Comments (1)
Hi Laura,
I'm assuming you already harmonized the GWAS.
The summary imputation tool indeed needs zscores - it assumes its existence and uses the observed values to impute missing zscores. I suggest re-running harmonization with zscore
in the generated columns.
Best,
Alvaro
from summary-gwas-imputation.
Related Issues (20)
- Report "OSError: Invalid flatbuffers message." when reading parquet files. HOT 2
- Coloc with GTEx data: WARNING - R[write to console]: Error in process.dataset(d = dataset1, suffix = " dataset df1: Length of snp names and beta vectors must match HOT 1
- Error in gwas harmonization step HOT 1
- AttributeError("'pyarrow.lib.ChunkedArray' object has no attribute 'name'") when using gwas_summary_imputation.py HOT 3
- post-processing of imputed chromosome files HOT 4
- Failing harmonization
- Imputation error: "AttributeError: type object 'object' has no attribute 'dtype'"
- Script output: gwas_summary_imputation.py HOT 1
- liftover from hg19 -> hg38 HOT 7
- Losing almost all variants after restricting to reference step in harmonization. HOT 2
- No objects to concatenate in post processing step HOT 1
- AttributeError: 'DataFrame' object has no attribute 'sample_size'
- error when run_coloc.py
- Error running run_coloc.py : dataset 1: missing required element(s) snp
- In the example data on summary statistics imputation, there is a .bed file eur_ld.bed.gz to run per-region imputation. Is summary statistics-based imputation by region applicable only for population-specific GWASes? Are there any ld block schemes applicable to multipopulation studies?
- OSError: Couldn't deserialize thrift: TProtocolException: Exceeded size limit
- Mismatched order of imputation column and header HOT 1
- ValueError: invalid literal for int() with base 10: '1_KI270766v1_alt' HOT 1
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from summary-gwas-imputation.