metacoder (version 0.3.7)

primersearch: Use EMBOSS primersearch for in silico PCR

Description

A pair of primers are aligned against a set of sequences. A taxmap object with two tables is returned: a table with information for each predicted amplicon, quality of match, and predicted amplicons, and a table with per-taxon amplification statistics. Requires the EMBOSS tool kit (https://emboss.sourceforge.net/) to be installed.

Usage

primersearch(obj, seqs, forward, reverse, mismatch = 5, clone = TRUE)

Value

A copy of the input taxmap object with two tables added. One table contains amplicon information with one row per predicted amplicon with the following info:

           (f_primer)
   5' AAGTACCTTAACGGAATTATAG ->        (r_primer)
                               <- TAAGCAAAGCATCCACCTCG 5'
5' ...AAGTACCTTAACGGAATTATAG......ATTCGTTTCGTAGGTGGAGC... 3'
      ^                    ^      ^                  ^
   f_start              f_end   r_rtart             r_end
     
      |--------------------||----||------------------|
             f_match       amplicon       r_match  
      |----------------------------------------------|
                           product
                           

taxon_id:

The taxon IDs for the sequence.

seq_index:

The index of the input sequence.

f_primer:

The sequence of the forward primer.

r_primer:

The sequence of the reverse primer.

f_mismatch:

The number of mismatches on the forward primer.

r_mismatch:

The number of mismatches on the reverse primer.

f_start:

The start location of the forward primer.

f_end:

The end location of the forward primer.

r_start:

The start location of the reverse primer.

r_end:

The end location of the reverse primer.

f_match:

The sequence matched by the forward primer.

r_match:

The sequence matched by the reverse primer.

amplicon:

The sequence amplified by the primers, not including the primers.

product:

The sequence amplified by the primers including the primers. This simulates a real PCR product.

The other table contains per-taxon information about the PCR, with one row per taxon. It has the following columns:

taxon_ids:

Taxon IDs.

query_count:

The number of sequences used as input.

seq_count:

The number of sequences that had at least one amplicon.

amp_count:

The number of amplicons. Might be more than one per sequence.

amplified:

If at least one sequence of that taxon had at least one amplicon.

multiple:

If at least one sequences had at least two amplicons.

prop_amplified:

The proportion of sequences with at least one amplicon.

med_amp_len:

The median amplicon length.

min_amp_len:

The minimum amplicon length.

max_amp_len:

The maximum amplicon length.

med_prod_len:

The median product length.

min_prod_len:

The minimum product length.

max_prod_len:

The maximum product length.

Arguments

obj

A taxmap object.

seqs

The sequences to do in silico PCR on. This can be any variable in obj$data listed in all_names(obj) or an external variable. If an external variable (i.e. not in obj$data), it must be named by taxon IDs or have the same length as the number of taxa in obj. Currently, only character vectors are accepted.

forward

(character of length 1) The forward primer sequence

reverse

(character of length 1) The reverse primer sequence

mismatch

An integer vector of length 1. The percentage of mismatches allowed.

clone

If TRUE, make a copy of the input object and add on the results (like most R functions). If FALSE, the input will be changed without saving the result, which uses less RAM.

Installing EMBOSS

The command-line tool "primersearch" from the EMBOSS tool kit is needed to use this function. How you install EMBOSS will depend on your operating system:

Linux:

Open up a terminal and type:

sudo apt-get install emboss

Mac OSX:

The easiest way to install EMBOSS on OSX is to use homebrew. After installing homebrew, open up a terminal and type:

brew install homebrew/science/emboss

Windows:

There is an installer for Windows here:

ftp://emboss.open-bio.org/pub/EMBOSS/windows/mEMBOSS-6.5.0.0-setup.exe

Details

It can be confusing how the primer sequence relates to the binding sites on a reference database sequence. A simplified diagram can help. For example, if the top strand below (5' -> 3') is the database sequence, the forward primer has the same sequence as the target region, since it will bind to the other strand (3' -> 5') during PCR and extend on the 3' end. However, the reverse primer must bind to the database strand, so it will have to be the complement of the reference sequence. It also has to be reversed to make it in the standard 5' -> 3' orientation. Therefore, the reverse primer must be the reverse complement of its binding site on the reference sequence.

Primer 1: 5' AAGTACCTTAACGGAATTATAG 3'
Primer 2: 5' GCTCCACCTACGAAACGAAT   3'
 
                               <- TAAGCAAAGCATCCACCTCG 5'
5' ...AAGTACCTTAACGGAATTATAG......ATTCGTTTCGTAGGTGGAGC... 3'
3' ...TTCATGGAATTGCCTTAATATC......TAAGCAAAGCATCCACCTCG... 5'
   5' AAGTACCTTAACGGAATTATAG ->

However, a database might have either the top or the bottom strand as a reference sequence. Since one implies the sequence of the other, either is valid, but this is another source of confusion. If we take the diagram above and rotate it 180 degrees, it would mean the same thing, but which primer we would want to call "forward" and which we would want to call "reverse" would change. Databases of a single locus (e.g. Greengenes) will likely have a convention for which strand will be present, so relative to this convention, there is a distinct "forward" and "reverse". However, computers dont know about this convention, so the "forward" primer is whichever primer has the same sequence as its binding region in the database (as opposed to the reverse complement). For this reason, primersearch will redefine which primer is "forward" and which is "reverse" based on how it binds the reference sequence. See the example code in primersearch_raw for a demonstration of this.

Examples

if (FALSE) {
# Get example FASTA file
fasta_path <- system.file(file.path("extdata", "silva_subset.fa"),
                          package = "metacoder")

# Parse the FASTA file as a taxmap object
obj <- parse_silva_fasta(file = fasta_path)

# Simulate PCR with primersearch
# Have to replace Us with Ts in sequences since primersearch
#   does not understand Us.
obj <- primersearch(obj,
                    gsub(silva_seq, pattern = "U", replace = "T"), 
                    forward = c("U519F" = "CAGYMGCCRCGGKAAHACC"),
                    reverse = c("Arch806R" = "GGACTACNSGGGTMTCTAAT"),
                    mismatch = 10)
                           
# Plot what did not ampilify                          
obj %>%
  filter_taxa(prop_amplified < 1) %>%
  heat_tree(node_label = taxon_names, 
            node_color = prop_amplified, 
            node_color_range = c("grey", "red", "purple", "green"),
            node_color_trans = "linear",
            node_color_axis_label = "Proportion amplified",
            node_size = n_obs,
            node_size_axis_label = "Number of sequences",
            layout = "da", 
            initial_layout = "re")
}