RRepoGEO

REPOGEO REPORT · LITE

seandavi/awesome-single-cell

Default branch master · commit 9005eaaf · scanned 6/25/2026, 8:37:10 AM

GitHub: 3,766 stars · 1,086 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface seandavi/awesome-single-cell, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README H1 and opening sentence to explicitly state 'awesome list'

    Why:

    CURRENT
    # awesome-single-cell

List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc. Contributions welcome...
    COPY-PASTE FIX
    # awesome-single-cell: A Curated List of Single-Cell Software and Resources

This is a community-curated awesome list of software packages, data resources, and methods for single-cell data analysis, including RNA-seq, ATAC-seq, spatial transcriptomics, and more. Contributions welcome...
  • hightopics#2
    Add 'curated-list' topic to reinforce repo's nature

    Why:

    CURRENT
    analysis-pipeline, atac-seq, awesome-list, bioinformatics, cell-clusters, cell-differentiation, cell-populations, clustering, data-integration, data-visualization, dimensionality-reduction, gene-expression, gene-expression-profiles, python, rna-seq-data, rna-seq-experiments, scrna-seq-data, single-cell, spatial-transcriptomics
    COPY-PASTE FIX
    analysis-pipeline, atac-seq, awesome-list, bioinformatics, cell-clusters, cell-differentiation, cell-populations, clustering, curated-list, data-integration, data-visualization, dimensionality-reduction, gene-expression, gene-expression-profiles, python, rna-seq-data, rna-seq-experiments, scrna-seq-data, single-cell, spatial-transcriptomics
  • mediumreadme#3
    Add a section highlighting the unique value of expert commentary

    Why:

    COPY-PASTE FIX
    ## Why this list is different

Unlike many other resource lists, awesome-single-cell includes expert commentary, critical evaluations, and insights into the practical utility and limitations of the listed software and resources. This provides a more opinionated and curated guide for researchers navigating the single-cell landscape.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface seandavi/awesome-single-cell
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Seurat
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Seurat · recommended 1×
  2. Scanpy · recommended 1×
  3. Cell Ranger · recommended 1×
  4. Monocle 3 · recommended 1×
  5. SCENIC · recommended 1×
  • CATEGORY QUERY
    How can I find software for analyzing single-cell RNA sequencing data?
    you: not recommended
    AI recommended (in order):
    1. Seurat
    2. Scanpy
    3. Cell Ranger
    4. Monocle 3
    5. SCENIC
    6. Velocyto
    7. scVelo
    8. Partek Flow

    AI recommended 8 alternatives but never named seandavi/awesome-single-cell. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find a curated list of bioinformatics tools for single-cell genomics?
    you: not recommended
    AI recommended (in order):
    1. Awesome Single Cell
    2. OmicVerse
    3. scRNA-tools
    4. The Human Cell Atlas (HCA) Data Coordination Platform (DCP) Documentation
    5. Nature Methods "Technology Feature" Articles on Single-Cell Analysis

    AI recommended 5 alternatives but never named seandavi/awesome-single-cell. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of seandavi/awesome-single-cell?
    pass
    AI named seandavi/awesome-single-cell explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts seandavi/awesome-single-cell in production, what risks or prerequisites should they evaluate first?
    pass
    AI named seandavi/awesome-single-cell explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo seandavi/awesome-single-cell solve, and who is the primary audience?
    pass
    AI did not name seandavi/awesome-single-cell — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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seandavi/awesome-single-cell — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite