02-quality-control-E-genefiltering.Rmd

```{r parameters-and-defaults, include = FALSE}
module <- "scRNAseq"
section <- "quality_control"
```

```{r parameter-merge, include = FALSE}
local_params <- module %>%
  options() %>%
  magrittr::extract2(module) %>%
  magrittr::extract2(section) %>%
  ReporteR.base::validate_params(parameters_and_defaults)
```

```{r scRNAseq-quality-control-E-genefiltering-checks, include = FALSE, echo = FALSE}
assertive.files::assert_all_are_readable_files(local_params$gene_filter_yml)

gene_filter <- yaml::read_yaml(local_params$gene_filter_yml)

# Check filter names
assertive.properties::assert_has_names(gene_filter)

# Assemble gene filter
filter_functions <- lapply(names(gene_filter), function(f) {
  fn <- strsplit(f, "::")[[1]]
  what <- if(length(fn)==1) {
    get(fn[[1]], envir=parent.frame(), mode="function")
  } else {
    get(fn[[2]], envir=asNamespace(fn[[1]]), mode="function")
  }
  do.call(what = what, args = gene_filter[[f]])
})
```

### Gene filtering

Gene filtering strives for the identification of features that should be excluded from downstream analysis, e.g. because they are lowly expressed and therefore do not allow a statistically robust quantification. Gene filtering is accomplished by applying so-called **filter functions** to the raw data, excluding low quality samples identified above.

```{r scRNAseq-quality-control-E-genefiltering-processing, include = FALSE, echo = FALSE}
keep_genes <- genefilter::genefilter(SummarizedExperiment::assay(object[, SummarizedExperiment::colData(object)$qc_status == "pass"], local_params$assay), genefilter::filterfun(filter_functions))
keep_genes <- ifelse(keep_genes, "pass", "fail")
SummarizedExperiment::rowData(object)$qc_status <- keep_genes
```

In total, **`r sum(keep_genes == "fail")`** features (`r round(sum(keep_genes == "fail")/length(keep_genes) * 100)`%) are excluded from downstream analysis (Table \@ref(tab:scRNAseq-quality-control-E-genefiltering-table)). 

```{r scRNAseq-quality-control-E-genefiltering-table, results = "asis"}
if(assertive.properties::is_non_empty(local_params$tabulate_features)) {
  Feature <- gsub("_", "-", SummarizedExperiment::rowData(object)[, local_params$tabulate_features])
  tbl <- stats::ftable(SummarizedExperiment::rowData(object)$qc_status, Feature, row.vars = 2)
  extra_caption <- paste0("by ", gsub("_", "-", local_params$tabulate_features))
} else {
  tbl <- stats::ftable(SummarizedExperiment::rowData(object)$qc_status)
  extra_caption <- ""
}

xftbl <- xtable::xtableFtable(tbl, method = "compact", caption = paste("(\\#tab:scRNAseq-quality-control-E-genefiltering-table)Number of features passing/failing quality control", extra_caption))
xtable::print.xtableFtable(xftbl, booktabs = TRUE, comment = FALSE, timestamp = NULL)
```