Bulk Proteomics

Expression Count Matrix

Examples of expression count matrix are Quantification, Filtered counts, Normalized counts. Analysis tasks that can be invoked from expression count matrix are listed below.

Task Menu Section	Analysis Task Name
Annotation/Metadata	Publish attributes to study
QA/QC	Feature distribution
Pre-analysis tools	Merge matrices
Filtering	Filter features Filter samples Split by attribute
Normalization and scaling	Normalization Normalization to baseline Scale expression (Available on normalized data only) Impute low expression (Available on normalized data only) Impute missing values
Batch removal	General linear model
Statistics	Differential analysis Correlation Descriptive statistics Compute biomarkers Cox Regression Kaplan-Meier Classification
Exploratory analysis	Graph-based clustering K-means clustering Compare clusters PCA t-SNE UMAP Hierarchical clustering / heatmap AUCell SVD
Biological interpretation	GSEA Gene set ANOVA Gene set enrichment

PCA

Analysis tasks that can be invoked from PCA data node are listed below.

Task Menu Section	Analysis Task Name
Annotation/Metadata	Publish attributes to study
Batch removal	General linear model Harmony
Statistics	Differential analysis Correlation Descriptive statistics Compute biomarkers Cox Regression Kaplan-Meier
Exploratory analysis	Graph-based clustering K-means clustering Compare clusters t-SNE UMAP Find multimodal neighbors SVD
Conversion	Export matrix

Differential Analysis Result

Analysis tasks that can be invoked from differential analysis result (e.g., limma-trend) are listed below.

Task Menu Section	Analysis Task Name
QA/QC	Feature distribution
Filtering	Differential analysis filter
Statistics	Descriptive statistics
Exploratory analysis	Hierarchical clustering / heatmap Merge differential expression results
Motif detection	Detect de novo motifs Search for known motifs
Biological interpretation	Gene set enrichment Correlation Engine atlases Correlation Engine pathways