dual_discrim_shared_likelihood: Calculate likelihood of two beta-sharing candidate alpha-beta...
In edwardslee/alphabetr: Algorithms for High-Throughput Sequencing of Antigen-Specific T Cells
Description
Usage
Arguments
Value
Description
dual_discrim_shared_likelihood() is used within dual_top
to calculate the likelihood that two alpha-beta pairs identified by
bagpipe sharing the same beta chain derive from a two
distinct clones sharing the same beta chain dual-alpha clone (instead of
a single dual-alpha clone)
Usage
1
2
dual_discrim_shared_likelihood(est1, est2, err, numb_cells, numb_wells,
binomials, multinomials)
Arguments
est1
Frequency estimate of the first alpha-beta clone
est2
Frequency estimate of the second alpha-beta clone
err
Mean drop error rate
numb_cells
Vector containing the number of cells per well
numb_wells
Vector containing the number of wells with the sample
sizes given by numb_cells
binomials
Calculations of the needed binomial coefficients; this is
faster in R than in Rcpp (from my own tests)
multinomials
Calculations of the needed multinomial coefficients;
this is way faster in R due to vectorization
Value
A numeric containing the negative log likelihood
edwardslee/alphabetr documentation built on May 15, 2019, 11:03 p.m.
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Description Usage Arguments Value
Description
dual_discrim_shared_likelihood() is used within dual_top
to calculate the likelihood that two alpha-beta pairs identified by
bagpipe sharing the same beta chain derive from a two
distinct clones sharing the same beta chain dual-alpha clone (instead of
a single dual-alpha clone)
Usage
1 2 | dual_discrim_shared_likelihood(est1, est2, err, numb_cells, numb_wells,
binomials, multinomials)
|
Arguments
est1 |
Frequency estimate of the first alpha-beta clone |
est2 |
Frequency estimate of the second alpha-beta clone |
err |
Mean drop error rate |
numb_cells |
Vector containing the number of cells per well |
numb_wells |
Vector containing the number of wells with the sample
sizes given by |
binomials |
Calculations of the needed binomial coefficients; this is faster in R than in Rcpp (from my own tests) |
multinomials |
Calculations of the needed multinomial coefficients; this is way faster in R due to vectorization |
Value
A numeric containing the negative log likelihood
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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