trinotateR is an R package to summarize annotation reports from Trinotate. Use devtools to install the package.

library(devtools)
install_github("cstubben/trinotateR")

read_trinotate loads a tab-delimited Trinotate annotation report into a data.table for faster data manipulation.

library(trinotateR)
x <- read_trinotate("Trinotate_report.xls")
# Read 75228 rows

summary_trinotate returns the number of unique and total annotations in the table.

summary_trinotate(x)

                      unique total
gene_id                56144 75228
transcript_id          65130 75228
prot_id                59260 59260
prot_coords            26889 59260
TrEMBL_Top_BLASTX_hit  38788 47358
TrEMBL_Top_BLASTP_hit  35836 43048
Pfam                   20897 25504
sprot_Top_BLASTX_hit   18586 23806
gene_ontology_blast     5996 23569
sprot_Top_BLASTP_hit   18267 22347
gene_ontology_pfam      1428 17254
eggnog                  1456 15225
TmHMM                   6236  7907
SignalP                  100  5947
RNAMMER                   20   129
transcript                 0     0
peptide                    0     0

Most of the annotations contain mutliple hits in a backtick-delimited list and each hit contains multiple fields in a caret-delimited list. For example, the second Pfam annotation below contains two hits and each hit contains a pfam id, symbol, name, alignment and e-value. The split_pfam functions splits multiple hits and fields, so the second Pfam annotation is now printed in rows 2 and 3 below.

na.omit(x$Pfam)[1:2]

[1] "PF02586.9^DUF159^Uncharacterised ACR, COG2135^37-105^E:9.1e-20"                                                                                       
[2] "PF01386.14^Ribosomal_L25p^Ribosomal L25p family^50-139^E:3.8e-07`PF14693.1^Ribosomal_TL5_C^Ribosomal protein TL5, C-terminal domain^154-209^E:3.5e-09"

x1 <- split_pfam(x)
# 46040 Pfam annotations
head(x1,3)

            gene       transcript protein    pfam          symbol                                     name   align  evalue
1: GG10000|c0_g1 GG10000|c0_g1_i1 m.81222 PF02586          DUF159             Uncharacterised ACR, COG2135  37-105 9.1e-20
2: GG10001|c2_g1 GG10001|c2_g1_i1 m.81232 PF01386  Ribosomal_L25p                    Ribosomal L25p family  50-139 3.8e-07
3: GG10001|c2_g1 GG10001|c2_g1_i1 m.81232 PF14693 Ribosomal_TL5_C Ribosomal protein TL5, C-terminal domain 154-209 3.5e-09

Finally, the summary_pfam lists the 3278 unique Pfam identifiers and the total number of genes, transcripts and proteins with a Pfam annotation.

x2 <- summary_pfam(x1)
# 3278 rows
head(x2)

      pfam      symbol                       name genes transcripts proteins total
1: PF00069     Pkinase      Protein kinase domain   655         953      999  1030
2: PF07714 Pkinase_Tyr    Protein tyrosine kinase   619         909      952   989
3: PF00400        WD40   WD domain, G-beta repeat   344         431      445   953
4: PF13504       LRR_7        Leucine rich repeat   333         383      393  2263
5: PF00023         Ank             Ankyrin repeat   299         367      404  1029
6: PF12796       Ank_2 Ankyrin repeats (3 copies)   255         321      363   739

The summary table also includes a count attribute with the number of unique genes, transcripts and proteins with a Pfam annotation, as well as the total number of annotations. In this example, there are 19418 unique genes with a Pfam annotation (35% of all genes) and 29952 total annotations to genes (since genes may have more than one Pfam annotation).

attr(x2, "count")

            unique annotations
Pfam          3278       46040
genes        19418       29952
transcripts  23700       37093
proteins     25504       38144

Load the DataTables library to browse and search within the table using RStudio. The screenshot below shows the Pfam DataTable while searching for "photos" - the full table with all 3278 rows is available here.

library(DT)
 z <- data.frame(x2)
 z$pfam <- paste0('<a href="http://pfam.xfam.org/family/', z$pfam, '">', z$pfam,  '</a>')
 datatable(z , escape=1, options = list( pageLength = 25 ) )

The trinotateR packages includes similar functions to split BLAST, GO, and eggnog columns. Additional functions to plot eggnogs and map the UniRef90 hits in the TrEMBL_Top_BLASTP_hit column to cluster names, KEGG pathways and any other UniProt database cross-reference will be described on the wiki pages.