createBaseline: Creates a Baseline object

In shazam: Immunoglobulin Somatic Hypermutation Analysis

Creates a Baseline object

Description

createBaseline creates and initialize a Baseline object.

Usage

createBaseline(
  description = "",
  db = data.frame(),
  regionDefinition = createRegionDefinition(),
  testStatistic = "",
  regions = NULL,
  numbOfSeqs = matrix(),
  binomK = matrix(),
  binomN = matrix(),
  binomP = matrix(),
  pdfs = list(),
  stats = data.frame()
)

Arguments

description	character providing general information regarding the sequences, selection analysis and/or object.
db	data.frame containing annotation information about the sequences and selection results.
regionDefinition	RegionDefinition object defining the regions and boundaries of the Ig sequences.
testStatistic	character indicating the statistical framework used to test for selection. For example, "local" or "focused" or "imbalanced".
regions	character vector defining the regions the BASELINe analysis was carried out on. For "cdr" and "fwr" or "cdr1", "cdr2", "cdr3", etc. If NULL then regions will be determined automatically from regionDefinition.
numbOfSeqs	matrix of dimensions r x c containing the number of sequences or PDFs in each region, where: r = number of rows = number of groups or sequences. c = number of columns = number of regions.
binomK	matrix of dimensions r x c containing the number of successes in the binomial trials in each region, where: r = number of rows = number of groups or sequences. c = number of columns = number of regions.
binomN	matrix of dimensions r x c containing the total number of trials in the binomial in each region, where: r = number of rows = number of groups or sequences. c = number of columns = number of regions.
binomP	matrix of dimensions r x c containing the probability of success in one binomial trial in each region, where: r = number of rows = number of groups or sequences. c = number of columns = number of regions.
pdfs	list of matrices containing PDFs with one item for each defined region (e.g. cdr and fwr). Matrices have dimensions r x c dementions, where: r = number of rows = number of sequences or groups. c = number of columns = length of the PDF (default 4001).
stats	data.frame of BASELINe statistics, including: mean selection strength (mean Sigma), 95% confidence intervals, and p-values with positive signs for the presence of positive selection and/or p-values with negative signs for the presence of negative selection.

Details

Create and initialize a Baseline object.

The testStatistic indicates the statistical framework used to test for selection. For example,

• local = CDR_R / (CDR_R + CDR_S).

• focused = CDR_R / (CDR_R + CDR_S + FWR_S).

• immbalance = CDR_R + CDR_s / (CDR_R + CDR_S + FWR_S + FWR_R)

For focused the regionDefinition must only contain two regions. If more than two regions are defined, then the local test statistic will be used. For further information on the frame of these tests see Uduman et al. (2011).

Value

A Baseline object.

References

1. Hershberg U, et al. Improved methods for detecting selection by mutation analysis of Ig V region sequences. Int Immunol. 2008 20(5):683-94.

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

3. Yaari G, et al. Models of somatic hypermutation targeting and substitution based on synonymous mutations from high-throughput immunoglobulin sequencing data. Front Immunol. 2013 4(November):358.

See Also

See Baseline for the return object.

Examples

# Creates an empty Baseline object
createBaseline()

shazam documentation built on Oct. 3, 2023, 1:06 a.m.