simplify_reanno: Generates one-hit hierarchial biotype annotation

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

Generates one-hit hierarchial biotype annotation

Description

simplify_reanno adds hierarchical classification to PAC.

Usage

simplify_reanno(
  input,
  hierarchy,
  mismatches = 2,
  bio_name = "Biotypes",
  merge_pac = FALSE,
  target_columns = NULL
)

Arguments

input	Data.frame with biotype/mismatch matrix generated by add_reanno. A PAC-list object can also be provided here where the Anno data.frame will be used as input. Important, PAC objects need biotype columns generated by add_reanno.
hierarchy	List with character vectors. The vectors search terms constructed as regular expressions that will be parsed to grepl() and searched for in the mismatch biotype reannotation matrix (colnames: mis0_bio, mis1_bio, mis2_bio, mis3_bio). Important hierarchy is order sensitive. For example if hierarchy is defined as list(rRNA="rRNA", miRNA="miRNA", piRNA="piRNA") a sequence annotated with 0 mismatches for all three biotypes will only be reported as rRNA since this biotype was put first in the list. Sequences annotated to neither of the biotypes listed in hierarchy, that is still annotated to something will be assigned as "other". Sequences without an annotation down to the specified mismatch level (mismatches will be assigned as "no_anno".
mismatches	Integer indicating the number of allowed mismatches. Note that this value can never be larger than the maximum number of mismatches used in the reannotation workflow (default=0).
bio_name	Character naming the final biotype column (default="Biotype")
merge_pac	Logical whether the simplified annotation column should automatically be added to the Anno object if a PAC list object were given as input (default=FALSE).
target_columns	Character vector naming the target columns for the reannotation matrix. When target_columns=NULL(default), the function assumes that one (and only one) reannotation matrix for biotypes generatated by add_reanno is present in anno(PAC) (colnames = mis0_bio, mis1_bio, mis2_bio etc). With target_columns two alternative reannotation matrices can be discriminated.

Details

This function deals with and can be used to explores the effect of multimapping. Given a biotype reannotation matrix (colnames = mis0_bio, mis1_bio, mis2_bio etc) created by add_reanno and usually added to the Anno data.frame of a PAC object, the function will generated a one-hit biotype vector according to a user-defined biotype hierarchy.

Value

Character vector with single best-hit biotypes with fewest mismatches.

See Also

http://bowtie-bio.sourceforge.net/index.shtml for information about Bowtie https://github.com/Danis102 for updates on the current package.

Other PAC reannotation: add_reanno(), as.reanno(), import_reanno(), make_conv(), make_reanno(), map_reanno()

Examples

#' ######################################################### 
##### hierarchical classification using simplify_reanno
closeAllConnections()
######################################################### 
##### Create an reanno object

### First, if you haven't already generated Bowtie indexes for the included
# fasta references you need to do so. If you are having problem see the small
# RNA guide (vignette) for more info.
                                                             
 ## tRNA:
 trna_file <- system.file("extdata/trna", "tRNA.fa", 
                          package = "seqpac", mustWork = TRUE)
 trna_dir <- dirname(trna_file)
 
 if(!sum(stringr::str_count(list.files(trna_dir), ".ebwt")) ==6){     
     Rbowtie::bowtie_build(trna_file, 
                           outdir=trna_dir, 
                           prefix="tRNA", force=TRUE)
                           }
 ## rRNA:
 rrna_file <- system.file("extdata/rrna", "rRNA.fa", 
                          package = "seqpac", mustWork = TRUE)
 rrna_dir <- dirname(rrna_file)
 
 if(!sum(stringr::str_count(list.files(rrna_dir), ".ebwt")) ==6){
     Rbowtie::bowtie_build(rrna_file, 
                           outdir=rrna_dir, 
                           prefix="rRNA", force=TRUE)
                           }
                           
                           
##  Then load a PAC-object and remove previous mapping from anno:
 load(system.file("extdata", "drosophila_sRNA_pac_filt_anno.Rdata", 
                   package = "seqpac", mustWork = TRUE))
 anno(pac) <- anno(pac)[,1, drop = FALSE]

                                    
##  You may add an output path of your choice, but here we use a temp folder:
 output <- paste0(tempdir(),"/seqpac/test")
 ref_paths <- list(trna= trna_file, rrna= rrna_file)
 
##  Then map the PAC-object against the fasta references. 
# Warning: if you use your own data, you may want to use override=FALSE, to avoid
# deleting previous mapping by mistake.

map_reanno(pac, ref_paths=ref_paths, output_path=output,
               type="internal", mismatches=1,  import="biotype", 
               threads=2, keep_temp=FALSE, override=TRUE)
 
##  Then import and generate a reanno-object of the temporary bowtie-files
reanno_biotype <- make_reanno(output, PAC=pac, mis_fasta_check = TRUE)
 
                                    
## Now make some search terms against reference names to create shorter names
# Theses can be used to create factors in downstream analysis
# One search hit (regular expressions) gives one new short name 

bio_search <- list(
              rrna=c("5S", "5.8S", "12S", "16S", "18S", "28S", "pre_S45"),
              trna =c("_tRNA", "mt:tRNA"))
 
 
## You can merge directly with your PAC-object by adding your original 
# PAC-object, that you used with map_reanno, to merge_pac option.

pac <- add_reanno(reanno_biotype, bio_search=bio_search, 
                       type="biotype", bio_perfect=FALSE, 
                       mismatches = 1, merge_pac=pac)

## Hierarchical classification with simplify_reanno
table(anno(pac)$mis0_bio)
table(anno(pac)$mis1_bio)

# Setup hierarchy(rRNA prioritized before tRNA) 
hierarchy_1 <- list(rRNA="rrna_",
                  tRNA="trna_")

# Setup hierarchy(specifies the hierarchy among rRNA)
hierarchy_2 <- list(r18S="rrna_18S",
                    r28S="rrna_28S",
                    r5.8S="rrna_5.8S",
                    r5S="rrna_5S",
                    pre45S="pre_S45",
                    other_rrna="rrna_other") 

# No mistmach for hierarchy_1:
test1 <- simplify_reanno(input=pac, hierarchy=hierarchy_1, mismatches=0, 
                      bio_name="Biotypes_mis0", merge_pac=FALSE)
                      
# Up to 2 mistmaches for rRNA hierarchy_2                      
test2 <- simplify_reanno(input=pac, hierarchy=hierarchy_2, mismatches=1, 
                      bio_name="rRNA_biotypes_mis2", merge_pac=FALSE)


table(test1$Biotypes_mis0) 
table(test2$rRNA_biotypes_mis2)
                     
# You can add the new column to your PAC-object using merge_pac=TRUE:
pac <- simplify_reanno(input=pac, hierarchy=hierarchy_2, mismatches=1, 
                      bio_name="rRNA_biotypes_mis1", merge_pac=TRUE)

table(anno(pac)$rRNA_biotypes_mis1)

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