In HIVDiversity/MotifBinner2: Processes NGS Primer ID Datasets

opts_chunk$set(echo=FALSE)
opts_chunk$set(warning=FALSE)
opts_chunk$set(fig.pos = 'H')

library(MotifBinner2)

if (!exists('result'))
{
  result <- all_results[[grep('buildConsensus', names(all_results))[1]]]
}
if (class(result) != 'buildConsensus')
{
  result <- all_results[[grep('buildConsensus', names(all_results))[1]]]
}

r result$config$op_full_name

Builds consensuses from aligned bins. Gaps still need to be removed - they result from insertions in the reads in the bin and can be removed.

A letter was called as an N if either:

1) The score of the highest scoring letter was not at least 5% higher than the score of the second highest scoring letter,

2) The score of the highest scoring letter minus the scores of all the other letters did not exceed 35.

In total r length(result$seq_dat) consensus sequences were produced.

Of those sequences, r sum(result$metrics$per_read_metrics$n_Ns > 0) contained at least one N and r sum(result$metrics$per_read_metrics$n_gaps > 0) contained at least one gap.

n_Ns <- sort(result$metrics$per_read_metrics$n_Ns, dec = T)
n_gaps <- sort(result$metrics$per_read_metrics$n_gaps, dec = T)

stats_tab <- rbind(
data.frame(metric = c('Total sequences with zero', 'Total sequences with one', 'Total sequences with two', 
                      'Total sequences with three', 'Total sequences with four', 'Total sequences with five or more'),
           Ns     = as.character(c(sum(n_Ns == 0),              sum(n_Ns == 1),             sum(n_Ns == 2),   
                      sum(n_Ns == 3),               sum(n_Ns == 4), sum(n_Ns >= 5))),
           Gaps   = as.character(c(sum(n_gaps == 0),            sum(n_gaps == 1),           sum(n_gaps == 2), 
                      sum(n_gaps == 3),             sum(n_gaps == 4), sum(n_gaps >= 5))))
,
data.frame(metric = c('', 'Highest number in single sequence', '2nd Highest number in single sequence', '3rd Highest number in single sequence'),
           Ns     = c('', n_Ns[1],                             n_Ns[2],                                 n_Ns[3]),
           Gaps   = c('', n_gaps[1],                           n_gaps[2],                               n_gaps[3]))
)
cat('\n\nTable: Stats about the number of sequences with gaps and Ns as well as the sequences with highest numbers of gaps and Ns.\n\n')
print(format_table(stats_tab))

kable_summary(result$summary)

timingTable(result)

cat('\n\n---\n\n')

HIVDiversity/MotifBinner2 documentation built on May 6, 2019, 6:44 p.m.