Pseudotime Inference

Overview

This block takes precomputed PCA embeddings and clustering assignments from upstream blocks and calculates a pseudotime trajectory, a measure of each cell's progression along a biological process like differentiation. It outputs a pseudotime value per cell and visualizes the results with UMAP and violin plots.

Pipeline context

This block requires both PCA embeddings and cluster assignments. It follows both Dimensionality Reduction and Leiden Clustering.

 Blocks                                 Result pool
                                       ┌───────────
             ┌─────────────────────────┤
             │                         │
             v                         │
 ╔═══════════════════════════╗ exports │
 ║ Dimensionality Reduction /║────->─-─┤ Embeddings & Clusters
 ║     Leiden Clustering     ║         │ -----------------------
 ╚═══════════════════════════╝         │
                                       ├ [sampleId][cellId] -> pcValue, clusterId
             ┌─────────────────────────┤
             │                         │
             v                         │
 ╔═══════════════════════════╗ exports │
 ║   Pseudotime Inference    ║────->─-─┤ Pseudotime scores
 ╚═══════════════════════════╝         │ -------------------
                                       ├ [sampleId][cellId] -> pseudotime
             ┌─────────────────────────┤
             │                         │
             v                         │
 ╔═══════════════════════╗             │
 ║  Downstream Analysis  ║             │
 ╚═══════════════════════╝             │

Core structure: axes and p-columns

The block consumes PCA embeddings and cluster assignments to produce a p-column containing a pseudotime value for each cell.

Input p-columns

The block requires two main inputs: principal component embeddings and cluster assignments.

1. Principal Components

• P-column name: pl7.app/rna-seq/pcvalue
• Description: The value for a given principal component for each cell.
• Requirement: Required.

# --- Core Identity ---
name: pl7.app/rna-seq/pcvalue
valueType: Double

# --- Axes ---
axesSpec:
  - name: pl7.app/sampleId
    type: String
  - name: pl7.app/sc/cellId
    type: String
  - name: pl7.app/rna-seq/pc-num
    type: String

# --- Domain ---
domain:
  pl7.app/blockId: "..." # blockId from the upstream dimensionality reduction run
  pl7.app/rna-seq/batch-corrected": "false"

# --- Annotations ---
annotations:
  pl7.app/label: "Principal Component Value"

2. Leiden Cluster

• P-column name: pl7.app/rna-seq/leidencluster
• Description: The cluster assignment for each cell.
• Requirement: Required.

name: pl7.app/rna-seq/leidencluster
valueType: String
axesSpec:
  - name: pl7.app/sampleId
    type: String
  - name: pl7.app/cellId
    type: String

Exported P-Columns

The block exports a p-frame containing the new pseudotimedpt p-column for programmatic use by downstream blocks.

1. Pseudotime Score

• P-column name: pl7.app/rna-seq/pseudotimedpt
• Description: The calculated pseudotime value, representing a cell's progress along a trajectory.
• Requirement: Required.
• Specification:

# --- Core Identity ---
name: pl7.app/rna-seq/pseudotimedpt
valueType: Double

# --- Axes ---
axesSpec:
  - name: pl7.app/sampleId
    type: String
  - name: pl7.app/cellId
    type: String

# --- Domain ---
domain:
  pl7.app/blockId: "..." # a unique identifier for the block run

# --- Annotations ---
annotations:
  pl7.app/label: "Pseudotime Scores"

Summary of Exported P-Columns

P-Column Name	Description	Axes	Requirement
pl7.app/rna-seq/pseudotimedpt	The calculated pseudotime value.	[sampleId][cellId]	Required