Publication-ready volcano plots and GO analysis with ease
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Upload your data
Upload a CSV or TSV file
Accepted file formats:
- CSV (comma or semicolon separated values)
- TSV (tab-separated values) Upload an omics dataset in which a single gene/protein is an observation
(must contain gene names!) Performs many data curations
(always displays an info in case data is modified!)
Multiple testing increases false positive risk - when testing many hypotheses, some will appear significant by chance alone.
Available Methods:
Benjamini-Hochberg (BH): Controls false discovery rate (FDR), balances power and false positives
Benjamini-Yekutieli (BY): More conservative than BH, makes no assumptions about dependencies
Hochberg: Less conservative than Bonferroni, controls family-wise error rate
Bonferroni: Most conservative, strongly controls family-wise error rate
None: Unadjusted p-values, high false positive risk
Recommendation: BH is suitable for most analyses. BY provides more conservative control but at the cost of statistical power.Use BY if you have, for example, RNA‐sequencing data from heterogeneous tumor samples where unpredictable, complex gene co-expression patterns create unknown dependencies among tests, necessitating robust FDR control despite reduced power.
Select
None
Bonferroni
Hochberg
Benjamini-Hochberg
Benjamini-Yekutieli
GSEA analysis controls
GO Term Selection Criteria for Gene Set Enrichment analysis (GSEA):
Terms must contain 5-500 genes detected in your experiment
At least 5% of genes in each term must be detected in your data
Filtered by selected ontology category
This ensures meaningful and statistically relevant GO terms for your analysis.
