make_m2: make_m2 (Integrated with Automatic Batching)

In splikit: Analysing RNA Splicing in Single-Cell RNA Sequencing Data

make_m2 (Integrated with Automatic Batching)

Description

Creates the M2 matrix from a given m1_inclusion_matrix and eventdata with intelligent memory management. Automatically detects when the operation would exceed memory limits and switches to a batched sparse matrix approach.

Usage

make_m2(
  m1_inclusion_matrix,
  eventdata,
  batch_size = 5000,
  memory_threshold = 2e+09,
  force_fast = FALSE,
  n_threads = 1,
  use_cpp = TRUE,
  verbose = FALSE
)

Arguments

m1_inclusion_matrix	A sparse matrix to be modified and used for creating the M2 matrix.
eventdata	A data.table containing event information with at least group_id and an index column.
batch_size	An integer specifying the number of groups to process per batch (default: 5000). Only used when batched processing is triggered.
memory_threshold	A numeric value representing the maximum number of rows allowed in the summary before switching to batched processing (default: 2e9, which is ~93% of 2^31).
force_fast	A logical flag to force fast processing regardless of size estimates (default: FALSE). WARNING: This may cause memory errors on large datasets.
n_threads	Number of threads for parallel processing (default: 1). Used for C++ implementation and batched R processing. Values > 1 require parallel package for batched mode.
use_cpp	Logical flag to use fast C++ implementation (default: TRUE). Falls back to R implementation if FALSE.
verbose	A logical flag for detailed progress reporting (default: FALSE).

Value

A sparse matrix M2 with the dummy row removed and proper adjustments made.

Examples

junction_abundance_object <- load_toy_SJ_object()
m1_obj <- make_m1(junction_ab_object = junction_abundance_object)

# obtaining the m1 and eventdata
m1 <- m1_obj$m1_inclusion_matrix
eventdata <- m1_obj$event_data
m2 <- make_m2(m1_inclusion_matrix = m1, eventdata = eventdata)

splikit documentation built on May 13, 2026, 9:08 a.m.