biogenies / tidysq

tidy processing of biological sequences in R

tidysq

Overview

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 tidyverse universe, especially dplyr and vctrs packages, making analyses tidier.

Getting started

Try our quick start vignette or our exhaustive documentation.

Installation

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")

Example usage

library(tidysq)

file <- system.file("examples", "example_aa.fasta", package = "tidysq")
sqibble <- read_fasta(file)
sqibble
#> # A tibble: 421 × 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
#> # … with 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 × 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:

library(dplyr)
# tidysq integrates well with dplyr verbs
sqibble %>%
  filter(sq %has% "VFF") %>%
  mutate(length = get_sq_lengths(sq))
#> # A tibble: 24 × 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
#> # … with 14 more rows

Citation

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.