Last updated: 2020-06-21
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Knit directory: analysis_pipelines/
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| Rmd | 4be4f67 | kevinlkx | 2020-05-25 | wflow_publish(“analysis/GWAS_sumstats.Rmd”) |
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| Rmd | c4cd35c | kevinlkx | 2020-05-24 | wflow_publish(“analysis/GWAS_sumstats.Rmd”) |
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| Rmd | c9c19d4 | kevinlkx | 2020-05-24 | wflow_publish(“analysis/GWAS_sumstats.Rmd”) |
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| Rmd | c721074 | kevinlkx | 2020-05-24 | wflow_publish(“analysis/GWAS_sumstats.Rmd”) |
| html | 8f14331 | kevinlkx | 2020-05-24 | Build site. |
| Rmd | d861aa6 | kevinlkx | 2020-05-24 | wflow_publish(“analysis/GWAS_sumstats.Rmd”) |
.sumstats formatConvert GWAS summary statistics to the LD-score format summary statistics (.sumstats) format using munge_sumstats.py, see ldsc wiki “Summary-Statistics-File-Format”
.sumstats format on RCCProcessed GWAS summary stats used in m6A-QTL paper (mostly from Jean’s GWAS collection, listed below) can be found on RCC: /project2/xinhe/kevinluo/GWAS/GWAS_summary_stats/GWAS_collection/ldsc_format/
/project2/xinhe/kevinluo/GWAS/GWAS_summary_stats/GWAS_summary_alkesgroup/independent_sumstats//project2/xinhe/kevinluo/GWAS/GWAS_summary_stats/GWAS_summary_alkesgroup/sumstats_formatted/Jean Morrison made a large collection of GWAS summary statistics from different sources and the data are shared in RCC /project2/compbio/gwas_summary_statistics/ directory. You can find more details in the README file in that directory, also in Xin He lab wiki. You can convert those data to LDSC .sumstats format using munge_sumstats.py.