make_PAC: Make PAC

In Danis102/seqpac: Seqpac: A Framework for smallRNA analysis in R using Sequence-Based Counts

Make PAC

Description

make_PAC Compiles, order and checks the assumptions of a PAC file.

Usage

make_PAC(counts, pheno = NULL, anno = NULL, output = "S4")

Arguments

counts	Data.frame representing a counts table, with column names as sample names and sequence names as row names. Contains the counts for each sequence across the samples. Can be generated by the make_counts.
pheno	Data.frame with sample names as row names containing metadata about each sample. Can be generated by the make_pheno function.
anno	Data.frame with unique sequences as row names containing metadata about each sequence. If anno=NULL, a simple Anno data.frame will automatically be generated from the the sequence names in counts. Annotations for each sequence can be extended using for example the reanno workflow (see vignette).
output	Character indicating output format. If type="S4" (default), then the PAC object is returned as an S4 object. If type="S3", the PAC object will be returned as a list of data.frames

Details

Given a pheno, an anno and a counts data.frames the functions will safely generate a simple PAC list-object.

Value

Ordered PAC list object, checked for compatibility with downstream analysis in seqpac.

See Also

https://github.com/Danis102 for updates on the current package.

Other PAC generation: PAC_check(), create_PAC(), make_counts(), make_cutadapt(), make_pheno(), make_trim(), merge_lanes()

Examples

### First make counts 

# Seqpac includes strongly down-sampled smallRNA fastq.
sys_path = system.file("extdata", package = "seqpac", mustWork = TRUE)
input <- list.files(path = sys_path, pattern = "fastq", all.files = FALSE,
                full.names = TRUE)

# Notice that make_counts will generate another temp folder, that will 
# be emptied on finalization. By setting save_temp=TRUE you may save the 
# content.  
 
counts  <- make_counts(input, threads=2, parse="default_neb",
                       trimming="seqpac", plot=TRUE,
                       evidence=c(experiment=2, sample=1))

colnames(counts$counts)

### Then generate a phenotype table with make_pheno

#  Note:  'Sample_ID' column needs to be similar IDs as 
#          colnames in the counts table. You may also 
#          specify a path to a txt file.

Sample_ID <- colnames(counts$counts)

pheno <- data.frame(Sample_ID=Sample_ID,
                       Treatment=c(rep("heat", times=1), 
                                   rep("control", times=2)),
                       Batch=rep(c("1", "2", "3"), times=1)) 

pheno <- make_pheno(pheno=pheno, progress_report=counts$progress_report, 
                     counts=counts$counts)


pheno 

# Note that progress report from make_counts is added if you specify it  
     
### Lastly combine into PAC

pac <- make_PAC(pheno=pheno, counts=counts$counts)


pac
names(pac)

# Note: a simple annotation table is added automatically.
head(anno(pac))

# Clean up temp
closeAllConnections()
fls_temp  <- list.files(tempdir(), recursive=TRUE, full.names = TRUE)
file.remove(fls_temp, showWarnings=FALSE)

Danis102/seqpac documentation built on Aug. 26, 2023, 10:15 a.m.