miplicorn establishes a unified analysis framework in R for molecular inversion probe (MIP) and amplicon-targeted sequencing analysis after micro haplotyping or variant calling. It provides tools for parsing large variant files, filtering and manipulating the data, and basic analyses and visualization.
You may install the package from
Github using devtools.
# Install most recent released version
devtools::install_github("bailey-lab/[email protected]")# Install development version
devtools::install_github("bailey-lab/miplicorn")See vignette("miplicorn") for a more extensive introduction and a
demonstration of several features of the package.
library(miplicorn)
ref_file <- miplicorn_example("reference_AA_table.csv")
alt_file <- miplicorn_example("alternate_AA_table.csv")
cov_file <- miplicorn_example("coverage_AA_table.csv")
data <- read_tbl_ref_alt_cov(ref_file, alt_file, cov_file, gene == "atp6" | gene == "crt")
data
#> # A ref alt cov table: 832 × 10
#> sample gene_id gene mutat…¹ exoni…² aa_ch…³ targe…⁴ ref_u…⁵ alt_u…⁶ cover…⁷
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 D10-JJJ… PF3D7_… atp6 atp6-A… missen… Ala623… Yes 608 0 608
#> 2 D10-JJJ… PF3D7_… atp6 atp6-A… missen… Ala623… Yes 20 0 20
#> 3 D10-JJJ… PF3D7_… atp6 atp6-A… missen… Ala623… Yes 158 0 158
#> 4 D10-JJJ… PF3D7_… atp6 atp6-A… missen… Ala623… Yes 2 0 2
#> 5 D10-JJJ… PF3D7_… atp6 atp6-A… missen… Ala623… Yes 1 0 1
#> # … with 827 more rows, and abbreviated variable names ¹mutation_name,
#> # ²exonic_func, ³aa_change, ⁴targeted, ⁵ref_umi_count, ⁶alt_umi_count,
#> # ⁷coverage
plot_coverage(data, mutation_name)
prev <- mutation_prevalence(data, threshold = 5)
prev
#> # A tibble: 16 × 4
#> mutation_name n_total n_mutant prevalence
#> <chr> <int> <int> <dbl>
#> 1 atp6-Ala623Glu 36 0 0
#> 2 atp6-Glu431Lys 39 0 0
#> 3 atp6-Gly639Asp 26 19 0.731
#> 4 atp6-Ser466Asn 15 9 0.6
#> 5 atp6-Ser769Asn 17 0 0
#> # … with 11 more rows
plot(prev)