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:6267,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=458721,TotalCases=2035,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_41248_6005.vcf.gz --id UKB-b:6267 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_41248_6005.txt.gz --cohort_cases 2035 --cohort_controls 458721 --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": "2019-09-13T13:24:06.131037",
    "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-6267/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6267/UKB-b-6267_raw.vcf.gz; Date=Thu Oct 17 12:17:56 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-6267/ukb-b-6267.vcf.gz; Date=Sun May 10 04:00:07 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-6267/UKB-b-6267_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6267/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6267/UKB-b-6267_data.vcf.gz ...
Read summary statistics for 3227992 SNPs.
Dropped 457 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, 797318 SNPs remain.
After merging with regression SNP LD, 797318 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0015 (0.0013)
Lambda GC: 1.1724
Mean Chi^2: 1.1722
Intercept: 1.156 (0.0103)
Ratio: 0.9062 (0.06)
Analysis finished at Thu Oct 17 14:41:03 2019
Total time elapsed: 44.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8339,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 4.1605e-07,
    "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": 25813,
    "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": 797318,
    "ldsc_nsnp_merge_regression_ld": 797318,
    "ldsc_observed_scale_h2_beta": 0.0015,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.156,
    "ldsc_intercept_se": 0.0103,
    "ldsc_lambda_gc": 1.1724,
    "ldsc_mean_chisq": 1.1722,
    "ldsc_ratio": 0.9059
}

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 3 58 0 3227538 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 3227992 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 8.660791e+00 5.772023e+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 7.853319e+07 5.670202e+07 828.0000000 3.159652e+07 6.891815e+07 1.147758e+08 2.492013e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.000000e-07 1.657000e-04 -0.0010351 -1.104000e-04 0.000000e+00 1.110000e-04 8.392000e-04 ▁▁▇▃▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.521000e-04 1.340000e-05 0.0001327 1.404000e-04 1.480000e-04 1.616000e-04 3.281000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.739842e-01 2.947735e-01 0.0000001 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.739857e-01 2.947451e-01 0.0000001 2.121561e-01 4.644950e-01 7.286453e-01 1.000000e+00 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.261565e-01 1.848288e-01 0.1719910 2.641200e-01 3.917930e-01 5.692270e-01 8.280090e-01 ▇▆▅▃▃
numeric AF_reference 25813 0.9920034 NA NA NA NA NA NA NA 4.112690e-01 1.978136e-01 0.0000000 2.511980e-01 3.841850e-01 5.563100e-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 0.0000424 0.0002441 0.8600001 0.8621013 0.623762 0.7821490 NA
1 54676 rs2462492 C T -0.0000702 0.0002418 0.7700005 0.7716662 0.400374 NA NA
1 91536 rs6702460 G T -0.0001686 0.0002381 0.4799997 0.4787987 0.456837 0.4207270 NA
1 534192 rs6680723 C T 0.0001218 0.0002720 0.6499995 0.6542883 0.240952 NA NA
1 706368 rs55727773 A G -0.0001139 0.0001688 0.5000000 0.4997379 0.515612 0.2751600 NA
1 763394 rs369924889 G A 0.0002673 0.0001979 0.1800002 0.1768448 0.706746 0.6176120 NA
1 768253 rs2977608 A C 0.0001278 0.0001615 0.4299995 0.4288107 0.761299 0.4894170 NA
1 776546 rs12124819 A G -0.0002443 0.0001804 0.1800002 0.1757493 0.265388 0.0756789 NA
1 798400 rs10900604 A G -0.0001464 0.0001723 0.4000000 0.3955914 0.206587 0.4105430 NA
1 798959 rs11240777 G A -0.0001464 0.0001724 0.4000000 0.3956689 0.206417 0.4099440 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C 0.0000593 0.0001590 0.7099994 0.7089766 0.713615 0.6369810 NA
22 51181919 rs9616825 G C 0.0000440 0.0001581 0.7800007 0.7810587 0.695449 0.6194090 NA
22 51182485 rs6009961 A G 0.0000425 0.0001595 0.7899998 0.7896762 0.715458 0.6383790 NA
22 51186143 rs2879914 T C -0.0000207 0.0001479 0.8900000 0.8886240 0.381787 0.2733630 NA
22 51186228 rs3865766 C T -0.0000654 0.0001441 0.6499995 0.6498406 0.451012 0.4532750 NA
22 51197266 rs61290853 A G -0.0001472 0.0001488 0.3200000 0.3226601 0.386300 0.4229230 NA
22 51198027 rs34939255 A G 0.0000560 0.0001684 0.7400005 0.7397458 0.254546 0.0984425 NA
22 51211106 rs9628250 T C 0.0000858 0.0001670 0.6100002 0.6073385 0.271542 0.1671330 NA
22 51212875 rs2238837 A C -0.0001159 0.0001587 0.4700002 0.4652374 0.331442 0.3724040 NA
22 51237063 rs3896457 T C -0.0002181 0.0001624 0.1800002 0.1794122 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623762 ES:SE:LP:AF:ID  4.23991e-05:0.000244094:0.0655015:0.623762:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400374 ES:SE:LP:AF:ID  -7.01819e-05:0.000241843:0.113509:0.400374:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456837 ES:SE:LP:AF:ID  -0.000168614:0.000238076:0.318759:0.456837:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240952 ES:SE:LP:AF:ID  0.000121793:0.000271973:0.187087:0.240952:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515612 ES:SE:LP:AF:ID  -0.000113937:0.00016882:0.30103:0.515612:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706746 ES:SE:LP:AF:ID  0.000267322:0.000197938:0.744727:0.706746:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761299 ES:SE:LP:AF:ID  0.000127819:0.000161545:0.366532:0.761299:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265388 ES:SE:LP:AF:ID  -0.000244322:0.00018045:0.744727:0.265388:rs12124819
1   798400  rs10900604  A   G   .   PASS    AF=0.206587 ES:SE:LP:AF:ID  -0.000146409:0.000172343:0.39794:0.206587:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206417 ES:SE:LP:AF:ID  -0.000146447:0.000172416:0.39794:0.206417:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772609 ES:SE:LP:AF:ID  0.000144302:0.00016401:0.420216:0.772609:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772837 ES:SE:LP:AF:ID  0.000151464:0.000164287:0.443698:0.772837:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340372 ES:SE:LP:AF:ID  -0.000100152:0.000231517:0.173925:0.340372:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697211 ES:SE:LP:AF:ID  -0.000206882:0.000154863:0.744727:0.697211:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705382 ES:SE:LP:AF:ID  -0.000269239:0.000152068:1.11351:0.705382:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705428 ES:SE:LP:AF:ID  -0.000276184:0.000152063:1.16115:0.705428:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705614 ES:SE:LP:AF:ID  -0.000273291:0.00015207:1.14267:0.705614:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705642 ES:SE:LP:AF:ID  -0.000273803:0.000152086:1.14267:0.705642:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730106 ES:SE:LP:AF:ID  -0.000272779:0.000156229:1.09151:0.730106:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294391 ES:SE:LP:AF:ID  0.000278202:0.000152079:1.17393:0.294391:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236756 ES:SE:LP:AF:ID  0.000386894:0.000161896:1.76955:0.236756:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236745 ES:SE:LP:AF:ID  0.000388403:0.000161898:1.79588:0.236745:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239808 ES:SE:LP:AF:ID  0.000372632:0.000161378:1.67778:0.239808:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236745 ES:SE:LP:AF:ID  0.000388426:0.000161896:1.79588:0.236745:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212483 ES:SE:LP:AF:ID  0.000411375:0.000168264:1.85387:0.212483:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212378 ES:SE:LP:AF:ID  0.000404615:0.000168294:1.79588:0.212378:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.23723  ES:SE:LP:AF:ID  0.000390312:0.000161772:1.79588:0.23723:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.213025 ES:SE:LP:AF:ID  0.000415027:0.000168054:1.85387:0.213025:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212987 ES:SE:LP:AF:ID  0.000414672:0.000168089:1.85387:0.212987:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241215 ES:SE:LP:AF:ID  0.000435098:0.000160641:2.16749:0.241215:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213606 ES:SE:LP:AF:ID  0.000416245:0.00016784:1.88606:0.213606:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269555 ES:SE:LP:AF:ID  0.000438571:0.000155014:2.3279:0.269555:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213576 ES:SE:LP:AF:ID  0.000416556:0.00016786:1.88606:0.213576:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214648 ES:SE:LP:AF:ID  0.000410219:0.000167536:1.85387:0.214648:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246257 ES:SE:LP:AF:ID  0.000438807:0.000159542:2.22185:0.246257:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270067 ES:SE:LP:AF:ID  0.000444271:0.000155124:2.37675:0.270067:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400158 ES:SE:LP:AF:ID  0.00016648:0.000140273:0.619789:0.400158:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237176 ES:SE:LP:AF:ID  0.000401243:0.000162909:1.85387:0.237176:rs1574243
1   842013  rs7419119   T   G   .   PASS    AF=0.215457 ES:SE:LP:AF:ID  0.000407954:0.00016765:1.82391:0.215457:rs7419119
1   842362  rs28540380  C   T   .   PASS    AF=0.235364 ES:SE:LP:AF:ID  0.000299135:0.000165358:1.1549:0.235364:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362554 ES:SE:LP:AF:ID  -3.11196e-05:0.000174168:0.0655015:0.362554:rs11516185
1   844300  rs61769713  C   G   .   PASS    AF=0.818887 ES:SE:LP:AF:ID  0.000203995:0.000178996:0.60206:0.818887:rs61769713
1   845283  rs7366404   G   T   .   PASS    AF=0.814573 ES:SE:LP:AF:ID  0.000140392:0.000177418:0.366532:0.814573:rs7366404
1   845635  rs117086422 C   T   .   PASS    AF=0.20545  ES:SE:LP:AF:ID  0.000282603:0.00017052:1.01323:0.20545:rs117086422
1   845938  rs57760052  G   A   .   PASS    AF=0.210882 ES:SE:LP:AF:ID  0.00026844:0.00016888:0.958607:0.210882:rs57760052
1   846078  rs28612348  C   T   .   PASS    AF=0.196804 ES:SE:LP:AF:ID  0.000306945:0.00017313:1.11919:0.196804:rs28612348
1   846338  rs4970334   A   G   .   PASS    AF=0.813905 ES:SE:LP:AF:ID  0.000138622:0.000177266:0.366532:0.813905:rs4970334
1   846398  rs58781670  G   A   .   PASS    AF=0.204461 ES:SE:LP:AF:ID  0.000258252:0.000171109:0.886057:0.204461:rs58781670
1   846489  rs4970333   T   C   .   PASS    AF=0.813995 ES:SE:LP:AF:ID  0.000137908:0.000177389:0.356547:0.813995:rs4970333
1   846808  rs4475691   C   T   .   PASS    AF=0.198397 ES:SE:LP:AF:ID  0.000300468:0.000172639:1.08619:0.198397:rs4475691