Fastq

The alakazam package includes a set of functions to inspect the sequencing quality.

Example data

Load example data:

library(alakazam)
library(dplyr)
library(airr)

db <- read_rearrangement(system.file("extdata", "example_quality.tsv", package="alakazam"))
fastq_file <- system.file("extdata", "example_quality.fastq", package="alakazam")

Load quality scores

This method allows to add the quality scores to the repertoire data.frame as strings.

original_cols <- colnames(db)
db <- readFastqDb(db, fastq_file, style="both", quality_sequence=TRUE)
new_cols <- setdiff(colnames(db), original_cols)
db[,new_cols] %>% head()
## # A tibble: 1 x 4
##   quality_num        quality        quality_alignment_num  quality_alignment    
##   <chr>              <chr>          <chr>                  <chr>                
## 1 90,90,90,90,90,90… {{{{{{{{{{{{{… 90,90,90,90,90,90,90,… {{{{{{{{{{{{{{{{{{{{…

The function readFastq takes as main inputs a repertoire data.frame (db) and a path to the corresponding .fastq file (fastq_file). The sequencing quality scores will be merged into the data.frame by sequence_id. The newly added columns are: quality_num, quality, quality_alignment_num, quality_alignment. The other fields, contain the ASCII quality scores in the form of a vector, where values are comma separated, and - or . positions have value " " (blank).

After loading the quality scores with readFastqDb, getPositionQuality can be used to generate a data.frame of sequencing quality values per position.

quality <- getPositionQuality(db, sequence_id="sequence_id", 
                              sequence="sequence_alignment",
                              quality_num="quality_alignment_num")
## Warning in FUN(X[[i]], ...): NAs introduced by coercion
head(quality)
##   position quality_alignment_num       sequence_id nt
## 1        1                    90 CGCTTTTCGGATTGGAA  C
## 2        2                    90 CGCTTTTCGGATTGGAA  A
## 3        3                    90 CGCTTTTCGGATTGGAA  G
## 4        4                    90 CGCTTTTCGGATTGGAA  C
## 5        5                    90 CGCTTTTCGGATTGGAA  T
## 6        6                    90 CGCTTTTCGGATTGGAA  G
min_pos <- min(quality$position)
max_pos <- max(quality$position)

ggplot(quality, aes(x=position,
                    y=quality_alignment_num,
                    color=nt)) +
  geom_point() +
  coord_cartesian(xlim=c(110,120)) +
  xlab("IMGT position") +
  ylab("Sequencing quality") +
  scale_fill_gradient(low = "light blue",  high = "dark red") +
  scale_x_continuous(breaks=c(min_pos:max_pos)) +
  alakazam::baseTheme()
## Warning: Removed 27 rows containing missing values (geom_point).

Sequence quality per IMGT position for one sequence.

You can add use the quality data.frame to complement analysis performed with other tools from the Immcantation framework. For example, you could inspect the sequencing quality of novel polymorphisms identified with tigger, or the sequencing quality in mutated/unmutated regions.

Mask low quality positions

Use maskPositionsByQuality to mask low quality positions. Positions with a sequencing quality < min_quality will be replaced with an ‘N’. A message will show the number of sequences in db that had at least one position masked.

db <- maskPositionsByQuality(db, min_quality=70,
                             sequence="sequence_alignment",
                             quality="quality_alignment_num")
## Number of masked sequences: 1