em_count: Count transcripts using an Expectation Maximization (EM)...

In Gibbons-Lab/mbtools: Provides helper functions for microbiome preprocessing and analysis

Count transcripts using an Expectation Maximization (EM) algorithm.

Description

Count transcripts using an Expectation Maximization (EM) algorithm.

Usage

em_count(
  txreads,
  txlengths,
  weights,
  ntx,
  nr,
  maxit = 1000L,
  reltol = 0.01,
  abstol = 0.01
)

Arguments

txreads	A minimal matrix where each row corresponds to an alignment. The first column denotes transcript indices in [0, ntx-1] and the second column denotes read indices in [0, nr -1].
txlengths	The sequence lengths for each transcript. Ideally those should be the effective transcript lengths meaning the overall number of possible alignment start positions in a transcript.
weights	Weights for individual alignments.
ntx	The total number of unique transcripts.
nr	The total number of unique reads.
maxit	Maximum number of EM iterations.
reltol	The relative tolerance for convergence.
abstol	The absolute tolerance for convergence.

Value

A list with the following components.

p

The length-normalized and read scaled transcript counts

iterations

The number of used EM iterations

num_ecs

The number of equivalence classes

change

The last osbserved absolute change in transcript counts

Gibbons-Lab/mbtools documentation built on Jan. 28, 2024, 11:08 a.m.