pwl_after_dewarping: Piecewise linear warping after aligning the landmarks

Description Usage Arguments Value

Description

Because at the right side of the gel, we have few peaks, data contain few information about the dewarping function. We downsample the gel, so that we only need to consider the dewarping results on the J=50 landmarks' dewarping results. NB: assumed that all gels have 19 non-reference lanes. Need to change otherwise.

Usage

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pwl_after_dewarping(g_id, l_id, normalized_rf, dat_without_lane1,
  data_lcm_all, zero_to_one_v_landmark, bugs_gel_id, bugs_in_gel_id,
  N_per_gel, Z_map, n_vec, lookup)

Arguments

g_id

Gel id

l_id

Lane id

normalized_rf

The normalized_rf that is between 0 and 1. Note this subtle change compared after cropping the right end of the gel.

dat_without_lane1

The data frame without peaks obtained from the reference lanes. Because when doing warping, we know these reference molecules do not exactly correspond to the molecules that would be observed in the serum samples.

data_lcm_all

A binary matrix of the number of rows being the number of serum samples and the number of columns being J+2 (J for intermediate landmarks and 2 end points)

zero_to_one_v_landmark

The landmark location on the zero to one scale.

bugs_gel_id

Starts from 1.

bugs_in_gel_id

Starts from 1 to say 19.

N_per_gel

Analyzed number of lanes per gel.

Z_map

a vector of length equal to total number of peaks detected; each element represents the landmark a peak is aligned to

n_vec

A vector of length equal to the total lane number; each element is the number of peaks within a lane.

lookup

A matrix with no. of rows equal to sample size, no. of columns equal to maximum number of peaks per lane. The numbers indicate the no. of peaks appearing from all the lanes.

Value

A list of two elements:


zhenkewu/spotgear documentation built on June 22, 2019, 1:55 a.m.