tRNA_class: Classify tsRNA/tRFs from PAC object

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

Classify tsRNA/tRFs from PAC object

Description

Classifying tRFs/tsRNA into 5'-tRF/halves, 3'-tRFs/halves, i'-tRFs/halves, as well as acceptor and decoder isotypes.

Usage

tRNA_class(PAC, map, terminal = 5)

Arguments

PAC	PAC-list object.
map	Map object with loop annotations generated by PAC_mapper followed by map_rangetype functions. Note, only full length reference tRNAs annotated with 3 loops in the ss file (see: map_rangetype) are used in the classifications. Explanation: sometimes tRNAscan-SE scans results in ss files with incomplete secondary structures with either more or fewer loops than the D, T and anticodon loops found in canonical tRNAs. Such tRNAs will be removed from the analysis.
terminal	Integer setting the terminal tolerance. Example, when terminal is set to 5 (default) sequenced reads starting within the 5 first nucleotides of the full-length tRNA reference will be classifed as 5'. If it instead ends within the 5 last nucleotides of the full-length tRNA reference it will be classified as 3'. If a read neither starts nor ends within the terminal threshold it will be classified as i' (internal). Note, for tsRNA/tRF classification we recommend a threshold of terminal=2 (not default). Advisably, however, PAC_mapper runs with N_up = "NNN" and N_down = "NNN" when mapping tsRNA/tRFs. Thus, the default threshold of 5 is used when full-length tRNAs has been extended with NNN up- and downstream to compensate for possible fragments from mature tRNAs (3+2). Always double check the exact fragment using PAC_covplot.

Details

Given a map object with range types generated by PAC_mapper followed by map_rangetype functions, sequences in a PAC object are classified according the terminals (5'/3'/i'), anticodon loop (half/tRF), and isotype (decoder/acceptor) of the full length tRNA.

Value

Merged PAC object with an extended Anno table containing the tRF/tsRNA classifications.

See Also

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

Other PAC analysis: PAC_covplot(), PAC_deseq(), PAC_filter(), PAC_filtsep(), PAC_gtf(), PAC_jitter(), PAC_mapper(), PAC_nbias(), PAC_norm(), PAC_pca(), PAC_pie(), PAC_saturation(), PAC_sizedist(), PAC_stackbar(), PAC_summary(), PAC_trna(), as.PAC(), filtsep_bin(), map_rangetype()

Examples

# Important: See ?PAC_trna on how to do tRNA analysis using Seqpac 

#'###########################################################
### tRNA classification in seqpac 
# (More details see vignette and manuals.)

##-------------------------------##
## Setup environment for testing ##

# First create an annotation blank PAC with group means
load(system.file("extdata", "drosophila_sRNA_pac_filt_anno.Rdata", 
                package = "seqpac", mustWork = TRUE))
anno(pac) <- anno(pac)[,1, drop=FALSE]
pac_trna <- PAC_summary(pac, norm = "cpm", type = "means", 
                       pheno_target=list("stage"), merge_pac = TRUE)


# Then load paths to example trna ref and ss files
trna_ref <- system.file("extdata/trna2", "tRNA2.fa", 
                       package = "seqpac", mustWork = TRUE)

ss_file <- system.file("extdata/trna2", "tRNA2.ss",
                      package = "seqpac", mustWork = TRUE)


##--------------------------------------##
## Create a map object using PAC_mapper ##
map_object <- PAC_mapper(pac_trna, ref=trna_ref, 
                        N_up = "NNN", N_down = "NNN",
                        mismatches=0, threads=2, 
                        report_string=TRUE, override = TRUE)
# Warning: override = TRUE, will remove everything in temporary output path.
# Note: bowtie indexes are not needed for PAC_mapper.


##-------------------------------------------##
## Classify tRNA fragment with map_rangetype ## 

# Classify according to loop structure using ss file provided with seqpac
map_object_ss <- map_rangetype(map_object, type="ss", ss=ss_file, 
                              min_loop_width=4)          
# Note 1: You may download your own ss file at for example GtRNAdb
# Note 2: The ss file must match the reference used in creating the map_object

map_object_ss[[1]]

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