Combining R tables to create a metabarlist object.
metabarlist_generator(reads, motus, pcrs, samples)MOTU abundance table. Rows and rownames of the table should correspond to PCRs and their names respectively. Columns and colnames should correspond to MOTUs and their names. Rownames in this table should correspond to PCR names respectively.
MOTU characteristics table (e.g. taxonomy, sequence, etc.). Rows and rownames of the table should correspond to MOTUs and their names respectively, and the columns to their characteristics. Mandatory fields: `sequence`, i.e. the sequence representative of the MOTU.
PCR characteristics table (e.g. tags, primers, plate wells, etc.). Rows and rownames of the table should correspond to PCRs and their names respectively, and the columns to their characteristics. Mandatory fields: (i) `sample_id`, i.e. the name of each biological sample. (ii) `type`, i.e. the type of PCR; can be `sample` or `control`. (iii) `control_type`, i.e. the type of control if applicable. Should be either: `NA` for samples, `extraction` for extraction negative controls, `pcr` for PCR negative controls, `sequencing` for sequencing negative controls (e.g. unused tag combinations), or `positive` for positive controls.
Sample characteristics table. Rows and rownames of the table should correspond to biological samples and their names respectively, and the columns to their environnemental characteristics.
a metabarlist object
This function formats R tables to create a metabarlist object. The four objects required are incorporated into a list of class metabarlist. Congruencies between all tables are tested internally with the check_metabarlist function.
# Create fake data
## MOTUs abundance table
reads <- matrix(sample(1:1000, 200, replace = TRUE), nrow = 10, ncol = 20)
rownames(reads) <- paste(c(rep(c("A", "B", "C"), each = 2), "ex", "pcr", "seq", "pos"),
c(rep(c("r1", "r2"), 3), rep(0, 4)),
sep = "_"
)
colnames(reads) <- sprintf("MOTU_%03d", 1:ncol(reads))
## MOTUs characteristics table
motus <- data.frame(
fake_taxon = sample(letters, ncol(reads), replace = TRUE),
sequence = sapply(
1:ncol(reads),
function(x) paste(sample(c("a", "t", "c", "g"), 20, TRUE), collapse = "")
),
row.names = colnames(reads), stringsAsFactors = FALSE
)
## PCR characteristics table
pcrs <- data.frame(
sample_id = sapply(strsplit(rownames(reads), "_"), "[[", 1),
type = c(rep("sample", 6), rep("control", 4)),
control_type = c(rep(NA, 6), "extraction", "pcr", "sequencing", "positive"),
fake_pcrplate = sample(c(1, 2), nrow(reads), replace = TRUE),
row.names = rownames(reads)
)
## Sample characteristics table
samples <- data.frame(
fake_latitude = 1:3, fake_longitude = 1:3,
row.names = unique(pcrs$sample_id[is.na(pcrs$control_type)])
)
## Generate the metabarlist object
test <- metabarlist_generator(reads = reads, motus = motus, pcrs = pcrs, samples = samples)
#> Warning: PCR plate design not properly provided: columns tag_fwd is missing in table `pcrs` of out!
#> PCR plate design not properly provided: columns tag_rev is missing in table `pcrs` of out!
#> PCR plate design not properly provided: columns primer_fwd is missing in table `pcrs` of out!
#> PCR plate design not properly provided: columns primer_rev is missing in table `pcrs` of out!
#> PCR plate design not properly provided: columns plate_no is missing in table `pcrs` of out!
#> PCR plate design not properly provided: columns plate_col is missing in table `pcrs` of out!
#> PCR plate design not properly provided: columns plate_row is missing in table `pcrs` of out!
## Warnings are returned because the PCR design (i.e. tags, primers, plate
# coordinates) is not defined in this example.