Sample Preparation and Analysis • FastQDesign

This vignette demonstrates sample preparation, downsampling, and pseudotime analysis functions.

Data Source

Reference data for sample preparation is hosted on Zenodo:

Download from: https://zenodo.org/records/19072084

# Download reference data
download.file(
  "https://zenodo.org/records/19072084/files/reference_list.rds",
  destfile = "reference_list.rds"
)

SamplePrep

Prepare reference data for experiment design:

# Load reference data (after downloading from Zenodo)
ref_list <- readRDS("reference_list.rds")

# Prepare sample (Seurat object)
cb03_list <- SamplePrep(
  ref_list[[1]],
  use_default_res = TRUE,
  cell_3d_embedding = FALSE,
  interactive = FALSE,
  min.pct = 0.2,
  logfc.threshold = 0.3,
  return.thresh = 0.05,
  verbose = TRUE
)

Parameters

Parameter	Description
`object`	Seurat object or BAM file list
`use_default_res`	Use default clustering resolution
`n_clusters`	Number of clusters (if not using default)
`condition`	Condition column for differential expression
`cell_3d_embedding`	Compute 3D embedding
`min.pct`	Minimum percentage for markers
`logfc.threshold`	Log fold change threshold

DownSample

Downsample cells to simulate different sequencing depths:

# Downsample reference
ds <- DownSample(
  ref_list[[1]],
  rate_cells = 0.1,
  enable_PCR = TRUE
)

Parameters

Parameter	Description
`object`	Seurat object
`rate_cells`	Fraction of cells to keep
`enable_PCR`	Enable PCR duplicate simulation

FindPseudotime

Perform pseudotime analysis using Monocle3:

# Perform pseudotime analysis
pt_result <- FindPseudotime(
  cb03_list,
  root_cells = NULL,  # or specify root cell names
  verbose = TRUE
)

The function returns a list with: - $cds**: Monocle3 CellDataSet - **$ pseudotime: Pseudotime values - $plot: Pseudotime visualization

SampleMatch

Compare experimental samples to reference:

# Compare samples
match_result <- SampleMatch(
  query = query_seurat,
  reference = reference_list,
  method = "seurat"
)