「aims」の検索結果

treekoR is a novel framework that aims to utilise the hierarchical nature of single cell cytometry data to find robust and interpretable associations between cell subsets and patient clinical end points. These associations are aimed to recapitulate the nested proportions prevalent in workflows inovlving manual gating, which are often overlooked in workflows using automatic clustering to identify cell populations. We developed treekoR to: Derive a hierarchical tree structure of cell clusters; qua

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This package aims to integrate GWAS-derived SNPs and coexpression networks to mine candidate genes associated with a particular phenotype. For that, users must define a set of guide genes, which are known genes involved in the studied phenotype. Additionally, the mined candidates can be given a score that favor candidates that are hubs and/or transcription factors. The scores can then be used to rank and select the top n most promising genes for downstream experiments.

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Manhattan plot and QQ Plot are commonly used to visualize the end result of Genome Wide Association Study. The "ggmanh" package aims to keep the generation of these plots simple while maintaining customizability. Main functions include manhattan_plot, qqunif, and thinPoints.

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cogeqc aims to facilitate systematic quality checks on standard comparative genomics analyses to help researchers detect issues and select the most suitable parameters for each data set. cogeqc can be used to asses: i. genome assembly and annotation quality with BUSCOs and comparisons of statistics with publicly available genomes on the NCBI; ii. orthogroup inference using a protein domain-based approach and; iii. synteny detection using synteny network properties. There are also data visualizat

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Installs a self-contained conda instance that is managed by the R/Bioconductor installation machinery. This aims to provide a consistent Python environment that can be used reliably by Bioconductor packages. Functions are also provided to e

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doubletrouble aims to identify duplicated genes from whole-genome protein sequences and classify them based on their modes of duplication. The duplication modes are i. segmental duplication (SD); ii. tandem duplication (TD); iii. proximal duplication (PD); iv. transposed duplication (TRD) and; v. dispersed duplication (DD). Transposon-derived duplicates (TRD) can be further subdivided into rTRD (retrotransposon-derived duplication) and dTRD (DNA transposon-derived duplication). If users want a s

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Draft, audit, or minimally revise English- or Chinese-language academic prose to reduce formulaic, vacuous, mechanically repetitive, or process-leaking language while preserving claims, evidence strength, logical relations, manuscript-wide terminology identity, document-level pattern variation, and scholarly register. Use for papers, abstracts, grants, cover letters, and reviewer responses when the user asks to de-AI, humanize, audit AI-like phrasing, or rewrite text without changing meaning. English is primary; Chinese is supported. Not for detector evasion, policy circumvention, pure translation, non-academic copy, or adding facts, citations, examples, or author experiences that the source does not contain.

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Use when a leader must review or approve TEXT-based team output before it ships — content briefs checked for angle, pillar, and CTA, ad copy and creative checked for substantiated claims, on-brand tone, a hook inside the first 125 characters, and platform policy, ending in an Approve, Revise, or Redo verdict with point-by-point feedback. Trigger on 'review this brief', 'approve the ad copy', 'check ads before launch', 'review team output', 'is this good enough to publish', 'my team keeps sending me drafts'. Not for — reviewing a visual design, see `47-design-review-global`; evaluating a person over a period, see `65-team-performance-review-global`; writing the copy yourself, see `05-ad-copy-global`.

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Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

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Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

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Grilling session that mines the user for fragments — heterogeneous nuggets of writing (claims, vignettes, sharp sentences, half-thoughts) — and appends them to a single document as raw material for a future article. Use when the user wants to develop ideas before imposing structure, or mentions "fragments", "ideate", or "raw material" for writing.

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Explain classroom chemistry observations and fictional potion concepts without unverified safety claims. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.

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Validates defensive controls with paired authorized action and observation evidence, distinguishing blocked, prevented, detected, responded, and telemetry-gap outcomes. Use for purple-team validation design or offline fixture review; not unsanctioned testing or production efficacy claims.

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Performs quality control, citation validation, and fact-checking before human review. Use after research is complete to verify all sources and claims before production.

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Conducts investigative-grade research with primary source analysis, cross-verification, and trial-level depth. Use when an album needs factual research, source material, or verification of claims.

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Adversarial code reviewer for Bug Hunter. Rigorously challenges each reported bug to determine if it's real or a false positive. Uses doc-lookup (Context Hub + Context7) to verify framework claims before disproval. The immune system that kills false positives.

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Use when `paper-review` has claims plus evidence gaps and needs the final referee-style report.

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Rewrite `outline/claim_evidence_matrix.md` as a projection/index of evidence packs (NO PROSE), so claims/axes are driven by `outline/evidence_drafts.jsonl` rather than outline placeholders.

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Use when a review workspace has manuscript text and needs a traceable claim ledger.

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Audit and rewrite evaluation/numeric claims to ensure they carry minimal protocol context (task + metric + constraint) and avoid underspecified model naming.

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Freshly judge whether a finished change and its claims meet original acceptance: PASS, FAIL or NOT_PROVEN. Use when: asked for a go/no-go, sign-off or independent verdict.

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Audit claims that work is done or shipped against the diff or repo. Use when: asked whether something really got done, even if it looks obvious.

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This skill should be used when verifying documentation claims against codebase reality. Triggers on "audit docs", "verify documentation", "check docs", "docs accurate", "documentation drift", "before release", "after refactor", "docs don't match". Uses two-pass extraction with pattern expansion for comprehensive detection.

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Runs verification commands and confirms output before success claims. Use before claiming work done or committing or PRs.

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