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## ----eval=TRUE, warning=FALSE, message=FALSE----------------------------------
# Import required packages
library(alakazam)
library(dplyr)
library(ggplot2)
library(shazam)
# Load and subset example data
data(ExampleDb, package="alakazam")
db <- subset(ExampleDb, c_call %in% c("IGHA", "IGHG") & sample_id == "+7d")
## ----eval=TRUE----------------------------------------------------------------
# Calculate R and S mutation counts
db_obs <- observedMutations(db, sequenceColumn="sequence_alignment",
germlineColumn="germline_alignment_d_mask",
regionDefinition=NULL,
frequency=FALSE,
nproc=1)
# Show new mutation count columns
db_obs %>%
select(sequence_id, starts_with("mu_count_")) %>%
head(n=4)
# Calculate R and S mutation frequencies
db_obs <- observedMutations(db_obs, sequenceColumn="sequence_alignment",
germlineColumn="germline_alignment_d_mask",
regionDefinition=NULL,
frequency=TRUE,
nproc=1)
# Show new mutation frequency columns
db_obs %>%
select(sequence_id, starts_with("mu_freq_")) %>%
head(n=4)
## ----eval=TRUE----------------------------------------------------------------
# Calculate combined R and S mutation frequencies
db_obs <- observedMutations(db, sequenceColumn="sequence_alignment",
germlineColumn="germline_alignment_d_mask",
regionDefinition=NULL,
frequency=TRUE,
combine=TRUE,
nproc=1)
# Show new mutation frequency columns
db_obs %>%
select(sequence_id, starts_with("mu_freq")) %>%
head(n=4)
## ----eval=TRUE, warning=FALSE-------------------------------------------------
g1 <- ggplot(db_obs, aes(x=c_call, y=mu_freq, fill=c_call)) +
geom_boxplot() +
labs(title = "Total mutations",
x = "Isotype", y = "Mutation frequency") +
scale_fill_manual(name="Isotype", values=IG_COLORS, limits=force) +
theme_bw()
plot(g1)
## ----eval=TRUE----------------------------------------------------------------
# Calculate R and S mutation counts for individual CDRs and FWRs
db_obs_v <- observedMutations(db, sequenceColumn="sequence_alignment",
germlineColumn="germline_alignment_d_mask",
regionDefinition=IMGT_V_BY_REGIONS,
frequency=FALSE,
nproc=1)
# Show new FWR mutation columns
db_obs_v %>%
select(sequence_id, starts_with("mu_count_fwr")) %>%
head(n=4)
# Calculate aggregate CDR and FWR V-segment R and S mutation frequencies
db_obs_v <- observedMutations(db_obs_v, sequenceColumn="sequence_alignment",
germlineColumn="germline_alignment_d_mask",
regionDefinition=IMGT_V,
frequency=TRUE,
nproc=1)
# Show new CDR and FWR mutation frequency columns
db_obs_v %>%
select(sequence_id, starts_with("mu_freq_")) %>%
head(n=4)
## ----eval=TRUE, warning=FALSE-------------------------------------------------
g2 <- ggplot(db_obs_v, aes(x=c_call, y=mu_freq_cdr_s, fill=c_call)) +
geom_boxplot() +
labs(title = "CDR silent mutations",
x = "Isotype", y = "Mutation frequency") +
scale_fill_manual(name="Isotype", values=IG_COLORS, limits=force) +
theme_bw()
g3 <- ggplot(db_obs_v, aes(x=c_call, y=mu_freq_cdr_r, fill=c_call)) +
geom_boxplot() +
labs(title = "CDR replacement mutations",
x = "Isotype", y = "Mutation frequency") +
scale_fill_manual(name="Isotype", values=IG_COLORS, limits=force) +
theme_bw()
alakazam::gridPlot(g2, g3, ncol=2)
## ----eval=TRUE----------------------------------------------------------------
# Calculate charge mutation frequency for the full sequence
db_obs_ch <- observedMutations(db, sequenceColumn="sequence_alignment",
germlineColumn="germline_alignment_d_mask",
regionDefinition=NULL,
mutationDefinition=CHARGE_MUTATIONS,
frequency=TRUE,
nproc=1)
# Show new charge mutation frequency columns
db_obs_ch %>%
select(sequence_id, starts_with("mu_freq_")) %>%
head(n=4)
## ----eval=TRUE, warning=FALSE-------------------------------------------------
g4 <- ggplot(db_obs_ch, aes(x=c_call, y=mu_freq_seq_r, fill=c_call)) +
geom_boxplot() +
labs(title="Charge replacement mutations",
x="Isotype", y="Mutation frequency") +
scale_fill_manual(name="Isotype", values=IG_COLORS, limits=force) +
theme_bw()
plot(g4)
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