shazam (version 1.2.0)

summarizeBaseline: Calculate BASELINe summary statistics

Description

summarizeBaseline calculates BASELINe statistics such as the mean selection strength (mean Sigma), the 95% confidence intervals and p-values for the presence of selection.

Usage

summarizeBaseline(baseline, returnType = c("baseline", "df"), nproc = 1)

Value

Either a modified Baseline object or data.frame containing the mean BASELINe selection strength, its 95% confidence intervals, and a p-value for the presence of selection.

Arguments

baseline

Baseline object returned by calcBaseline containing annotations and BASELINe posterior probability density functions (PDFs) for each sequence.

returnType

One of c("baseline", "df") defining whether to return a Baseline object ("baseline") with an updated stats slot or a data.frame ("df") of summary statistics.

nproc

number of cores to distribute the operation over. If nproc = 0 then the cluster has already been set and will not be reset.

Details

The returned p-value can be either positive or negative. Its magnitude (without the sign) should be interpreted as per normal. Its sign indicates the direction of the selection detected. A positive p-value indicates positive selection, whereas a negative p-value indicates negative selection.

References

1. Uduman M, et al. Detecting selection in immunoglobulin sequences. Nucleic Acids Res. 2011 39(Web Server issue):W499-504.

See Also

See calcBaseline for generating Baseline objects and groupBaseline for convolving groups of BASELINe PDFs.

Examples

# \donttest{
# Subset example data
data(ExampleDb, package="alakazam")
db <- subset(ExampleDb, c_call == "IGHG")
set.seed(112)
db <- dplyr::slice_sample(db, n=100)

# Collapse clones
db <- collapseClones(db, cloneColumn="clone_id",
                     sequenceColumn="sequence_alignment",
                     germlineColumn="germline_alignment_d_mask",
                     method="thresholdedFreq", minimumFrequency=0.6,
                     includeAmbiguous=FALSE, breakTiesStochastic=FALSE)
                     
# Calculate BASELINe
baseline <- calcBaseline(db, 
                         sequenceColumn="clonal_sequence",
                         germlineColumn="clonal_germline", 
                         testStatistic="focused",
                         regionDefinition=IMGT_V,
                         targetingModel=HH_S5F,
                         nproc = 1)

# Grouping the PDFs by the sample annotation
grouped <- groupBaseline(baseline, groupBy="sample_id")

# Get a data.frame of the summary statistics
stats <- summarizeBaseline(grouped, returnType="df")
# }