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\">",
    "FORMAT": "<ID=AF,Number=A,Type=Float,Description=\"Alternate allele frequency in the association study\">",
    "FORMAT.1": "<ID=ES,Number=A,Type=Float,Description=\"Effect size estimate relative to the alternative allele\">",
    "FORMAT.2": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
    "FORMAT.3": "<ID=ID,Number=1,Type=String,Description=\"Study variant identifier\">",
    "FORMAT.4": "<ID=LP,Number=A,Type=Float,Description=\"-log10 p-value for effect estimate\">",
    "FORMAT.5": "<ID=NC,Number=A,Type=Float,Description=\"Number of cases used to estimate genetic effect\">",
    "FORMAT.6": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
    "FORMAT.7": "<ID=SI,Number=A,Type=Float,Description=\"Accuracy score of summary data imputation\">",
    "FORMAT.8": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
    "INFO": "<ID=AF,Number=A,Type=Float,Description=\"Allele Frequency\">",
    "INFO.1": "<ID=ReverseComplementedAlleles,Number=0,Type=Flag,Description=\"The REF and the ALT alleles have been reverse complemented in liftover since the mapping from the previous reference to the current one was on the negative strand.\">",
    "INFO.2": "<ID=SwappedAlleles,Number=0,Type=Flag,Description=\"The REF and the ALT alleles have been swapped in liftover due to changes in the reference. It is possible that not all INFO annotations reflect this swap, and in the genotypes, only the GT, PL, and AD fields have been modified. You should check the TAGS_TO_REVERSE parameter that was used during the LiftOver to be sure.\">",
    "META": "<ID=HarmonisedVariants,Number=1,Type=Integer,Description=\"Total number of harmonised variants\">",
    "META.1": "<ID=StudyType,Number=1,Type=String,Description=\"Type of GWAS study [Continuous or CaseControl]\">",
    "META.2": "<ID=SwitchedAlleles,Number=1,Type=Integer,Description=\"Total number of variants strand switched\">",
    "META.3": "<ID=TotalCases,Number=1,Type=Integer,Description=\"Total number of cases in the association study\">",
    "META.4": "<ID=TotalControls,Number=1,Type=Integer,Description=\"Total number of controls in the association study\">",
    "META.5": "<ID=TotalVariants,Number=1,Type=Integer,Description=\"Total number of variants in input\">",
    "META.6": "<ID=VariantsNotHarmonised,Number=1,Type=Integer,Description=\"Total number of variants that could not be harmonised\">",
    "META.7": "<ID=VariantsNotRead,Number=1,Type=Integer,Description=\"Number of variants that could not be read\">",
    "SAMPLE": "<ID=EBI-a-GCST006353,TotalVariants=5667532,VariantsNotRead=0,HarmonisedVariants=5667532,VariantsNotHarmonised=0,SwitchedAlleles=0,TotalControls=935.0,StudyType=Continuous>",
    "contig": "<ID=1,length=249250621>",
    "contig.1": "<ID=2,length=243199373>",
    "contig.2": "<ID=3,length=198022430>",
    "contig.3": "<ID=4,length=191154276>",
    "contig.4": "<ID=5,length=180915260>",
    "contig.5": "<ID=6,length=171115067>",
    "contig.6": "<ID=7,length=159138663>",
    "contig.7": "<ID=8,length=146364022>",
    "contig.8": "<ID=9,length=141213431>",
    "contig.9": "<ID=10,length=135534747>",
    "contig.10": "<ID=11,length=135006516>",
    "contig.11": "<ID=12,length=133851895>",
    "contig.12": "<ID=13,length=115169878>",
    "contig.13": "<ID=14,length=107349540>",
    "contig.14": "<ID=15,length=102531392>",
    "contig.15": "<ID=16,length=90354753>",
    "contig.16": "<ID=17,length=81195210>",
    "contig.17": "<ID=18,length=78077248>",
    "contig.18": "<ID=19,length=59128983>",
    "contig.19": "<ID=20,length=63025520>",
    "contig.20": "<ID=21,length=48129895>",
    "contig.21": "<ID=22,length=51304566>",
    "contig.22": "<ID=X,length=155270560>",
    "contig.23": "<ID=Y,length=59373566>",
    "contig.24": "<ID=MT,length=16569>",
    "contig.25": "<ID=GL000207.1,length=4262>",
    "contig.26": "<ID=GL000226.1,length=15008>",
    "contig.27": "<ID=GL000229.1,length=19913>",
    "contig.28": "<ID=GL000231.1,length=27386>",
    "contig.29": "<ID=GL000210.1,length=27682>",
    "contig.30": "<ID=GL000239.1,length=33824>",
    "contig.31": "<ID=GL000235.1,length=34474>",
    "contig.32": "<ID=GL000201.1,length=36148>",
    "contig.33": "<ID=GL000247.1,length=36422>",
    "contig.34": "<ID=GL000245.1,length=36651>",
    "contig.35": "<ID=GL000197.1,length=37175>",
    "contig.36": "<ID=GL000203.1,length=37498>",
    "contig.37": "<ID=GL000246.1,length=38154>",
    "contig.38": "<ID=GL000249.1,length=38502>",
    "contig.39": "<ID=GL000196.1,length=38914>",
    "contig.40": "<ID=GL000248.1,length=39786>",
    "contig.41": "<ID=GL000244.1,length=39929>",
    "contig.42": "<ID=GL000238.1,length=39939>",
    "contig.43": "<ID=GL000202.1,length=40103>",
    "contig.44": "<ID=GL000234.1,length=40531>",
    "contig.45": "<ID=GL000232.1,length=40652>",
    "contig.46": "<ID=GL000206.1,length=41001>",
    "contig.47": "<ID=GL000240.1,length=41933>",
    "contig.48": "<ID=GL000236.1,length=41934>",
    "contig.49": "<ID=GL000241.1,length=42152>",
    "contig.50": "<ID=GL000243.1,length=43341>",
    "contig.51": "<ID=GL000242.1,length=43523>",
    "contig.52": "<ID=GL000230.1,length=43691>",
    "contig.53": "<ID=GL000237.1,length=45867>",
    "contig.54": "<ID=GL000233.1,length=45941>",
    "contig.55": "<ID=GL000204.1,length=81310>",
    "contig.56": "<ID=GL000198.1,length=90085>",
    "contig.57": "<ID=GL000208.1,length=92689>",
    "contig.58": "<ID=GL000191.1,length=106433>",
    "contig.59": "<ID=GL000227.1,length=128374>",
    "contig.60": "<ID=GL000228.1,length=129120>",
    "contig.61": "<ID=GL000214.1,length=137718>",
    "contig.62": "<ID=GL000221.1,length=155397>",
    "contig.63": "<ID=GL000209.1,length=159169>",
    "contig.64": "<ID=GL000218.1,length=161147>",
    "contig.65": "<ID=GL000220.1,length=161802>",
    "contig.66": "<ID=GL000213.1,length=164239>",
    "contig.67": "<ID=GL000211.1,length=166566>",
    "contig.68": "<ID=GL000199.1,length=169874>",
    "contig.69": "<ID=GL000217.1,length=172149>",
    "contig.70": "<ID=GL000216.1,length=172294>",
    "contig.71": "<ID=GL000215.1,length=172545>",
    "contig.72": "<ID=GL000205.1,length=174588>",
    "contig.73": "<ID=GL000219.1,length=179198>",
    "contig.74": "<ID=GL000224.1,length=179693>",
    "contig.75": "<ID=GL000223.1,length=180455>",
    "contig.76": "<ID=GL000195.1,length=182896>",
    "contig.77": "<ID=GL000212.1,length=186858>",
    "contig.78": "<ID=GL000222.1,length=186861>",
    "contig.79": "<ID=GL000200.1,length=187035>",
    "contig.80": "<ID=GL000193.1,length=189789>",
    "contig.81": "<ID=GL000194.1,length=191469>",
    "contig.82": "<ID=GL000225.1,length=211173>",
    "contig.83": "<ID=GL000192.1,length=547496>",
    "file_date": "2019-10-26T21:42:19.865704",
    "gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006353/EBI-a-GCST006353_data.json --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/hg38/hg38.fa; 1.1.1",
    "reference": "file:/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/b37/human_g1k_v37.fasta",
    "bcftools_annotateVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
    "bcftools_annotateCommand": "annotate -a /mnt/storage/home/gh13047/mr-eve/vcf-reference-datasets/dbsnp/dbsnp.v153.b37.vcf.gz -c ID -o /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006353/EBI-a-GCST006353.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006353/EBI-a-GCST006353_data.vcf.gz; Date=Sat Oct 26 21:55:26 2019",
    "bcftools_viewVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
    "bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006353/ebi-a-GCST006353.vcf.gz; Date=Sat May  9 17:01:25 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/dev/ebi_gwas_import/processed/EBI-a-GCST006353/EBI-a-GCST006353.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006353/ldsc.txt \
--snplist /data/ref/snplist.gz \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Sat Oct 26 22:21:48 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006353/EBI-a-GCST006353.vcf.gz ...
and extracting SNPs specified in /data/ref/snplist.gz ...
Traceback (most recent call last):
  File "./ldsc/ldsc.py", line 647, in <module>
    sumstats.estimate_h2(args, log)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
    args, log, args.h2)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 246, in _read_ld_sumstats
    sumstats = _read_sumstats(args, log, fh, alleles=alleles, dropna=dropna)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 165, in _read_sumstats
    sumstats = ps.sumstats(fh, alleles=alleles, dropna=dropna, slh=args.snplist)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 85, in sumstats
    x = read_vcf(fh, alleles, slh)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 161, in read_vcf
    with gzip.open(slh) as f:
  File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 34, in open
    return GzipFile(filename, mode, compresslevel)
  File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 94, in __init__
    fileobj = self.myfileobj = __builtin__.open(filename, mode or 'rb')
IOError: [Errno 2] No such file or directory: '/data/ref/snplist.gz'

Analysis finished at Sat Oct 26 22:22:26 2019
Total time elapsed: 37.42s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9154,
    "inflation_factor": 1.0149,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 5667532,
    "n_clumped_hits": 1,
    "n_p_sig": 67,
    "n_mono": 0,
    "n_ns": 416467,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 174730,
    "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": "NA",
    "ldsc_nsnp_merge_regression_ld": "NA",
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": "NA",
    "ldsc_intercept_se": "NA",
    "ldsc_lambda_gc": "NA",
    "ldsc_mean_chisq": "NA",
    "ldsc_ratio": "NA"
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio TRUE
ldsc_intercept_beta TRUE
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 5654471 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 951 0 19016 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 42 0 10065 0 NA NA NA NA NA NA NA NA NA NA
logical N 5654495 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 8.586804e+00 5.706313e+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 7.896135e+07 5.620303e+07 302.0000000 3.263165e+07 6.956397e+07 1.145193e+08 2.491747e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 8.910000e-05 2.326590e-02 -0.1589430 -1.442030e-02 9.300000e-05 1.453780e-02 1.419350e-01 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.234330e-02 5.905600e-03 0.0152519 1.743250e-02 2.015570e-02 2.592530e-02 4.105500e-02 ▇▃▂▂▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.975760e-01 2.890707e-01 0.0000000 2.464087e-01 4.968336e-01 7.479008e-01 9.999990e-01 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.974014e-01 2.891751e-01 0.0000000 2.461056e-01 4.966623e-01 7.478277e-01 9.999993e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.369441e-01 2.464971e-01 0.0452040 1.258060e-01 2.645160e-01 5.053760e-01 9.553860e-01 ▇▃▂▂▂
numeric AF_reference 174730 0.9690989 NA NA NA NA NA NA NA 3.336709e-01 2.387413e-01 0.0001997 1.367810e-01 2.709660e-01 4.946090e-01 1.000000e+00 ▇▆▃▂▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 752566 rs3094315 G A 0.0115183 0.0239659 0.6309065 0.6307923 0.855914 0.718251 NA
1 752721 rs3131972 A G 0.0149403 0.0238923 0.5319172 0.5317620 0.853226 0.653355 NA
1 752894 rs3131971 T C 0.0096023 0.0238216 0.6869751 0.6868814 0.852211 0.753195 NA
1 753405 rs3115860 C A 0.0109130 0.0264379 0.6798702 0.6797688 0.887133 0.751797 NA
1 753474 rs2073814 C G 0.0195129 0.0241372 0.4190617 0.4188511 0.856284 0.611422 NA
1 753541 rs2073813 G A -0.0125876 0.0268113 0.6388369 0.6387204 0.110419 0.301917 NA
1 754503 rs3115859 G A 0.0140324 0.0242896 0.5636026 0.5634584 0.857454 0.663938 NA
1 754964 rs3131966 C T 0.0140607 0.0240847 0.5595050 0.5593534 0.848245 0.663339 NA
1 755775 rs3131965 A G 0.0180073 0.0241683 0.4564204 0.4562238 0.853170 NA NA
1 755890 rs3115858 A T 0.0079819 0.0267874 0.7657941 0.7657235 0.888826 0.751398 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51212624 rs2238836 G A -0.0709031 0.0380781 0.0629260 0.0625969 0.0512249 0.0591054 NA
22 51213759 rs141103268 G C -0.0239406 0.0341532 0.4834995 0.4833175 0.0656733 0.0736821 NA
22 51216564 rs9616970 T C -0.0351302 0.0268179 0.1905531 0.1902116 0.1184060 0.1563500 NA
22 51217954 rs9616974 G A -0.0306332 0.0344345 0.3739151 0.3736765 0.0642303 0.0621006 NA
22 51218224 rs9616975 C A -0.0306332 0.0344345 0.3739151 0.3736765 0.0642303 0.0619010 NA
22 51218377 rs2519461 G C -0.0309990 0.0338336 0.3597990 0.3595518 0.0676275 0.0826677 NA
22 51219387 rs9616832 T C -0.0287343 0.0355149 0.4186894 0.4184707 0.0605381 0.0654952 NA
22 51221731 rs115055839 T C -0.0306332 0.0344345 0.3739151 0.3736765 0.0642303 0.0625000 NA
22 51222100 rs114553188 G T -0.0206034 0.0360202 0.5674662 0.5673249 0.0563991 0.0880591 NA
22 51229805 rs9616985 T C -0.0306332 0.0344345 0.3739151 0.3736765 0.0642303 0.0730831 NA

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.855914 ES:SE:LP:AF:ID  0.0115183:0.0239659:0.200035:0.855914:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.853226 ES:SE:LP:AF:ID  0.0149403:0.0238923:0.274156:0.853226:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.852211 ES:SE:LP:AF:ID  0.00960227:0.0238216:0.163059:0.852211:rs3131971
1   753405  rs3115860   C   A   .   PASS    AF=0.887133 ES:SE:LP:AF:ID  0.010913:0.0264379:0.167574:0.887133:rs3115860
1   753474  rs2073814   C   G   .   PASS    AF=0.856284 ES:SE:LP:AF:ID  0.0195129:0.0241372:0.377722:0.856284:rs2073814
1   753541  rs2073813   G   A   .   PASS    AF=0.110419 ES:SE:LP:AF:ID  -0.0125876:0.0268113:0.19461:0.110419:rs2073813
1   754503  rs3115859   G   A   .   PASS    AF=0.857454 ES:SE:LP:AF:ID  0.0140324:0.0242896:0.249027:0.857454:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.848245 ES:SE:LP:AF:ID  0.0140607:0.0240847:0.252196:0.848245:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.85317  ES:SE:LP:AF:ID  0.0180073:0.0241683:0.340635:0.85317:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.888826 ES:SE:LP:AF:ID  0.00798193:0.0267874:0.115888:0.888826:rs3115858
1   757734  rs4951929   C   T   .   PASS    AF=0.889266 ES:SE:LP:AF:ID  0.00781428:0.0268479:0.112903:0.889266:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.88914  ES:SE:LP:AF:ID  0.00796491:0.0268661:0.115236:0.88914:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870288 ES:SE:LP:AF:ID  0.0146487:0.0252129:0.250739:0.870288:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.889266 ES:SE:LP:AF:ID  0.00781428:0.0268479:0.112903:0.889266:rs3131954
1   759700  rs3115852   T   C   .   PASS    AF=0.856127 ES:SE:LP:AF:ID  0.0123589:0.0240682:0.216288:0.856127:rs3115852
1   768448  rs12562034  G   A   .   PASS    AF=0.106452 ES:SE:LP:AF:ID  0.0150734:0.0271968:0.236906:0.106452:rs12562034
1   769963  rs7518545   G   A   .   PASS    AF=0.0992408    ES:SE:LP:AF:ID  0.00752302:0.0283716:0.101853:0.0992408:rs7518545
1   776546  rs12124819  A   G   .   PASS    AF=0.256989 ES:SE:LP:AF:ID  -0.0400445:0.0189024:1.46343:0.256989:rs12124819
1   791853  rs6684487   G   A   .   PASS    AF=0.0878076    ES:SE:LP:AF:ID  -0.000561356:0.0299139:0.00654966:0.0878076:rs6684487
1   794332  rs12127425  G   A   .   PASS    AF=0.0875831    ES:SE:LP:AF:ID  -0.00351301:0.0300063:0.042476:0.0875831:rs12127425
1   795222  rs12131377  C   G   .   PASS    AF=0.0875831    ES:SE:LP:AF:ID  -0.00322509:0.0300152:0.0388367:0.0875831:rs12131377
1   796100  rs12132398  C   T   .   PASS    AF=0.0875831    ES:SE:LP:AF:ID  -0.00420889:0.0300025:0.0513587:0.0875831:rs12132398
1   796375  rs12083781  T   C   .   PASS    AF=0.0910615    ES:SE:LP:AF:ID  -0.0123241:0.0285864:0.176208:0.0910615:rs12083781
1   797126  rs55744324  GTAAT   G   .   PASS    AF=0.0881375    ES:SE:LP:AF:ID  -0.00550724:0.0299373:0.0684979:0.0881375:rs140389426
1   797281  rs76631953  G   C   .   PASS    AF=0.0888889    ES:SE:LP:AF:ID  -0.000847653:0.02989:0.00993566:0.0888889:rs76631953
1   797325  rs111739932 T   C   .   PASS    AF=0.0880399    ES:SE:LP:AF:ID  -0.00563633:0.0299196:0.0702649:0.0880399:rs111739932
1   797440  rs58013264  T   C   .   PASS    AF=0.0917793    ES:SE:LP:AF:ID  -0.00527248:0.0285762:0.0687156:0.0917793:rs58013264
1   798026  rs4951864   C   T   .   PASS    AF=0.911765 ES:SE:LP:AF:ID  0.00589942:0.0299394:0.0737414:0.911765:rs4951864
1   798400  rs10900604  A   G   .   PASS    AF=0.199783 ES:SE:LP:AF:ID  -0.00640127:0.0206205:0.121304:0.199783:rs10900604
1   798801  rs12132517  G   A   .   PASS    AF=0.0899321    ES:SE:LP:AF:ID  -0.00691832:0.0299941:0.08744:0.0899321:rs12132517
1   798959  rs11240777  G   A   .   PASS    AF=0.200538 ES:SE:LP:AF:ID  -0.00762401:0.0205226:0.148524:0.200538:rs11240777
1   799499  rs147634896 T   C   .   PASS    AF=0.0867631    ES:SE:LP:AF:ID  -0.003296:0.0302019:0.0394712:0.0867631:rs147634896
1   801661  rs12132974  C   T   .   PASS    AF=0.0850112    ES:SE:LP:AF:ID  -0.00923894:0.0304909:0.11807:0.0850112:rs12132974
1   801680  rs12134490  A   C   .   PASS    AF=0.0850112    ES:SE:LP:AF:ID  -0.00923894:0.0304909:0.11807:0.0850112:rs12134490
1   801858  rs17276806  C   T   .   PASS    AF=0.0845465    ES:SE:LP:AF:ID  -0.00807689:0.0305774:0.101423:0.0845465:rs17276806
1   802398  rs111444624 C   T   .   PASS    AF=0.0785311    ES:SE:LP:AF:ID  -0.0325023:0.0320065:0.508424:0.0785311:rs111444624
1   802856  rs139867617 C   T   .   PASS    AF=0.0780543    ES:SE:LP:AF:ID  -0.0316264:0.0321584:0.487242:0.0780543:rs139867617
1   833927  rs28593608  T   C   .   PASS    AF=0.190848 ES:SE:LP:AF:ID  -0.00615172:0.0214806:0.110894:0.190848:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.190848 ES:SE:LP:AF:ID  -0.00615172:0.0214806:0.110894:0.190848:rs28385272
1   834928  rs4422949   A   G   .   PASS    AF=0.191704 ES:SE:LP:AF:ID  -0.00764844:0.021492:0.141451:0.191704:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.191061 ES:SE:LP:AF:ID  -0.00643049:0.0214939:0.11641:0.191061:rs28570054
1   836529  rs28731045  C   G   .   PASS    AF=0.199343 ES:SE:LP:AF:ID  -0.00837178:0.0209324:0.161596:0.199343:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.263626 ES:SE:LP:AF:ID  0.000614896:0.0192105:0.0112302:0.263626:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.199343 ES:SE:LP:AF:ID  -0.00837178:0.0209324:0.161596:0.199343:rs72890788
1   837192  rs57494724  A   G   .   PASS    AF=0.0553691    ES:SE:LP:AF:ID  0.0114562:0.0369835:0.121013:0.0553691:rs57494724
1   838329  rs144685080 G   GC  .   PASS    AF=0.199013 ES:SE:LP:AF:ID  -0.0083547:0.0209582:0.16099:0.199013:rs144685080
1   838387  rs4970384   T   C   .   PASS    AF=0.201099 ES:SE:LP:AF:ID  -0.00479859:0.0209288:0.0868741:0.201099:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.238172 ES:SE:LP:AF:ID  5.58284e-05:0.0195424:0.000990887:0.238172:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.263827 ES:SE:LP:AF:ID  0.00201381:0.0192014:0.0378694:0.263827:rs28562941
1   839873  rs192553893 C   T   .   PASS    AF=0.23043  ES:SE:LP:AF:ID  -0.00609425:0.0201859:0.117593:0.23043:rs192553893