Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

{
    "fileformat": "VCFv4.2",
    "FILTER": "<ID=PASS,Description=\"All filters passed\">",
    "INFO": "<ID=AF,Number=A,Type=Float,Description=\"Allele Frequency\">",
    "FORMAT": "<ID=ES,Number=A,Type=Float,Description=\"Effect size estimate relative to the alternative allele\">",
    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
    "FORMAT.2": "<ID=LP,Number=A,Type=Float,Description=\"-log10 p-value for effect estimate\">",
    "FORMAT.3": "<ID=AF,Number=A,Type=Float,Description=\"Alternate allele frequency in the association study\">",
    "FORMAT.4": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
    "FORMAT.6": "<ID=SI,Number=A,Type=Float,Description=\"Accuracy score of summary data imputation\">",
    "FORMAT.7": "<ID=NC,Number=A,Type=Float,Description=\"Number of cases used to estimate genetic effect\">",
    "FORMAT.8": "<ID=ID,Number=1,Type=String,Description=\"Study variant identifier\">",
    "META": "<ID=TotalVariants,Number=1,Type=Integer,Description=\"Total number of variants in input\">",
    "META.1": "<ID=VariantsNotRead,Number=1,Type=Integer,Description=\"Number of variants that could not be read\">",
    "META.2": "<ID=HarmonisedVariants,Number=1,Type=Integer,Description=\"Total number of harmonised variants\">",
    "META.3": "<ID=VariantsNotHarmonised,Number=1,Type=Integer,Description=\"Total number of variants that could not be harmonised\">",
    "META.4": "<ID=SwitchedAlleles,Number=1,Type=Integer,Description=\"Total number of variants strand switched\">",
    "META.5": "<ID=TotalControls,Number=1,Type=Integer,Description=\"Total number of controls in the association study\">",
    "META.6": "<ID=TotalCases,Number=1,Type=Integer,Description=\"Total number of cases in the association study\">",
    "META.7": "<ID=StudyType,Number=1,Type=String,Description=\"Type of GWAS study [Continuous or CaseControl]\">",
    "SAMPLE": "<ID=UKB-b:1675,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=461545,TotalCases=1388,StudyType=CaseControl>",
    "contig": "<ID=1,length=249250621,assembly=GRCh37>",
    "contig.1": "<ID=2,length=243199373,assembly=GRCh37>",
    "contig.2": "<ID=3,length=198022430,assembly=GRCh37>",
    "contig.3": "<ID=4,length=191154276,assembly=GRCh37>",
    "contig.4": "<ID=5,length=180915260,assembly=GRCh37>",
    "contig.5": "<ID=6,length=171115067,assembly=GRCh37>",
    "contig.6": "<ID=7,length=159138663,assembly=GRCh37>",
    "contig.7": "<ID=8,length=146364022,assembly=GRCh37>",
    "contig.8": "<ID=9,length=141213431,assembly=GRCh37>",
    "contig.9": "<ID=10,length=135534747,assembly=GRCh37>",
    "contig.10": "<ID=11,length=135006516,assembly=GRCh37>",
    "contig.11": "<ID=12,length=133851895,assembly=GRCh37>",
    "contig.12": "<ID=13,length=115169878,assembly=GRCh37>",
    "contig.13": "<ID=14,length=107349540,assembly=GRCh37>",
    "contig.14": "<ID=15,length=102531392,assembly=GRCh37>",
    "contig.15": "<ID=16,length=90354753,assembly=GRCh37>",
    "contig.16": "<ID=17,length=81195210,assembly=GRCh37>",
    "contig.17": "<ID=18,length=78077248,assembly=GRCh37>",
    "contig.18": "<ID=19,length=59128983,assembly=GRCh37>",
    "contig.19": "<ID=20,length=63025520,assembly=GRCh37>",
    "contig.20": "<ID=21,length=48129895,assembly=GRCh37>",
    "contig.21": "<ID=22,length=51304566,assembly=GRCh37>",
    "contig.22": "<ID=X,length=155270560,assembly=GRCh37>",
    "contig.23": "<ID=Y,length=59373566,assembly=GRCh37>",
    "contig.24": "<ID=MT,length=16569,assembly=GRCh37>",
    "contig.25": "<ID=GL000207.1,length=4262,assembly=GRCh37>",
    "contig.26": "<ID=GL000226.1,length=15008,assembly=GRCh37>",
    "contig.27": "<ID=GL000229.1,length=19913,assembly=GRCh37>",
    "contig.28": "<ID=GL000231.1,length=27386,assembly=GRCh37>",
    "contig.29": "<ID=GL000210.1,length=27682,assembly=GRCh37>",
    "contig.30": "<ID=GL000239.1,length=33824,assembly=GRCh37>",
    "contig.31": "<ID=GL000235.1,length=34474,assembly=GRCh37>",
    "contig.32": "<ID=GL000201.1,length=36148,assembly=GRCh37>",
    "contig.33": "<ID=GL000247.1,length=36422,assembly=GRCh37>",
    "contig.34": "<ID=GL000245.1,length=36651,assembly=GRCh37>",
    "contig.35": "<ID=GL000197.1,length=37175,assembly=GRCh37>",
    "contig.36": "<ID=GL000203.1,length=37498,assembly=GRCh37>",
    "contig.37": "<ID=GL000246.1,length=38154,assembly=GRCh37>",
    "contig.38": "<ID=GL000249.1,length=38502,assembly=GRCh37>",
    "contig.39": "<ID=GL000196.1,length=38914,assembly=GRCh37>",
    "contig.40": "<ID=GL000248.1,length=39786,assembly=GRCh37>",
    "contig.41": "<ID=GL000244.1,length=39929,assembly=GRCh37>",
    "contig.42": "<ID=GL000238.1,length=39939,assembly=GRCh37>",
    "contig.43": "<ID=GL000202.1,length=40103,assembly=GRCh37>",
    "contig.44": "<ID=GL000234.1,length=40531,assembly=GRCh37>",
    "contig.45": "<ID=GL000232.1,length=40652,assembly=GRCh37>",
    "contig.46": "<ID=GL000206.1,length=41001,assembly=GRCh37>",
    "contig.47": "<ID=GL000240.1,length=41933,assembly=GRCh37>",
    "contig.48": "<ID=GL000236.1,length=41934,assembly=GRCh37>",
    "contig.49": "<ID=GL000241.1,length=42152,assembly=GRCh37>",
    "contig.50": "<ID=GL000243.1,length=43341,assembly=GRCh37>",
    "contig.51": "<ID=GL000242.1,length=43523,assembly=GRCh37>",
    "contig.52": "<ID=GL000230.1,length=43691,assembly=GRCh37>",
    "contig.53": "<ID=GL000237.1,length=45867,assembly=GRCh37>",
    "contig.54": "<ID=GL000233.1,length=45941,assembly=GRCh37>",
    "contig.55": "<ID=GL000204.1,length=81310,assembly=GRCh37>",
    "contig.56": "<ID=GL000198.1,length=90085,assembly=GRCh37>",
    "contig.57": "<ID=GL000208.1,length=92689,assembly=GRCh37>",
    "contig.58": "<ID=GL000191.1,length=106433,assembly=GRCh37>",
    "contig.59": "<ID=GL000227.1,length=128374,assembly=GRCh37>",
    "contig.60": "<ID=GL000228.1,length=129120,assembly=GRCh37>",
    "contig.61": "<ID=GL000214.1,length=137718,assembly=GRCh37>",
    "contig.62": "<ID=GL000221.1,length=155397,assembly=GRCh37>",
    "contig.63": "<ID=GL000209.1,length=159169,assembly=GRCh37>",
    "contig.64": "<ID=GL000218.1,length=161147,assembly=GRCh37>",
    "contig.65": "<ID=GL000220.1,length=161802,assembly=GRCh37>",
    "contig.66": "<ID=GL000213.1,length=164239,assembly=GRCh37>",
    "contig.67": "<ID=GL000211.1,length=166566,assembly=GRCh37>",
    "contig.68": "<ID=GL000199.1,length=169874,assembly=GRCh37>",
    "contig.69": "<ID=GL000217.1,length=172149,assembly=GRCh37>",
    "contig.70": "<ID=GL000216.1,length=172294,assembly=GRCh37>",
    "contig.71": "<ID=GL000215.1,length=172545,assembly=GRCh37>",
    "contig.72": "<ID=GL000205.1,length=174588,assembly=GRCh37>",
    "contig.73": "<ID=GL000219.1,length=179198,assembly=GRCh37>",
    "contig.74": "<ID=GL000224.1,length=179693,assembly=GRCh37>",
    "contig.75": "<ID=GL000223.1,length=180455,assembly=GRCh37>",
    "contig.76": "<ID=GL000195.1,length=182896,assembly=GRCh37>",
    "contig.77": "<ID=GL000212.1,length=186858,assembly=GRCh37>",
    "contig.78": "<ID=GL000222.1,length=186861,assembly=GRCh37>",
    "contig.79": "<ID=GL000200.1,length=187035,assembly=GRCh37>",
    "contig.80": "<ID=GL000193.1,length=189789,assembly=GRCh37>",
    "contig.81": "<ID=GL000194.1,length=191469,assembly=GRCh37>",
    "contig.82": "<ID=GL000225.1,length=211173,assembly=GRCh37>",
    "contig.83": "<ID=GL000192.1,length=547496,assembly=GRCh37>",
    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_20003_1140888688.vcf.gz --id UKB-b:1675 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20003_1140888688.txt.gz --cohort_cases 1388 --cohort_controls 461545 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
    "file_date": "2019-09-13T04:25:03.464206",
    "bcftools_viewVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
    "bcftools_viewCommand": "view -T ^/mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1675/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1675/UKB-b-1675_raw.vcf.gz; Date=Thu Oct 17 12:34:02 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-1675/ukb-b-1675.vcf.gz; Date=Sun May 10 04:24:39 2020"
}
 

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/public/UKB-b-1675/UKB-b-1675_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1675/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1675/UKB-b-1675_data.vcf.gz ...
Read summary statistics for 2296372 SNPs.
Dropped 251 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 584393 SNPs remain.
After merging with regression SNP LD, 584393 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0003 (0.0012)
Lambda GC: 1.0161
Mean Chi^2: 1.0151
Intercept: 1.0114 (0.0105)
Ratio: 0.7592 (0.6966)
Analysis finished at Thu Oct 17 14:45:48 2019
Total time elapsed: 32.19s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7421,
    "inflation_factor": 1,
    "mean_EFFECT": 6.1551e-08,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 18179,
    "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": 584393,
    "ldsc_nsnp_merge_regression_ld": 584393,
    "ldsc_observed_scale_h2_beta": 0.0003,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0114,
    "ldsc_intercept_se": 0.0105,
    "ldsc_lambda_gc": 1.0161,
    "ldsc_mean_chisq": 1.0151,
    "ldsc_ratio": 0.755
}
 

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 TRUE
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 0 1.0000000 4 58 0 2296123 0 NA NA 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 NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 2296372 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 8.652147e+00 5.769403e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.860934e+07 5.664513e+07 5687.0000000 3.174528e+07 6.906049e+07 1.147458e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.000000e-07 1.208000e-04 -0.0005992 -8.120000e-05 -3.000000e-07 8.130000e-05 5.976000e-04 ▁▂▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.197000e-04 5.600000e-06 0.0001096 1.151000e-04 1.182000e-04 1.235000e-04 2.368000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.974538e-01 2.892688e-01 0.0000055 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.974552e-01 2.892448e-01 0.0000055 2.468149e-01 4.967876e-01 7.475330e-01 9.999989e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.601242e-01 1.412031e-01 0.2521620 3.359610e-01 4.409110e-01 5.743960e-01 7.478380e-01 ▇▆▅▅▃
numeric AF_reference 18179 0.9920836 NA NA NA NA NA NA NA 4.409876e-01 1.700021e-01 0.0001997 3.081070e-01 4.281150e-01 5.648960e-01 1.000000e+00 ▂▇▇▃▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -0.0000969 0.0002018 0.6300007 0.6311898 0.623763 0.7821490 NA
1 54676 rs2462492 C T -0.0001609 0.0001999 0.4199997 0.4210072 0.400401 NA NA
1 91536 rs6702460 G T 0.0000634 0.0001968 0.7499995 0.7473885 0.456851 0.4207270 NA
1 706368 rs55727773 A G -0.0000359 0.0001396 0.8000000 0.7968213 0.515650 0.2751600 NA
1 763394 rs369924889 G A -0.0000607 0.0001636 0.7099994 0.7108730 0.706753 0.6176120 NA
1 776546 rs12124819 A G 0.0000977 0.0001492 0.5099998 0.5123409 0.265390 0.0756789 NA
1 814495 rs74461805 C A 0.0001246 0.0001914 0.5099998 0.5149471 0.340397 NA NA
1 830181 rs28444699 A G 0.0000210 0.0001280 0.8700001 0.8698913 0.697259 0.6912940 NA
1 831489 rs4970385 C T 0.0000351 0.0001257 0.7800007 0.7803325 0.705403 0.6491610 NA
1 831909 rs9697642 C T 0.0000350 0.0001257 0.7800007 0.7805835 0.705448 0.6485620 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C 0.0002240 0.0001314 0.0879995 0.0881452 0.713658 0.6369810 NA
22 51181919 rs9616825 G C 0.0000945 0.0001307 0.4700002 0.4695998 0.695471 0.6194090 NA
22 51182485 rs6009961 A G 0.0002347 0.0001318 0.0749998 0.0749318 0.715505 0.6383790 NA
22 51186143 rs2879914 T C -0.0000441 0.0001222 0.7199992 0.7180025 0.381826 0.2733630 NA
22 51186228 rs3865766 C T -0.0000640 0.0001191 0.5900000 0.5907828 0.451063 0.4532750 NA
22 51197266 rs61290853 A G -0.0001861 0.0001230 0.1299999 0.1302023 0.386333 0.4229230 NA
22 51198027 rs34939255 A G 0.0002991 0.0001392 0.0320000 0.0316638 0.254557 0.0984425 NA
22 51211106 rs9628250 T C 0.0003142 0.0001380 0.0230001 0.0227853 0.271547 0.1671330 NA
22 51212875 rs2238837 A C -0.0000814 0.0001311 0.5300002 0.5349860 0.331455 0.3724040 NA
22 51237063 rs3896457 T C -0.0001846 0.0001342 0.1700000 0.1691375 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  -9.68713e-05:0.000201793:0.200659:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.000160865:0.000199913:0.376751:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  6.33998e-05:0.000196842:0.124939:0.456851:rs6702460
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -3.59367e-05:0.00013958:0.09691:0.51565:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -6.06602e-05:0.000163644:0.148742:0.706753:rs3115847
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  9.77495e-05:0.000149191:0.29243:0.26539:rs12124819
1   814495  rs74461805  C   A   .   PASS    AF=0.340397 ES:SE:LP:AF:ID  0.000124625:0.000191391:0.29243:0.340397:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697259 ES:SE:LP:AF:ID  2.09735e-05:0.000128046:0.0604807:0.697259:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705403 ES:SE:LP:AF:ID  3.50643e-05:0.00012573:0.107905:0.705403:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705448 ES:SE:LP:AF:ID  3.50218e-05:0.000125725:0.107905:0.705448:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705634 ES:SE:LP:AF:ID  3.46089e-05:0.000125731:0.107905:0.705634:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705662 ES:SE:LP:AF:ID  3.41437e-05:0.000125744:0.102373:0.705662:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730134 ES:SE:LP:AF:ID  2.86942e-05:0.000129171:0.0861861:0.730134:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294371 ES:SE:LP:AF:ID  -3.46305e-05:0.000125739:0.107905:0.294371:rs28765502
1   836896  rs28705752  T   C   .   PASS    AF=0.269503 ES:SE:LP:AF:ID  -7.74135e-05:0.000128173:0.259637:0.269503:rs28705752
1   839103  rs28562941  A   G   .   PASS    AF=0.27001  ES:SE:LP:AF:ID  -6.82184e-05:0.000128264:0.229148:0.27001:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400106 ES:SE:LP:AF:ID  -3.18558e-06:0.000115975:0.00877392:0.400106:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362599 ES:SE:LP:AF:ID  1.59697e-05:0.000143971:0.0409586:0.362599:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590333 ES:SE:LP:AF:ID  -9.16896e-06:0.000115635:0.0268721:0.590333:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603726 ES:SE:LP:AF:ID  -2.34239e-05:0.000116284:0.0757207:0.603726:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603944 ES:SE:LP:AF:ID  -3.89309e-05:0.000116268:0.130768:0.603944:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.589688 ES:SE:LP:AF:ID  -2.38424e-05:0.000115823:0.0757207:0.589688:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589667 ES:SE:LP:AF:ID  -2.10175e-05:0.000115771:0.0655015:0.589667:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607674 ES:SE:LP:AF:ID  -1.52235e-05:0.000116528:0.0457575:0.607674:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607833 ES:SE:LP:AF:ID  -1.68624e-05:0.000116544:0.0555173:0.607833:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.610318 ES:SE:LP:AF:ID  -1.23967e-05:0.000116658:0.0362122:0.610318:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603286 ES:SE:LP:AF:ID  -3.36285e-05:0.000116313:0.113509:0.603286:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610338 ES:SE:LP:AF:ID  -1.25045e-05:0.00011666:0.0409586:0.610338:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389935 ES:SE:LP:AF:ID  7.70765e-06:0.000116683:0.0222764:0.389935:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.389918 ES:SE:LP:AF:ID  7.75224e-06:0.000116689:0.0222764:0.389918:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350351 ES:SE:LP:AF:ID  4.9516e-05:0.000119873:0.167491:0.350351:rs4040605
1   866893  rs2880024   T   C   .   PASS    AF=0.610554 ES:SE:LP:AF:ID  2.92721e-05:0.000117316:0.09691:0.610554:rs2880024
1   868418  rs28546443  C   T   .   PASS    AF=0.297865 ES:SE:LP:AF:ID  0.000143366:0.000128897:0.568636:0.297865:rs28546443
1   870645  rs28576697  T   C   .   PASS    AF=0.291287 ES:SE:LP:AF:ID  1.94743e-05:0.00012787:0.0555173:0.291287:rs28576697
1   871334  rs4072383   G   T   .   PASS    AF=0.720619 ES:SE:LP:AF:ID  1.15953e-05:0.000127078:0.0315171:0.720619:rs4072383
1   872352  rs1806780   G   C   .   PASS    AF=0.267526 ES:SE:LP:AF:ID  3.03724e-05:0.000128801:0.091515:0.267526:rs1806780
1   873558  rs1110052   G   T   .   PASS    AF=0.715253 ES:SE:LP:AF:ID  2.55099e-05:0.000126068:0.0757207:0.715253:rs1110052
1   875770  rs4970379   A   G   .   PASS    AF=0.600084 ES:SE:LP:AF:ID  0.000190387:0.000118291:0.958607:0.600084:rs4970379
1   881627  rs2272757   G   A   .   PASS    AF=0.65239  ES:SE:LP:AF:ID  9.86626e-05:0.000119494:0.387216:0.65239:rs2272757
1   891059  rs13303065  C   T   .   PASS    AF=0.652428 ES:SE:LP:AF:ID  0.000107627:0.000119475:0.431798:0.652428:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.65249  ES:SE:LP:AF:ID  0.000110256:0.000119614:0.443698:0.65249:rs13303106
1   900505  rs28705211  G   C   .   PASS    AF=0.271766 ES:SE:LP:AF:ID  -0.000122465:0.000129313:0.468521:0.271766:rs28705211
1   903245  rs28690976  A   G   .   PASS    AF=0.566937 ES:SE:LP:AF:ID  5.47201e-05:0.000118804:0.187087:0.566937:rs28690976
1   909073  rs3892467   C   T   .   PASS    AF=0.386683 ES:SE:LP:AF:ID  0.000171877:0.000118481:0.823909:0.386683:rs3892467
1   909238  rs3829740   G   C   .   PASS    AF=0.571412 ES:SE:LP:AF:ID  3.06279e-05:0.000114745:0.102373:0.571412:rs3829740
1   910394  rs28477686  C   T   .   PASS    AF=0.324456 ES:SE:LP:AF:ID  -0.000165627:0.000124371:0.744727:0.324456:rs28477686
1   912049  rs7367995   T   C   .   PASS    AF=0.58525  ES:SE:LP:AF:ID  4.48691e-05:0.000115908:0.154902:0.58525:rs7367995
1   913889  rs2340596   G   A   .   PASS    AF=0.599213 ES:SE:LP:AF:ID  2.45059e-05:0.000116097:0.0809219:0.599213:rs2340596
1   914333  rs13302979  C   G   .   PASS    AF=0.602521 ES:SE:LP:AF:ID  3.61115e-05:0.000116449:0.119186:0.602521:rs13302979
1   914852  rs13303368  G   C   .   PASS    AF=0.600078 ES:SE:LP:AF:ID  2.57749e-05:0.000116225:0.0861861:0.600078:rs13303368