fx bugs & update docs

R/ascat.R

@@ -148,6 +148,7 @@ gcap.runASCAT <- function(tumourseqfile,
             BED_file = BED_file,
             probloci_file = probloci_file,
             gender = gd,
+            genomeVersion = genome_build,
             chrom_names = chrom_names,
             min_base_qual = min_base_qual,
             min_map_qual = min_map_qual,
@@ -164,7 +165,7 @@ gcap.runASCAT <- function(tumourseqfile,
             genomeVersion = genome_build
           )
 
-          ascat.bc <- ASCAT::ascat.correctLogR(ascat.bc, GCcontentfile, replictimingfile, genomeVersion = genome_build)
+          ascat.bc <- ASCAT::ascat.correctLogR(ascat.bc, GCcontentfile, replictimingfile)
 
         } else {
           ascat.prepareHTS(
@@ -223,6 +224,12 @@ gcap.runASCAT <- function(tumourseqfile,
           ascat.output = c(ascat.output, list(QC = QC))
         }
 
+        # Clean unnecessary files
+        fls = list.files(pattern = "alleleFrequencies", full.names = TRUE)
+        if (length(fls) > 0) {
+          file.remove(fls)
+        }
+
         saveRDS(ascat.output, file = paste0(id, ".ASCAT.rds"))
 
         lg$info("job {id} done")

README.md

@@ -14,18 +14,6 @@ sources are preferred as input of **gcap** .
 
 ## Installation
 
-### Download reference files (WES bam data only)
-
-For advanced users, you can prepare the reference files by following the instructions
-from <https://github.com/shixiangwang/ascat/tree/v3.0>.
-
-We recommend all users directly download the reference files from the links below:
-
-- [Curated reference files for GCAP (WES)](https://zenodo.org/records/6364977)
-
-> The prediction model was built with data on the top of hg38 genome build, so 
-hg38-based BAM file input is more recommended.
-
 ### Install alleleCount (WES bam data only)
 
 [**alleleCount**](https://github.com/cancerit/alleleCount) is required to run **ASCAT** on WES bam data,
@@ -41,7 +29,7 @@ if you use **conda** or other approaches, please set the path when you use corre
 
 ### Install ASCAT (required)
 
-#### Latest ASCAT
+#### Latest ASCAT v3
 
 From v1.2, GCAP uses the latest version of ASCAT. Install **ASCAT** v3 in R console from GitHub with:
 
@@ -52,7 +40,17 @@ remotes::install_github('VanLoo-lab/ascat/ASCAT')
 
 We have provided generated reference files above, but sometimes you may want to generate the reference data for yourself, in such case, please refer to <https://github.com/VanLoo-lab/ascat> for generating the required allele-specific copy number data.
 
-#### A fixed version of ASCAT
+**Reference files**:
+
+The reference files are required in ASCAT for copy number calling.
+
+- [Curated reference files for WES](https://github.com/VanLoo-lab/ascat/tree/master/ReferenceFiles/WES)
+
+> The prediction model was built with data on the top of hg38 genome build, so 
+hg38-based BAM file input is more recommended.
+
+
+#### A fixed version of ASCAT v3
 
 In our manuscript, we used a fixed version of ASCAT for the GCAP data pre-processing (modified and adapted for GCAP workflow in HPC). It does not fit the R version `>=4.3`.
 
@@ -64,6 +62,10 @@ remotes::install_github("ShixiangWang/ascat@v3-for-gcap-v1", subdir = "ASCAT")
 # See https://github.com/ShixiangWang/gcap/issues/27
 ```
 
+**Reference files**:
+
+- [Curated reference files for WES](https://zenodo.org/records/6364977)
+
 ### Alternatives to ASCAT
 
 For the latest version of GCAP, [sequenza](https://shixiangwang.github.io/gcap/reference/gcap.workflow.seqz.html) or [facets](https://shixiangwang.github.io/gcap/reference/gcap.workflow.facets.html) are supported for preprocessing the bam data, please refer to the provided links for usage.
@@ -80,6 +82,9 @@ install.packages('gcap', repos = c('https://shixiangwang.r-universe.dev', 'https
 remotes::install_github("ShixiangWang/gcap")
 ```
 
+> To work with the **fixed version of ASCAT**, you have to install version commits no more newer than `42f216d` (tag `v1.1.5`),
+> i.e., please use `remotes::install_github("ShixiangWang/[email protected]")` and the R version should below v4.3.
+
 If you would like to use CLI program in Shell terminal, run the following code in your R console after installation:
 
 ```r