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ExtremaRank

Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk

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Details

External ID
1402629607
Source
GITHUB
Company
—
Product
ExtremaRank
Website domain
github.com
Launched
Oct. 3, 2026
Cohort
—
Upvotes
10
Upvotes percentile
0.09
Tags
bioconductor, bioinformatics, cpp, deseq2, edger, exact-optimization, limma, metabolomics, microarray, omics, paired-data, proteomics, python, r, r-package, reproducible-research, rna-seq, robustness, sample-influence, single-cell

Enrichment

Niche
machine learning and search infrastructure
Vertical
Healthcare
Function
Analytics & BI
Audience
Developer
AI stance
Not AI
Project type
Hobby / open-source project
Normalized one-liner
sample-deletion robustness analysis for omics data
Manually corrected
False

Could you build this?

No This is a specialized bioinformatics/biostatistics framework implementing theoretical sample-deletion robustness bounds and Bioconductor model refits for omics data.

What it would actually take: The package requires deep expertise in statistical genomics, mathematical robustness proofs (influence functions, deletion certificates), and integration with Bioconductor pipelines (DESeq2, edgeR). The architecture consists of core numerical algorithms in C++/R/Python to compute minimum deletion bounds without brute-force combinatorial refits. Building it requires peer-reviewed statistical methodology and domain knowledge of single-cell and pseudobulk transcriptomics.

Competitors

Other products that read as similar to this one — 711 launches clear the similarity bar, closest 8 shown.

Attention rank: #597 of 712 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 334 days after the earliest competitor.

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