Table 3.

Plastid’s command-line scripts automate common analysis tasks

Analysis of count and alignment data
counts_in_region	Count the number of read alignments covering arbitrary regions of interest in the genome, and calculate read densities (in reads per nucleotide and in RPKM) over these regions
cs	Count the number of read alignments and calculate read densities (in RPKM) specifically for genes and sub-regions (5′ UTR, CDS, 3′ UTR), correcting gene and sub-region boundaries for overlapping genes
get_count_vectors	Fetch vectors of counts at each nucleotide position in one or more regions of interest, saving each vector as its own line-delimited text file
make_wiggle	Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-protected footprints at their P-sites), for visualization in a genome browser
metagene	Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of interest
phase_by_size	Estimate sub-codon phasing in ribosome profiling data
psite	Estimate position of ribosomal P-site within ribosome profiling read alignments as a function of read length
Manipulation of genomic features
crossmap	Empirically annotate multimapping regions of a genome, given alignment criteria
gff_parent_types	Determine parent-child relationships of features in a GFF3 file
reformat_transcripts	Convert transcripts between BED, BigBed, GTF2, GFF3, and PSL formats
findjuncs	Find all unique splice junctions in one or more transcript annotations, and optionally export these in Tophat’s.juncs format
slidejuncs	Compare a set of splice junctions to a reference set, and, if possible with equal sequence support, slide discovered junctions to compatible known junctions