
    "n_snps": 7465013,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 252389,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 7465013,
    "n_miss_AF_reference": 148441,
    "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": 1191073,
    "ldsc_nsnp_merge_regression_ld": 1191073,
    "ldsc_observed_scale_h2_beta": 0.0353,
    "ldsc_observed_scale_h2_se": 0.0211,
    "ldsc_intercept_beta": 1.0058,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0291,
    "ldsc_mean_chisq": 1.0212,
    "ldsc_ratio": 0.2736
}

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 between AF and AF_reference.
inflation_factor (lambda): Genomic inflation factor.
mean_EFFECT: Mean of EFFECT size.
n: Maximum value of reported sample size across all SNPs, \(n\).
n_clumped_hits: Number of clumped hits.
n_snps: Number of SNPs
n_p_sig: Number of SNPs with pvalue below 5e-8.
n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
n_ns: Number of SNPs with nonsense values:
- alleles other than A, C, G or T.
- P-values < 0 or > 1.
- negative or infinite standard errors (<= 0 or = Infinity).
- infinite beta estimates or allele frequencies < 0 or > 1.
n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
n_miss_<*>: Number of NA observations 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 expect ratio_se_n to 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 of diff and the mean of diff2 (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<*>: r2 statistics under various assumptions
- 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
- 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: NOT is_snpid_unique.
mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
n_p_sig: n_p_sig > 1000.
miss_<*>: n_miss_<*> / n_snps > 0.01.
ldsc_ratio: ldsc_ratio > 0.5
ldsc_intercept_beta: ldsc_intercept_beta > 1.5
n_clumped_hits: n_clumped_hits > 1000
r2_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	0.9999983	3	58	0	7464896	0	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.0000000	1	43	0	14895	0	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
character	ALT	0	1.0000000	1	44	0	5389	0	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
logical	AF	7465013	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	8.646251e+00	5.753221e+00	1.0000e+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	7.898340e+07	5.636960e+07	3.0200e+02	3.269918e+07	6.968910e+07	1.147299e+08	2.492223e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	1.590000e-05	1.945470e-02	-2.1510e-01	-9.800000e-03	0.000000e+00	9.900000e-03	2.256000e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	1.696680e-02	9.131000e-03	7.2000e-03	1.030000e-02	1.310000e-02	2.040000e-02	6.150000e-02	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	4.953704e-01	2.892897e-01	1.0000e-07	2.440001e-01	4.931000e-01	7.460003e-01	1.000000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	4.953727e-01	2.892963e-01	1.0000e-07	2.440399e-01	4.932271e-01	7.460822e-01	1.000000e+00	▇▇▇▇▇
numeric	AF_reference	148441	0.9801151	NA	NA	NA	NA	NA	NA	NA	2.779184e-01	2.510102e-01	1.9970e-04	7.208470e-02	1.968850e-01	4.309110e-01	1.000000e+00	▇▃▂▂▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	NA	NA	2.071999e+04	2.438943e+03	1.4206e+04	2.008300e+04	2.129300e+04	2.265600e+04	2.265600e+04	▁▁▁▁▇

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	797440	rs58013264	T	C	-0.0124	0.0150	0.4081004	0.4084260	NA	0.189497	18190
1	798400	rs10900604	A	G	-0.0066	0.0127	0.6019993	0.6032831	NA	0.410543	18190
1	798959	rs11240777	G	A	-0.0009	0.0123	0.9390000	0.9416703	NA	0.409944	19400
1	801467	rs61768212	G	C	-0.0120	0.0150	0.4245003	0.4237108	NA	0.193091	18190
1	804759	rs7526310	C	T	-0.0099	0.0150	0.5087003	0.5092538	NA	0.193890	18190
1	808223	rs4951933	G	C	-0.0030	0.0133	0.8193001	0.8215406	NA	0.452077	15720
1	808631	rs11240779	G	A	0.0053	0.0122	0.6663003	0.6639790	NA	0.453474	18190
1	808928	rs11240780	C	T	0.0049	0.0122	0.6908997	0.6879495	NA	0.452276	18190
1	845274	rs112856858	G	T	0.0056	0.0142	0.6942006	0.6933107	NA	0.374002	15720
1	845635	rs117086422	C	T	0.0079	0.0126	0.5329003	0.5306696	NA	0.158546	19400

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
22	51177257	rs73174437	C	T	-0.0104	0.0286	0.7146000	0.7161296	NA	0.0091853	19674
22	51178607	rs6010067	G	C	-0.0729	0.0373	0.0505603	0.0506511	NA	0.0814696	15720
22	51180878	rs6010069	A	G	0.0231	0.0143	0.1051001	0.1062274	NA	0.1589460	16019
22	51180959	rs6010070	A	G	0.0231	0.0143	0.1044999	0.1062274	NA	0.2056710	16019
22	51181685	rs34756634	G	A	-0.0126	0.0164	0.4430003	0.4423133	NA	0.7118610	16019
22	51181687	rs9616955	A	T	0.0192	0.0230	0.4034001	0.4038401	NA	0.0485224	15720
22	51181759	rs13056621	A	G	0.0099	0.0145	0.4948004	0.4947594	NA	0.6761180	20774
22	51182090	rs28516879	G	A	0.0047	0.0190	0.8056001	0.8046231	NA	0.0467252	20475
22	51185848	rs3865764	G	A	-0.0024	0.0260	0.9272000	0.9264536	NA	0.9776360	18599
22	51188319	rs139620215	T	C	-0.0360	0.0466	0.4389004	0.4397993	NA	0.0037939	14800

bcf preview

1   797440  rs58013264  T   C   .   PASS    .   ES:SE:LP:SS:ID  -0.0124:0.015:0.389233:18190:rs58013264
1   798400  rs10900604  A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0066:0.0127:0.220404:18190:rs10900604
1   798959  rs11240777  G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0009:0.0123:0.0273344:19400:rs11240777
1   801467  rs61768212  G   C   .   PASS    .   ES:SE:LP:SS:ID  -0.012:0.015:0.372122:18190:rs61768212
1   804759  rs7526310   C   T   .   PASS    .   ES:SE:LP:SS:ID  -0.0099:0.015:0.293538:18190:rs7526310
1   808223  rs1557576983    G   C   .   PASS    .   ES:SE:LP:SS:ID  -0.003:0.0133:0.086557:15720:rs1557576983
1   808631  rs11240779  G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0053:0.0122:0.17633:18190:rs11240779
1   808928  rs1247187939    C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0049:0.0122:0.160585:18190:rs1247187939
1   845274  rs1324283754    G   T   .   PASS    .   ES:SE:LP:SS:ID  0.0056:0.0142:0.158515:15720:rs1324283754
1   845635  rs117086422 C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0079:0.0126:0.273354:19400:rs117086422
1   845938  rs57760052  G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0112:0.0126:0.429924:19400:rs57760052
1   846078  rs778265812 C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0069:0.0132:0.222863:19400:rs778265812
1   846236  rs138796872 G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0442:0.0414:0.543027:14800:rs138796872
1   846398  rs58781670  G   A   .   PASS    .   ES:SE:LP:SS:ID  0.008:0.0128:0.275642:19400:rs58781670
1   846465  rs60454217  C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0616:0.0396:0.922269:14800:rs60454217
1   846543  rs79396034  G   T   .   PASS    .   ES:SE:LP:SS:ID  0.0652:0.041:0.951558:14800:rs79396034
1   846808  rs4475691   C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0074:0.0131:0.2423:19400:rs4475691
1   846864  rs1269142199    G   C   .   PASS    .   ES:SE:LP:SS:ID  0.0075:0.0132:0.244583:19400:rs1269142199
1   847228  rs3905286   C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0046:0.0129:0.142848:19400:rs3905286
1   847491  rs1158719307    G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0031:0.0128:0.0918368:19400:rs1158719307
1   848090  rs4246505   G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0031:0.0128:0.0923737:19400:rs4246505
1   848445  rs1156895099    G   A   .   PASS    .   ES:SE:LP:SS:ID  0.004:0.0128:0.120961:19400:rs1156895099
1   848456  rs11507767  A   G   .   PASS    .   ES:SE:LP:SS:ID  0.0041:0.0128:0.126098:19400:rs11507767
1   848738  rs3829741   C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0029:0.0128:0.0869283:19400:rs3829741
1   850062  rs28723578  A   T   .   PASS    .   ES:SE:LP:SS:ID  0.0036:0.0128:0.107182:19400:rs28723578
1   850123  rs28622257  C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0031:0.0128:0.0916222:19400:rs28622257
1   851190  rs28609852  G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0039:0.0128:0.119472:19400:rs28609852
1   851204  rs28552953  G   C   .   PASS    .   ES:SE:LP:SS:ID  0.0043:0.0127:0.132827:19400:rs28552953
1   852664  rs28605311  C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0081:0.0129:0.276791:19400:rs28605311
1   852758  rs4970462   G   C   .   PASS    .   ES:SE:LP:SS:ID  0.0083:0.0129:0.285167:19400:rs4970462
1   853239  rs4970380   A   G   .   PASS    .   ES:SE:LP:SS:ID  0.0089:0.0129:0.309715:19400:rs4970380
1   853805  rs3748591   C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0055:0.0355:0.0566539:14800:rs3748591
1   854250  rs7537756   A   G   .   PASS    .   ES:SE:LP:SS:ID  0.0088:0.0129:0.307065:19400:rs7537756
1   854429  rs72902552  G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0055:0.0355:0.0566539:14800:rs72902552
1   856436  rs34105146  TG  T   .   PASS    .   ES:SE:LP:SS:ID  0.0042:0.0146:0.110642:15720:rs34105146
1   856476  rs4040605   A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0062:0.0109:0.242984:18190:rs4040605
1   857177  rs386627408 T   C   .   PASS    .   ES:SE:LP:SS:ID  0.0213:0.0351:0.2648:14800:rs386627408
1   858040  rs4970460   C   A   .   PASS    .   ES:SE:LP:SS:ID  0.0157:0.013:0.643974:18190:rs4970460
1   858051  rs4970459   C   T   .   PASS    .   ES:SE:LP:SS:ID  0.0155:0.013:0.636764:18190:rs4970459
1   858801  rs7418179   A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0142:0.0125:0.59159:18190:rs7418179
1   859685  rs111572704 G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0079:0.0143:0.238448:15720:rs111572704
1   859913  rs1187056171    A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0545:0.0379:0.821887:14800:rs1187056171
1   860416  rs61464428  G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0165:0.0125:0.723768:18190:rs61464428
1   860461  rs57465118  G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0125:0.0342:0.146302:14800:rs57465118
1   860521  rs57924093  C   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0125:0.0342:0.146302:14800:rs57924093
1   860688  rs60837925  G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0163:0.0125:0.715118:18190:rs60837925
1   861008  rs28521172  G   C   .   PASS    .   ES:SE:LP:SS:ID  -0.0125:0.0342:0.146302:14800:rs28521172
1   861630  rs2879816   G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0162:0.0125:0.705975:18190:rs2879816
1   861808  rs13302982  A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0125:0.0342:0.146302:14800:rs13302982
1   862093  rs1210451934    T   C   .   PASS    .   ES:SE:LP:SS:ID  -0.0125:0.0342:0.146302:14800:rs1210451934

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bcf preview