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tidysq contains tools for analysis and manipulation of biological
sequences (including amino acid and nucleic acid – e.g. RNA, DNA –
sequences). Two major features of this package are:
-
effective compression of sequence data, allowing to fit larger datasets in R,
-
compatibility with most of
tidyverseuniverse, especiallydplyrandvctrspackages, making analyses tidier.
Try our quick start vignette or our exhaustive documentation.
The easiest way to install tidysq package is to download its latest
version from CRAN repository:
install.packages("tidysq")Alternatively, it is possible to download the development version directly from GitHub repository:
# install.packages("devtools") devtools::install_github("BioGenies/tidysq")
library(tidysq)×ばつ 2 #> sq name #> <ami_bsc> <chr> #> 1 PGGGKVQIV <13> AMY1|K19|T-Protein (Tau) #> 2 NLKHQPGGG <43> AMY9|K19Gluc41|T-Protein (Tau) #> 3 NLKHQPGGG <19> AMY14|K19Gluc782|T-Protein (Tau) #> 4 GKVQIVYK <8> AMY17|PHF8|T-Protein (Tau) #> 5 VQIVYK <6> AMY18|PHF6|T-Protein (Tau) #> 6 DAEFRHDSG <40> AMY22|Whole|Amyloid beta A4 peptide #> 7 VPHQKLVFF <15> AMY23|HABP1|Amyloid beta A4 peptide #> 8 VHPQKLVFF <15> AMY24|HABP2|Amyloid beta A4 peptide #> 9 VHHPKLVFF <15> AMY25|HABP3|Amyloid beta A4 peptide #> 10 VHHQPLVFF <15> AMY26|HABP4|Amyloid beta A4 peptide #> # i 411 more rows sq_ami <- sqibble$sq sq_ami #> basic amino acid sequences list: #> [1] PGGGKVQIVYKPV <13> #> [2] NLKHQPGGGKVQIVYKPVDLSKVTSKCGSLGNIHHKPGGGQVE <43> #> [3] NLKHQPGGGKVQIVYKEVD <19> #> [4] GKVQIVYK <8> #> [5] VQIVYK <6> #> [6] DAEFRHDSGYEVHHQKLVFFAEDVGSNKGAIIGLMVGGVV <40> #> [7] VPHQKLVFFAEDVGS <15> #> [8] VHPQKLVFFAEDVGS <15> #> [9] VHHPKLVFFAEDVGS <15> #> [10] VHHQPLVFFAEDVGS <15> #> printed 10 out of 421 # Subsequences can be extracted with bite() bite(sq_ami, 5:10) #> Warning in CPP_bite(x, indices, NA_letter, on_warning): some sequences are #> subsetted with index bigger than length - NA introduced #> basic amino acid sequences list: #> [1] KVQIVY <6> #> [2] QPGGGK <6> #> [3] QPGGGK <6> #> [4] IVYK!! <6> #> [5] YK!!!! <6> #> [6] RHDSGY <6> #> [7] KLVFFA <6> #> [8] KLVFFA <6> #> [9] KLVFFA <6> #> [10] PLVFFA <6> #> printed 10 out of 421 # There are also more traditional functions reverse(sq_ami) #> basic amino acid sequences list: #> [1] VPKYVIQVKGGGP <13> #> [2] EVQGGGPKHHINGLSGCKSTVKSLDVPKYVIQVKGGGPQHKLN <43> #> [3] DVEKYVIQVKGGGPQHKLN <19> #> [4] KYVIQVKG <8> #> [5] KYVIQV <6> #> [6] VVGGVMLGIIAGKNSGVDEAFFVLKQHHVEYGSDHRFEAD <40> #> [7] SGVDEAFFVLKQHPV <15> #> [8] SGVDEAFFVLKQPHV <15> #> [9] SGVDEAFFVLKPHHV <15> #> [10] SGVDEAFFVLPQHHV <15> #> printed 10 out of 421 # find_motifs() returns a whole tibble of useful informations find_motifs(sqibble, "^VHX") #> # A tibble: 9 ×ばつ 5 #> names found sought start end #> <chr> <ami_bsc> <chr> <int> <int> #> 1 AMY24|HABP2|Amyloid beta A4 peptide VHP <3> ^VHX 1 3 #> 2 AMY25|HABP3|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 3 AMY26|HABP4|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 4 AMY34|HABP12|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 5 AMY35|HABP13|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 6 AMY36|HABP14|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 7 AMY38|HABP16|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 8 AMY43|AB5|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 9 AMY195|86-95|Prion protein (human) VHD <3> ^VHX 1 3">
file <- system.file("examples", "example_aa.fasta", package = "tidysq") sqibble <- read_fasta(file) sqibble #> # A tibble: 421 ×ばつ 2 #> sq name #> <ami_bsc> <chr> #> 1 PGGGKVQIV <13> AMY1|K19|T-Protein (Tau) #> 2 NLKHQPGGG <43> AMY9|K19Gluc41|T-Protein (Tau) #> 3 NLKHQPGGG <19> AMY14|K19Gluc782|T-Protein (Tau) #> 4 GKVQIVYK <8> AMY17|PHF8|T-Protein (Tau) #> 5 VQIVYK <6> AMY18|PHF6|T-Protein (Tau) #> 6 DAEFRHDSG <40> AMY22|Whole|Amyloid beta A4 peptide #> 7 VPHQKLVFF <15> AMY23|HABP1|Amyloid beta A4 peptide #> 8 VHPQKLVFF <15> AMY24|HABP2|Amyloid beta A4 peptide #> 9 VHHPKLVFF <15> AMY25|HABP3|Amyloid beta A4 peptide #> 10 VHHQPLVFF <15> AMY26|HABP4|Amyloid beta A4 peptide #> # i 411 more rows sq_ami <- sqibble$sq sq_ami #> basic amino acid sequences list: #> [1] PGGGKVQIVYKPV <13> #> [2] NLKHQPGGGKVQIVYKPVDLSKVTSKCGSLGNIHHKPGGGQVE <43> #> [3] NLKHQPGGGKVQIVYKEVD <19> #> [4] GKVQIVYK <8> #> [5] VQIVYK <6> #> [6] DAEFRHDSGYEVHHQKLVFFAEDVGSNKGAIIGLMVGGVV <40> #> [7] VPHQKLVFFAEDVGS <15> #> [8] VHPQKLVFFAEDVGS <15> #> [9] VHHPKLVFFAEDVGS <15> #> [10] VHHQPLVFFAEDVGS <15> #> printed 10 out of 421 # Subsequences can be extracted with bite() bite(sq_ami, 5:10) #> Warning in CPP_bite(x, indices, NA_letter, on_warning): some sequences are #> subsetted with index bigger than length - NA introduced #> basic amino acid sequences list: #> [1] KVQIVY <6> #> [2] QPGGGK <6> #> [3] QPGGGK <6> #> [4] IVYK!! <6> #> [5] YK!!!! <6> #> [6] RHDSGY <6> #> [7] KLVFFA <6> #> [8] KLVFFA <6> #> [9] KLVFFA <6> #> [10] PLVFFA <6> #> printed 10 out of 421 # There are also more traditional functions reverse(sq_ami) #> basic amino acid sequences list: #> [1] VPKYVIQVKGGGP <13> #> [2] EVQGGGPKHHINGLSGCKSTVKSLDVPKYVIQVKGGGPQHKLN <43> #> [3] DVEKYVIQVKGGGPQHKLN <19> #> [4] KYVIQVKG <8> #> [5] KYVIQV <6> #> [6] VVGGVMLGIIAGKNSGVDEAFFVLKQHHVEYGSDHRFEAD <40> #> [7] SGVDEAFFVLKQHPV <15> #> [8] SGVDEAFFVLKQPHV <15> #> [9] SGVDEAFFVLKPHHV <15> #> [10] SGVDEAFFVLPQHHV <15> #> printed 10 out of 421 # find_motifs() returns a whole tibble of useful informations find_motifs(sqibble, "^VHX") #> # A tibble: 9 ×ばつ 5 #> names found sought start end #> <chr> <ami_bsc> <chr> <int> <int> #> 1 AMY24|HABP2|Amyloid beta A4 peptide VHP <3> ^VHX 1 3 #> 2 AMY25|HABP3|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 3 AMY26|HABP4|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 4 AMY34|HABP12|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 5 AMY35|HABP13|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 6 AMY36|HABP14|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 7 AMY38|HABP16|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 8 AMY43|AB5|Amyloid beta A4 peptide VHH <3> ^VHX 1 3 #> 9 AMY195|86-95|Prion protein (human) VHD <3> ^VHX 1 3
An example of dplyr integration:
×ばつ 3 #> sq name length #> <ami_bsc> <chr> <dbl> #> 1 DAEFRHDSG <40> AMY22|Whole|Amyloid beta A4 peptide 40 #> 2 VPHQKLVFF <15> AMY23|HABP1|Amyloid beta A4 peptide 15 #> 3 VHPQKLVFF <15> AMY24|HABP2|Amyloid beta A4 peptide 15 #> 4 VHHPKLVFF <15> AMY25|HABP3|Amyloid beta A4 peptide 15 #> 5 VHHQPLVFF <15> AMY26|HABP4|Amyloid beta A4 peptide 15 #> 6 KKLVFFPED <9> AMY32|HABP10|Amyloid beta A4 peptide 9 #> 7 VHHQEKLVF <16> AMY34|HABP12|Amyloid beta A4 peptide 16 #> 8 VHHQEKLVF <16> AMY35|HABP13|Amyloid beta A4 peptide 16 #> 9 VHHQEKLVF <16> AMY36|HABP14|Amyloid beta A4 peptide 16 #> 10 KKLVFFAED <9> AMY37|HABP15|Amyloid beta A4 peptide 9 #> # i 14 more rows">
library(dplyr) # tidysq integrates well with dplyr verbs sqibble %>% filter(sq %has% "VFF") %>% mutate(length = get_sq_lengths(sq)) #> # A tibble: 24 ×ばつ 3 #> sq name length #> <ami_bsc> <chr> <dbl> #> 1 DAEFRHDSG <40> AMY22|Whole|Amyloid beta A4 peptide 40 #> 2 VPHQKLVFF <15> AMY23|HABP1|Amyloid beta A4 peptide 15 #> 3 VHPQKLVFF <15> AMY24|HABP2|Amyloid beta A4 peptide 15 #> 4 VHHPKLVFF <15> AMY25|HABP3|Amyloid beta A4 peptide 15 #> 5 VHHQPLVFF <15> AMY26|HABP4|Amyloid beta A4 peptide 15 #> 6 KKLVFFPED <9> AMY32|HABP10|Amyloid beta A4 peptide 9 #> 7 VHHQEKLVF <16> AMY34|HABP12|Amyloid beta A4 peptide 16 #> 8 VHHQEKLVF <16> AMY35|HABP13|Amyloid beta A4 peptide 16 #> 9 VHHQEKLVF <16> AMY36|HABP14|Amyloid beta A4 peptide 16 #> 10 KKLVFFAED <9> AMY37|HABP15|Amyloid beta A4 peptide 9 #> # i 14 more rows
For citation type:
citation("tidysq")or use:
Michal Burdukiewicz, Dominik Rafacz, Laura Bakala, Jadwiga Slowik, Weronika Puchala, Filip Pietluch, Katarzyna Sidorczuk, Stefan Roediger and Leon Eyrich Jessen (2021). tidysq: Tidy Processing and Analysis of Biological Sequences. R package version 1.1.3.