precimed / mixer

Causal Mixture Model for GWAS summary statistics
GNU General Public License v3.0
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Problem visualising results #75

Closed jmkyang closed 1 year ago

jmkyang commented 1 year ago

Hi,

I am using the singularity version of MiXeR and adapted the MIXER_REAL.job script to my cluster and data. This runs bit after each line it outputs: ERROR: ld.so: object '/sara/tools/xalt/xalt/lib64/libxalt_init.so' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored.

I am then able to successfully combine the data using e.g. python /tools/mixer/precimed/mixer_figures.py combine --json BDI_female.fit.rep@.json --out BDI_female.fit

However, when running: python /tools/mixer/precimed/mixer_figures.py one --json BDI_female.fit.json BDI_male.fit.json --out BDI_F_and_BDI_M.fit --statistic mean std --ext svg

I receive the following:

ERROR: ld.so: object '/sara/tools/xalt/xalt/lib64/libxalt_init.so' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored.
generate BDI_F_and_BDI_M.fit.csv from 2 json files...
Done.
Skip generating power plots, data not available. Did you include --power-curve in your "python mixer.py fit" command?
--json argument is a wild-card (contains *), skip figures generation

And similarly when running: python /tools/mixer/precimed/mixer_figures.py two --json-fit PGC4_BDI_FvsM.fit.json --json-test PGC4_BDI_FvsM.test.json --out PGC4_BDI_FvsM --statistic mean std --ext svg

I get the following:

ERROR: ld.so: object '/sara/tools/xalt/xalt/lib64/libxalt_init.so' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored.
generate PGC4_BDI_FvsM.csv from 2 json files...
Done.
/tools/mixer/precimed/mixer/figures.py:264: RuntimeWarning: All-NaN slice encountered
  plot_y[i, :] = plot_y[i, :] - np.nanmin(plot_y[i, :])
/tools/mixer/precimed/mixer/figures.py:266: RuntimeWarning: Mean of empty slice
  plot_y = np.nanmean(plot_y, 0)
Generated PGC4_BDI_FvsM.svg

But no plots are generated. I am new to using containers and am not sure what the problem is, or if i should try downloading MiXeR manually instead? Any help would be much appreciated!

Thanks, Jess

jmkyang commented 1 year ago

In addition to this, I have also tried: python /tools/mixer/precimed/mixer_figures.py one --json BDI_female.test.json --out BDI_F.test --statistic mean std --ext svg

And get the output:

ERROR: ld.so: object '/sara/tools/xalt/xalt/lib64/libxalt_init.so' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored.
generate BDI_F.test.csv from 1 json files...
Done.
HAS POWER? True
/tools/mixer/precimed/mixer/figures.py:338: UserWarning: FixedFormatter should only be used together with FixedLocator
  plt.gca().set_xticklabels(labels=['10K', '100K', '1M', '10M', '100M'])
/tools/mixer/precimed/mixer/figures.py:340: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
  plt.axes().set_yticklabels(labels=['0', '20', '40', '60', '80', '100'])
Generated BDI_F.test.power.svg
Generated BDI_F.test.qq.svg
Skip generating qq plots (3x3 bins of MAF and LD score), data not available. Did you include --qq-plots in your "python mixer.py fit" command?
jmkyang commented 1 year ago

Finally realised that the issue was with the "--ext svg" tag which I copied from the mixer_real.md file. As I'm new to these file types and was not sure what this flag did I didn't realise I had to remove this to get the .png files I was expecting. Maybe this could be added for info for future?