diff 01_htseq_count_analysis.Rmd @ 0:dcf65671e56a draft

planemo upload commit 841d8b22bf9f1aaed6bfe8344b60617f45b275b2-dirty

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+---
+title: 'HTSeq-count Analysis'
+output:
+    html_document:
+      highlight: pygments
+---
+
+## Job script
+
+```{bash, echo=FALSE}
+sh ${TOOL_INSTALL_DIR}/build-and-run-job-scripts.sh > ${REPORT_FILES_PATH}/log.txt 2>&1
+```
+
+```{r echo=FALSE, comment='', results='asis'}
+cat('```bash\n')
+cat(readLines(paste0(Sys.getenv('REPORT_FILES_PATH'), '/htseq-count.sh')), sep = '\n')
+cat('\n```')
+```
+
+## Counts
+
+Write data into a CSV file.
+
+```{r, echo=TRUE}
+count_data = read.table(paste0(opt$X_d, '/counts.txt'), row.names = 1)
+sample_names = trimws(strsplit(opt$X_B, ',')[[1]])
+colnames(count_data) = rep(sample_names, length = ncol(count_data))
+
+
+# modify column names
+count_data = data.frame(feature_id = rownames(count_data), count_data)
+write.csv(count_data, 
+          file = paste0(Sys.getenv('REPORT_FILES_PATH'), '/count_data.csv'),
+          quote = FALSE, row.names = FALSE)
+```
+
+Display the top 1000 rows with largest average counts.
+
+```{r echo=TRUE}
+# Sort count table by count average
+rownames(count_data) = count_data$feature_id
+count_data = count_data[, -1]
+sorted_ct_table = count_data[order(rowMeans(count_data), decreasing = TRUE), ]
+DT::datatable(head(sorted_ct_table, 1000))
+```
+
+