'No GWAS intersection for region' in imputation

[Sophie Chan]

Hi there,

I ran the imputation but I got nothing, even for the whole chromosome:

INFO - Beginning process
INFO - Creating context by variant
INFO - Loading study
INFO - Loading variants' parquet file
INFO - Loading variants metadata
Level 9 - Loading row group 0
/home/pclam/anaconda3/envs/imlabtools/lib/python3.7/site-packages/pyarrow/pandas_compat.py:752: FutureWarning: .labels was deprecated in version 0.24.0. Use .codes instead.
  labels, = index.labels
INFO - Loading regions
Level 9 - Selecting target regions with specific chromosome
Level 9 - generating GWAS whitelist
INFO - Loading gwas
INFO - Acquiring filter tree for 2162604 targets
INFO - Processing gwas source
Level 9 - Loaded 0 GWAS variants
Level 9 - Parsing GWAS
Level 9 - Processing region 1/131 [10583.0, 1961168.0]
Level 8 - Roll out imputation
INFO - No GWAS intersection for region
Level 9 - Processing region 2/131 [1961168.0, 3666172.0]
Level 8 - Roll out imputation
INFO - No GWAS intersection for region
Level 9 - Processing region 3/131 [3666172.0, 4320751.0]
Level 8 - Roll out imputation
INFO - No GWAS intersection for region
...
Level 9 - Processing region 130/131 [245343444.0, 247181216.0]
Level 8 - Roll out imputation
INFO - No GWAS intersection for region
Level 9 - Processing region 131/131 [247181216.0, 248945267.0]
Level 8 - Roll out imputation
INFO - No GWAS intersection for region
INFO - Finished in 78.23940965719521 seconds

My harmonized gwas file looks like:
variant_id non_effect_allele effect_allele effect_size standard_error pvalue chromosome position zscore sample_size panel_variant_id frequency
rs143225517 T C -0.0238 0.0215 0.2705 chr1 816376 -1.1019118 8293 chr1_816376_T_C_b38 0.1203883495145631
rs3094315 G A 0.0253 0.0196 0.1924 chr1 817186 1.3035121 8293 chr1_817186_G_A_b38 0.8388349514563107

I wonder what's going on here? And how do I fix it? Thanks.

Best
Sophie

[Alvaro Barbeira]

Hi Sophie,

Feel free to share here your complete command line instructions and I'll take a look.

Best,

Alvaro

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[Sophie Chan]

Hi Alvaro,

My command is like:

python $GWAS_TOOLS/gwas_summary_imputation.py \

-by_region_file $DATA/eur_ld.bed.gz \

-gwas_file $DATA/summary_stats/harmonized_gwas/IL6.harmonised.txt.gz \

-parquet_genotype $DATA/reference_panel_1000G/chr1.variants.parquet \

-parquet_genotype_metadata $DATA/reference_panel_1000G/variant_metadata.parquet \

-window 100000 \

-parsimony 7 \

-chromosome 1 \

-regularization 0.1 \

-frequency_filter 0.01 \

--standardise_dosages \

-output $OUTPUT/IL6_chr1_ff0.01_by_region.txt.gz

The guide I followed is https://github.com/hakyimlab/summary-gwas-imputation/wiki/GWAS-Harmonization-And-Imputation and https://github.com/hakyimlab/MetaXcan/wiki/Tutorial:-GTEx-v8-MASH-models-integration-with-a-Coronary-Artery-Disease-GWAS.

Thanks,

Sophie

[Alvaro Barbeira]

Hi Sophie,

I can spot nothing amiss. Unfortunately, you would have to debug the process when running your data, using the python debugger.

I would start at _gaussian_by_region method in src\genomic_tools_lib\summary_imputation\SummaryInputation.py of the gwas-summary-imputation tools.

Best,

Alvaro

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[Katya O]

Sophie and Alvaro,

Was this ever resolved? I am getting the same issue - "loaded 0 GWAS variants," etc.

Thank you,

Katya