Commit a42c7580 authored by Leon-Charles Tranchevent's avatar Leon-Charles Tranchevent
Browse files

Refactoring step 04 to process all datasets at once (Second part - after match).

parent f2e78969
......@@ -15,7 +15,5 @@ ps:
@sbatch ${CODE_FOLDER}create_probelists.sh
match:
@sbatch ${CODE_FOLDER}match_probes.sh
biomarker:
@sbatch ${CODE_FOLDER}plot_biomarkers.sh
doc:
@sbatch ${CODE_FOLDER}doc.sh
@sbatch ${CODE_FOLDER}doc.sh
\ No newline at end of file
......@@ -122,29 +122,11 @@ do
echo ' }' >> ${OUTPUT_FOLDER}results_summary.tex
echo '\end{figure}' >> ${OUTPUT_FOLDER}results_summary.tex
echo '' >> ${OUTPUT_FOLDER}results_summary.tex
done
echo '\clearpage' >> ${OUTPUT_FOLDER}results_summary.tex
echo '' >> ${OUTPUT_FOLDER}results_summary.tex
# Per biomarker analysis.
nbBiomarkers=${#biomarkers__name[@]}
for (( i=0; i<$nbBiomarkers; i++ ))
do
biomarkerName=${biomarkers__name[$i]}
biomarkerTissue=${biomarkers__tissue[$i]}
biomarkerTissueForFile=${biomarkerTissue/ /_}
echo '\begin{figure}[ht]' >> ${OUTPUT_FOLDER}results_summary.tex
echo ' \centering' >> ${OUTPUT_FOLDER}results_summary.tex
echo ' \includegraphics[scale=0.43]{'"$OUTPUT_FOLDER"'Biomarker_'"${biomarkerTissueForFile}"'_'"${biomarkerName}"'.png}' >> ${OUTPUT_FOLDER}results_summary.tex
echo ' \caption{Expression values for biomarker '"${biomarkerName}"' for both DA and SN tissues.' >> ${OUTPUT_FOLDER}results_summary.tex
echo ' (Top) Usage of expression values as derived from pre-processing. (Bottom) Usage of Z-scores ' >> ${OUTPUT_FOLDER}results_summary.tex
echo ' derived from the expression values. (Left) VSN correction applied. (Right) No VSN correction applied.}' >> ${OUTPUT_FOLDER}results_summary.tex
echo '\end{figure}' >> ${OUTPUT_FOLDER}results_summary.tex
echo '\clearpage' >> ${OUTPUT_FOLDER}results_summary.tex
echo '' >> ${OUTPUT_FOLDER}results_summary.tex
done
done
# Print footer
echo '' >> ${OUTPUT_FOLDER}results_summary.tex
......
......@@ -377,7 +377,8 @@ for (i in seq_len(length(config$platforms))) {
dplyr::rename(!!platform$platform_name := probesets)
rm(deps_matching, matching_dataset, platform)
} # End for each platform.
rm(i, genes_probe_matching, geneset_probe_matching)
#rm(i, genes_probe_matching, geneset_probe_matching)
rm(i)
# We merge the dataframes, create one global matching dataframe and save it.
global_matching_data_merged <- NULL
......
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