R - Create new column based on substring from another column with conditions-CodePudding

I am working with microbial data where every taxa level (i.e. Kingdom, Phylum, Class, Order, Family, Genus and Species) are separated by ;.

Example input data:

input_data <- data.frame(taxon = c("k__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Lactobacillus;s__crispatus", "k__Bacteria;p__Firmicutes;c__Tissierellia;o__Tissierellales;f__Peptoniphilaceae;g__Anaerococcus;s__", "k__Bacteria;p__Proteobacteria;c__Betap__Proteobacteria;o__Burkholderiales;f__Comamonadaceae", "k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae", "k__Bacteria;p__Proteobacteria;c__Alphap__Proteobacteria;o__Rhizobiales;f__Bradyrhizobiaceae;g__Bosea;s__massiliensis", "k__Bacteria;p__Proteobacteria;c__Gammap__Proteobacteria;o__Pseudomonadales;f__Moraxellaceae;g__Acinetobacter;s__baumannii", "k__Bacteria;p__Proteobacteria;c__Betap__Proteobacteria;o__Nitrosomonadales;f__Methylophilaceae"))

print(input_data)

The input data will look like this:

taxon
1 k__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Lactobacillus;s__crispatus
2 k__Bacteria;p__Firmicutes;c__Tissierellia;o__Tissierellales;f__Peptoniphilaceae;g__Anaerococcus;s__
3 k__Bacteria;p__Proteobacteria;c__Betap__Proteobacteria;o__Burkholderiales;f__Comamonadaceae
4 k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae
5 k__Bacteria;p__Proteobacteria;c__Alphap__Proteobacteria;o__Rhizobiales;f__Bradyrhizobiaceae;g__Bosea;s__massiliensis
6 k__Bacteria;p__Proteobacteria;c__Gammap__Proteobacteria;o__Pseudomonadales;f__Moraxellaceae;g__Acinetobacter;s__baumannii
7 k__Bacteria;p__Proteobacteria;c__Betap__Proteobacteria;o__Nitrosomonadales;f__Methylophilaceae

I would like to create a new column taxon_main that is based on the highest available taxa level that looks like the example output data below.

Example output data:

output_data <- data.frame(
  taxon = c("k__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Lactobacillus;s__crispatus",
            "k__Bacteria;p__Firmicutes;c__Tissierellia;o__Tissierellales;f__Peptoniphilaceae;g__Anaerococcus;s__", 
            "k__Bacteria;p__Proteobacteria;c__Betap__Proteobacteria;o__Burkholderiales;f__Comamonadaceae", "k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae", "k__Bacteria;p__Proteobacteria;c__Alphap__Proteobacteria;o__Rhizobiales;f__Bradyrhizobiaceae;g__Bosea;s__massiliensis",
            "k__Bacteria;p__Proteobacteria;c__Gammap__Proteobacteria;o__Pseudomonadales;f__Moraxellaceae;g__Acinetobacter;s__baumannii",
            "k__Bacteria;p__Proteobacteria;c__Betap__Proteobacteria;o__Nitrosomonadales;f__Methylophilaceae"),
  taxon_main = c("Lactobacillus_crispatus", "g_Anaerococcus", "f_Comamonadaceae",
                 "f_Lachnospiraceae", "Bosea_massiliensis", "Acinetobacter_baumannii",
                 "f_Methylophilaceae"))

print(output_data)

The output data will have a new column taxon_main that should look like this:

               taxon_main
1 Lactobacillus_crispatus
2          g_Anaerococcus
3        f_Comamonadaceae
4       f_Lachnospiraceae
5      Bosea_massiliensis
6 Acinetobacter_baumannii
7      f_Methylophilaceae

Since I cannot just create the new column based on extracting the taxa after the last separator using dplyr::mutate(taxon_main = str_extract(taxon, "[^;] $")) because I need to new column to be based on following criteria:

If genus g__* and species s__* are available, then concatenate to become genus_species.
If genus and/or species not available, then use next highest level - e.g. o_Order.
Only keep a single underscore _ as a separator for the new column rather than double underscores __.

The functions I have tried using are separate(taxon, sep = ";"), mutate(Species = na_if(Species, "s__") and paste(input_data$Genus, input_data$Species, sep = "_"). However, I can't seem to make this applicable to all conditions required to get the desired output.

If anyone has any ideas of how best to wrangle the data to become what I am hoping to do, that would be great. Thank you!

CodePudding user response：

There is probably a more efficient way to do this, but we could do a series of ifelse statements using case_when from tidyverse. First, I remove any rows that just end with ;s__. Then, in the series of statements, I check to if a given taxonomic level is present, then if so, then return that in the desired format. Then, that is repeated across all taxonomic levels.

library(tidyverse)

output <- input_data %>%
  mutate(taxon = trimws(taxon, whitespace = ";s__")) %>%
  mutate(taxon_main = case_when(str_detect(taxon, "s__") ~ trimws(str_replace_all(str_extract(taxon, "(?<=g__).*"), ";s_", ""), whitespace = '_'),
                                !str_detect(taxon, "s__") & str_detect(taxon, "g__")~ str_replace_all(str_extract(taxon, "g__.*"), "__", "_"),
                                !str_detect(taxon, "g__") & str_detect(taxon, "f__") ~ str_replace_all(str_extract(taxon, "f__.*"), "__", "_"),
                                !str_detect(taxon, "f__") & str_detect(taxon, "o__")~ str_replace_all(str_extract(taxon, "o__.*"), "__", "_"),
                                !str_detect(taxon, "o__") & str_detect(taxon, "c__")~ str_replace_all(str_extract(taxon, "c__.*"), "__", "_"),
                                !str_detect(taxon, "c__") & str_detect(taxon, "p__")~ str_replace_all(str_extract(taxon, "p__.*"), "__", "_"),
                                !str_detect(taxon, "p__") & str_detect(taxon, "k__")~ str_replace_all(str_extract(taxon, "k__.*"), "__", "_"),
                                TRUE ~ NA_character_))

Output

output %>% select(taxon_main)

               taxon_main
1 Lactobacillus_crispatus
2          g_Anaerococcus
3        f_Comamonadaceae
4       f_Lachnospiraceae
5      Bosea_massiliensis
6 Acinetobacter_baumannii
7      f_Methylophilaceae

Or you could also use separate first, which will make the code less reliant on using a lot of stringr. We can clean up before using separate, such as only having one underscore and remove extra s__. Then, we can go through the ifelse statements, and then we can bind back to the original taxon column and drop all the other columns, except for taxon_main.

input_data %>%
  mutate(taxon = trimws(taxon, whitespace = ";s__"),
         taxon = str_replace_all(taxon, ";s__", ";"),
         taxon = str_replace_all(taxon, "__", "_")) %>%
  separate(taxon, sep = ";", into = c("Kingdom", "Phylum", "Class", "Order", "Family", "Genus", "Species")) %>%
  mutate(taxon_main = case_when(!is.na(Species) ~ paste(str_extract(Genus, "(?<=g_).*"), Species, sep = "_"),
                                is.na(Species) & !is.na(Genus) ~ Genus,
                                is.na(Genus) & !is.na(Family) ~ Family,
                                is.na(Family) & !is.na(Order) ~ Order,
                                is.na(Order) & !is.na(Class) ~ Class,
                                is.na(Class) & !is.na(Phylum) ~ Phylum,
                                is.na(Phylum) & !is.na(Kingdom) ~ Kingdom
                                )) %>% 
  bind_cols(input_data,.) %>% 
  select(taxon_main, taxon)

Output

               taxon_main                                                                                                                     taxon
1 Lactobacillus_crispatus                 k__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Lactobacillus;s__crispatus
2          g_Anaerococcus                       k__Bacteria;p__Firmicutes;c__Tissierellia;o__Tissierellales;f__Peptoniphilaceae;g__Anaerococcus;s__
3        f_Comamonadaceae                               k__Bacteria;p__Proteobacteria;c__Betap__Proteobacteria;o__Burkholderiales;f__Comamonadaceae
4       f_Lachnospiraceae                                               k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae
5      Bosea_massiliensis      k__Bacteria;p__Proteobacteria;c__Alphap__Proteobacteria;o__Rhizobiales;f__Bradyrhizobiaceae;g__Bosea;s__massiliensis
6 Acinetobacter_baumannii k__Bacteria;p__Proteobacteria;c__Gammap__Proteobacteria;o__Pseudomonadales;f__Moraxellaceae;g__Acinetobacter;s__baumannii
7      f_Methylophilaceae                            k__Bacteria;p__Proteobacteria;c__Betap__Proteobacteria;o__Nitrosomonadales;f__Methylophilaceae