RNA-seq Differential Expression
Identify differentially expressed genes from count/expression matrix
Input: CSV/TSV with genes × samples (first column = gene names, header row = sample names, last row of header can have group labels)
Params: pvalue_cutoff, log2fc_cutoff, method
Single-cell RNA-seq Clustering
Cell type identification and UMAP visualization
Input: CSV/TSV with genes × cells count matrix
Params: n_pcs, resolution
Proteomics Quantification
Protein expression analysis and normalization
Input: CSV/TSV with proteins × samples intensity matrix
Params: normalization, missing_value
Volcano Plot
Generate volcano plot from DE results or expression data
Input: CSV with columns: gene, log2FC, pvalue OR expression matrix with group info
Params: pvalue_cutoff, log2fc_cutoff
Correlation Analysis
Gene-gene or feature correlation heatmap
Input: CSV/TSV expression matrix
Params: method
DESeq2 Differential Expression (R)
Publication-grade DE analysis using R DESeq2 with volcano/MA/heatmap plots
Input: CSV count matrix (genes x samples, first col = gene names)
Params: pvalue_cutoff, log2fc_cutoff, control_prefix, treat_prefix