library(fastqcr)
library(dplyr)
# Read all modules
qc <- qc_read(qc.path)
# Elements contained in the qc object
names(qc)
## [1] "summary" "basic_statistics" "per_base_sequence_quality" "per_tile_sequence_quality"
## [5] "per_sequence_quality_scores" "per_base_sequence_content" "per_sequence_gc_content" "per_base_n_content"
## [9] "sequence_length_distribution" "sequence_duplication_levels" "overrepresented_sequences" "adapter_content"
## [13] "kmer_content" "total_deduplicated_percentage"
Summary shows a summary of the modules which were tested, and the status of the test resuls:
Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look normal.
qc_plot(qc, "summary")
Basic statistics shows basic data metrics such as:
qc_plot(qc, "Basic statistics")
qc_plot(qc, "Per base sequence quality")
qc_plot(qc, "Per sequence quality scores")
qc_plot(qc, "Per base sequence content")
qc_plot(qc, "Per sequence GC content")
qc_plot(qc, "Per base N content")
qc_plot(qc, "Sequence length distribution")
qc_plot(qc, "Sequence duplication levels")
qc_plot(qc, "Overrepresented sequences")
qc_plot(qc, "Adapter content")
qc_plot(qc, "Kmer content")