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:17965,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=455393,TotalCases=5800,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_41245_1520.vcf.gz --id UKB-b:17965 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_41245_1520.txt.gz --cohort_cases 5800 --cohort_controls 455393 --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": "2019-09-13T13:13:26.156836",
    "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-17965/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17965/UKB-b-17965_raw.vcf.gz; Date=Thu Oct 17 12:35:38 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-17965/ukb-b-17965.vcf.gz; Date=Sun May 10 10:38:03 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-17965/UKB-b-17965_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17965/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17965/UKB-b-17965_data.vcf.gz ...
Read summary statistics for 5141721 SNPs.
Dropped 1566 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, 1133453 SNPs remain.
After merging with regression SNP LD, 1133453 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0005 (0.001)
Lambda GC: 1.0424
Mean Chi^2: 1.0324
Intercept: 1.0278 (0.0076)
Ratio: 0.8597 (0.2338)
Analysis finished at Thu Oct 17 14:41:21 2019
Total time elapsed: 1.0m:3.17s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9095,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 1.081e-06,
    "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": 44184,
    "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": 1133453,
    "ldsc_nsnp_merge_regression_ld": 1133453,
    "ldsc_observed_scale_h2_beta": 0.0005,
    "ldsc_observed_scale_h2_se": 0.001,
    "ldsc_intercept_beta": 1.0278,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.0424,
    "ldsc_mean_chisq": 1.0324,
    "ldsc_ratio": 0.858
}

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 5140166 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 5141721 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 8.672398e+00 5.764229e+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 7.853360e+07 5.660127e+07 828.0000000 3.189872e+07 6.892051e+07 1.144911e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.100000e-06 3.179000e-04 -0.0021972 -2.009000e-04 8.000000e-07 2.026000e-04 2.259500e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.047000e-04 7.240000e-05 0.0002240 2.435000e-04 2.784000e-04 3.502000e-04 8.759000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.942228e-01 2.899065e-01 0.0000001 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.942250e-01 2.898795e-01 0.0000001 2.419878e-01 4.908181e-01 7.454134e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.458167e-01 2.410198e-01 0.0603450 1.384560e-01 2.778300e-01 5.126170e-01 9.396550e-01 ▇▅▃▂▂
numeric AF_reference 44184 0.9914068 NA NA NA NA NA NA NA 3.396969e-01 2.370912e-01 0.0000000 1.441690e-01 2.809500e-01 5.019970e-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 0.0000312 0.0004121 0.9400001 0.9397418 0.623777 0.7821490 NA
1 54676 rs2462492 C T -0.0003517 0.0004084 0.3900004 0.3890614 0.400400 NA NA
1 86028 rs114608975 T C 0.0002256 0.0006529 0.7300002 0.7296998 0.103559 0.0277556 NA
1 91536 rs6702460 G T -0.0000320 0.0004020 0.9400001 0.9364982 0.456852 0.4207270 NA
1 234313 rs8179466 C T -0.0015382 0.0007927 0.0519996 0.0523237 0.074511 NA NA
1 534192 rs6680723 C T 0.0003860 0.0004593 0.4000000 0.4006210 0.240949 NA NA
1 546697 rs12025928 A G -0.0007250 0.0005729 0.2099999 0.2057405 0.913476 NA NA
1 693731 rs12238997 A G -0.0000510 0.0003849 0.8900000 0.8945493 0.116332 0.1417730 NA
1 705882 rs72631875 G A 0.0004685 0.0005639 0.4100001 0.4061256 0.067303 0.0315495 NA
1 706368 rs55727773 A G -0.0004786 0.0002851 0.0929994 0.0932216 0.515662 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51213613 rs34726907 C T -0.0002859 0.0003529 0.4199997 0.4178609 0.127814 0.1727240 NA
22 51216564 rs9616970 T C -0.0002718 0.0003514 0.4400003 0.4391079 0.128326 0.1563500 NA
22 51217954 rs9616974 G A -0.0000475 0.0004458 0.9199999 0.9151108 0.073300 0.0621006 NA
22 51218224 rs9616975 C A -0.0000555 0.0004460 0.9000000 0.9008830 0.073321 0.0619010 NA
22 51218377 rs2519461 G C -0.0000063 0.0004455 0.9900000 0.9886607 0.073608 0.0826677 NA
22 51219006 rs28729663 G A -0.0002076 0.0003439 0.5500004 0.5460307 0.137950 0.2052720 NA
22 51219387 rs9616832 T C -0.0000702 0.0004464 0.8700001 0.8749527 0.073733 0.0654952 NA
22 51221731 rs115055839 T C -0.0000521 0.0004466 0.9100000 0.9071802 0.073223 0.0625000 NA
22 51229805 rs9616985 T C -0.0000539 0.0004483 0.9000000 0.9042633 0.073060 0.0730831 NA
22 51237063 rs3896457 T C 0.0000610 0.0002742 0.8200001 0.8238347 0.297984 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623777 ES:SE:LP:AF:ID  3.11545e-05:0.000412127:0.0268721:0.623777:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.4004   ES:SE:LP:AF:ID  -0.000351747:0.000408381:0.408935:0.4004:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103559 ES:SE:LP:AF:ID  0.000225577:0.000652853:0.136677:0.103559:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456852 ES:SE:LP:AF:ID  -3.2031e-05:0.000402036:0.0268721:0.456852:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074511 ES:SE:LP:AF:ID  -0.00153818:0.000792688:1.284:0.074511:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240949 ES:SE:LP:AF:ID  0.000386008:0.000459253:0.39794:0.240949:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  -0.000724953:0.00057292:0.677781:0.913476:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116332 ES:SE:LP:AF:ID  -5.10157e-05:0.000384879:0.05061:0.116332:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067303 ES:SE:LP:AF:ID  0.00046847:0.000563925:0.387216:0.067303:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515662 ES:SE:LP:AF:ID  -0.000478598:0.00028511:1.03152:0.515662:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101205 ES:SE:LP:AF:ID  0.000812577:0.000470378:1.07572:0.101205:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.843188 ES:SE:LP:AF:ID  -0.000178003:0.000333535:0.229148:0.843188:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.12232  ES:SE:LP:AF:ID  4.35054e-05:0.000365092:0.0409586:0.12232:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121563 ES:SE:LP:AF:ID  6.31261e-05:0.000365245:0.0655015:0.121563:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132342 ES:SE:LP:AF:ID  0.000255403:0.000359987:0.318759:0.132342:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.83893  ES:SE:LP:AF:ID  -6.61869e-05:0.000323005:0.0757207:0.83893:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838558 ES:SE:LP:AF:ID  -8.57725e-05:0.000322657:0.102373:0.838558:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869768 ES:SE:LP:AF:ID  5.91368e-07:0.000346231:-0:0.869768:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129886 ES:SE:LP:AF:ID  4.92317e-05:0.000346932:0.05061:0.129886:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869108 ES:SE:LP:AF:ID  -3.34994e-05:0.00034555:0.0362122:0.869108:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869206 ES:SE:LP:AF:ID  -4.47945e-05:0.000345686:0.0457575:0.869206:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869112 ES:SE:LP:AF:ID  -3.54222e-05:0.000345544:0.0362122:0.869112:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.83801  ES:SE:LP:AF:ID  -8.37837e-05:0.000321759:0.102373:0.83801:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.83864  ES:SE:LP:AF:ID  -6.49499e-05:0.000322663:0.0757207:0.83864:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839756 ES:SE:LP:AF:ID  -4.60407e-05:0.00032703:0.05061:0.839756:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869393 ES:SE:LP:AF:ID  -5.58421e-06:0.000345146:0.00436481:0.869393:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868942 ES:SE:LP:AF:ID  -3.13089e-05:0.000344281:0.0315171:0.868942:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867891 ES:SE:LP:AF:ID  -7.96363e-05:0.000343616:0.0861861:0.867891:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869084 ES:SE:LP:AF:ID  -2.13686e-05:0.000344561:0.0222764:0.869084:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869093 ES:SE:LP:AF:ID  -2.21385e-05:0.000344588:0.0222764:0.869093:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -2.20813e-05:0.000344596:0.0222764:0.869101:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869576 ES:SE:LP:AF:ID  -1.06107e-05:0.000345539:0.00877392:0.869576:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.83829  ES:SE:LP:AF:ID  -3.46122e-05:0.000321146:0.0409586:0.83829:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838411 ES:SE:LP:AF:ID  -2.84361e-05:0.000321374:0.0315171:0.838411:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862246 ES:SE:LP:AF:ID  1.97822e-05:0.000343344:0.0222764:0.862246:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706756 ES:SE:LP:AF:ID  -0.00014573:0.000334259:0.180456:0.706756:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105133 ES:SE:LP:AF:ID  0.000115065:0.000385074:0.113509:0.105133:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761327 ES:SE:LP:AF:ID  -0.000274268:0.000272826:0.508638:0.761327:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106458 ES:SE:LP:AF:ID  0.000466112:0.000376055:0.657577:0.106458:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129582 ES:SE:LP:AF:ID  4.54657e-05:0.000346734:0.0457575:0.129582:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868904 ES:SE:LP:AF:ID  -1.8823e-05:0.000344885:0.0177288:0.868904:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129684 ES:SE:LP:AF:ID  4.2007e-05:0.00034651:0.0457575:0.129684:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868914 ES:SE:LP:AF:ID  -2.21504e-06:0.000344892:0.00436481:0.868914:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265366 ES:SE:LP:AF:ID  -8.5996e-06:0.000304731:0.00877392:0.265366:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870033 ES:SE:LP:AF:ID  5.57141e-06:0.000345593:0.00436481:0.870033:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095117 ES:SE:LP:AF:ID  0.000267806:0.000400574:0.30103:0.095117:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128585 ES:SE:LP:AF:ID  1.07432e-05:0.000346954:0.00877392:0.128585:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128883 ES:SE:LP:AF:ID  6.41471e-06:0.000346364:0.00436481:0.128883:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868773 ES:SE:LP:AF:ID  -2.32882e-05:0.000344669:0.0222764:0.868773:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.101866 ES:SE:LP:AF:ID  0.000153586:0.000390567:0.161151:0.101866:rs61768199