Infer gene regulatory networks from bulk or general expression data with mutual-information (ARACNe) and tree-ensemble (GENIE3, GRNBoost2) methods, and infer transcription-factor protein activity from regulons with VIPER and msVIPER. Covers the activity-not-edges paradigm, the undirected-association caveat, the DREAM5 wisdom-of-crowds and method-complementarity result, AUPRC-over-AUROC evaluation, and gold-standard incompleteness. Use when inferring a regulatory network from a bulk expression matrix, finding master regulators, or scoring TF activity from a signature. For single-cell motif-pruned regulons see scenic-regulons; for co-expression modules see coexpression-networks.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/HPClaw☆ 32026年10月11日 更新
Download genome assemblies, gene records, and ortholog data from NCBI using the modern Datasets v2 CLI (replaces assembly_summary.txt scraping and many EFetch workflows). Use when bulk-pulling genome assemblies, gene metadata across species, ortholog sets, or BLAST databases; when E-utilities are too slow for genome-scale work; or when automatic checksum verification, parallel download, and clean accession-driven retrieval are required. Encodes the JSON-lines output format, dataformat conversion, --dehydrated for cloud workflows, and when Datasets is/isn't the right tool.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/HPClaw☆ 32026年10月11日 更新
Query the Ensembl REST API for gene/transcript/protein lookup, sequence retrieval, comparative genomics (Compara), variant effect prediction (VEP), regulatory features, and cross-species ortholog/paralog calls. Use when pulling Ensembl-native data (Ensembl Gene IDs, version-pinned releases, archive endpoints for reproducibility), gene/transcript/exon structure with stable IDs, or VEP for variant annotation. Encodes the 15 req/sec rate limit, archive (e110.rest.ensembl.org) for reproducibility, Ensembl divisions (vertebrates / plants / fungi / metazoa / bacteria), and the symbol-vs-ID stability problem.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/HPClaw☆ 32026年10月11日 更新
Build publication-quality figures in R with ggplot2 using the grammar of graphics (data + aesthetics + geometries + scales + facets + themes) with CVD-safe palettes, cairo_pdf TrueType embedding, programmatic aes via tidy evaluation, and the theme_classic publication baseline. Use when producing static figures in R for papers, presentations, or reports.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/HPClaw☆ 32026年10月11日 更新
Quality control for pooled CRISPR screens covering library representation, Gini index, log-skew, replicate Pearson and Spearman concordance, essentialome precision-recall AUC against CEGv2 (Hart 2017), Cas9 cut-toxicity diagnostics, copy-number amplicon detection (Aguirre 2016 / Munoz 2016), bottleneck propagation through plasmid pool, infection, selection, and endpoint stages, MOI verification, and DepMap-style screen-quality scoring. Use when assessing screen quality before hit calling, deciding whether to repeat or rescue a screen, diagnosing low-confidence hits, choosing between MAGeCK / BAGEL2 / Chronos based on quality grade, picking a normalization strategy from QC signatures, or evaluating whether an in-vivo screen retained adequate library complexity.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/HPClaw☆ 32026年10月11日 更新
Compute genome-to-genome distances (ANI, AAI, dDDH, k-mer Mash) and assign taxonomic classifications using skani (Shaw 2023), FastANI (Jain 2018), pyani / pyANI ANIb / ANIm, OrthoANI (Lee 2016), AAI (amino-acid identity), dDDH via TYGS / GGDC, GTDB-Tk (Chaumeil 2020 standard prokaryote taxonomy), and Mash MinHash (Ondov 2016). Use when delineating prokaryote species (95% ANI threshold; Jain 2018 Nat Commun 9:5114), assigning genomes to GTDB taxonomy with ANI radius, computing genome similarity matrices for clustering, classifying archaea, evaluating MAG (metagenome-assembled genome) species assignment, applying skani for fast metagenomic ANI screening, or reconciling 16S rRNA-based taxonomy with whole-genome ANI.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/HPClaw☆ 32026年10月11日 更新
Predict RBP binding from RNA sequence using deep learning models (RBPNet sequence-to-signal, RNAProt RNN, GraphProt2 GCN with structure, DeepCLIP, DeepRiPe multi-modal CNN) for variant-effect prediction, in silico binding-site discovery, model interpretation, and transfer learning from CLIP and RBNS datasets. Use when computational prediction of RBP binding from sequence is needed, evaluating variant effects on binding without further wet-lab experiments, comparing model performance, or training a custom model on ENCODE eCLIP data.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/HPClaw☆ 32026年10月11日 更新
Estimate causal effects of an exposure on an outcome from GWAS summary statistics using genetic instruments. Implements IVW (fixed/random), MR-Egger, weighted median/mode, MR-RAPS, CAUSE, GSMR-HEIDI, MR-PRESSO, MVMR, MR-Clust, LCV, and LHC-MR via TwoSampleMR, MendelianRandomization, MR-PRESSO, cause, and lhcMR. Use when testing causal direction between traits, evaluating drug-target effects via cis-pQTL/cis-eQTL, performing multivariable mediation MR, distinguishing causation from correlated horizontal pleiotropy, or producing STROBE-MR-compliant sensitivity batteries.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/HPClaw☆ 32026年10月11日 更新
Assesses RNA-seq data quality specifically for alternative splicing analysis. QC layers include experimental design audit (library prep, read length, depth, replicates), STAR 2-pass cohort-style alignment, junction saturation curves and discovery plateau detection, novel-vs-known junction ratio diagnostics, junction-overhang distribution, splice-site strength scoring (MaxEntScan intrinsic + SpliceAI context-aware), strandedness verification, GENCODE basic vs comprehensive choice, and rRNA contamination screening. Splicing analysis is more demanding than DGE on read length, depth, library prep, alignment strategy, and annotation choice — failures silently bias PSI estimates and inflate novel-junction false positives. Use when evaluating data suitability for splicing analysis, troubleshooting low event detection, or designing sequencing experiments where AS is a primary endpoint.
日本語の概要は準備中です。原文の説明を表示しています。
peacezha/HPClaw☆ 32026年10月11日 更新
Use this skill to evaluate which defensive driving program is best for your fleet. Compares Smith System, CarriersEdge, Compass-native training, and other options.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill when the user asks about the financial differences between being an owner-operator vs company driver — gross pay, expenses, net pay, capital requirements, risk tolerance, lifestyle, and how to evaluate the path. Reference industry pay surveys.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill to evaluate document retention software options. Covers compliance features, ease of use, integration, and cost.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill when selecting a TPR-registered Training Provider for behind-the-wheel ELDT training. Covers the registry, evaluation criteria, and common pitfalls.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill when the user asks how to build, measure, or improve safety culture in a motor carrier — leading vs lagging safety indicators, blame-free reporting, near-miss programs, safety committee structure, monthly safety meetings, ATA Safety Management Program guidance, and how to evaluate cultural maturity. Reference ATA SMP + DOT safety culture research.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use when a carrier is evaluating ELD / telematics / dashcam platforms and needs an objective comparison of Samsara, Motive (formerly KeepTruckin), and Geotab. Covers ELD compliance, AI dashcams, driver scoring, integrations, pricing structure, and which fleet profile suits which platform.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill when selecting or replacing an ELD provider. Covers the FMCSA Registered ELD list, evaluation criteria, common provider removals from the registered list, and the 60-day transition rule.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill to evaluate whether to switch from annual MVR pulls to continuous monitoring. Covers cost-benefit, intervention timing, and major providers.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill to evaluate which DataQ challenges have winning evidence and which don't. Covers documented vs anecdotal evidence and the 8 high-success patterns.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill when selecting an MRO for drug testing program oversight. Covers MRO qualifications under Part 40, what the MRO does, and how to evaluate MRO services.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill when referring a driver to SAP after a positive test or refusal. Covers SAP selection, the evaluation/treatment cycle, return-to-duty test, and follow-up testing schedule.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use when a carrier needs to build an internal dispatcher training program, onboard new dispatchers, or certify dispatcher competency. Covers job description, required skills, training modules, certification frameworks (CDS, CTP), shadowing, evaluation, and career path.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill to use the Pre-Employment Screening Program (PSP) for evaluating driver applicants. Covers what PSP shows, cost, and how to interpret reports.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill to evaluate whether credit reports are appropriate for driver applicant screening. Covers EEOC guidance, FCRA, and common carrier policies.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新
Use when a carrier asks how to calculate cost-per-mile (CPM) at the fleet, truck, lane, or driver level — separating fixed vs variable costs, allocating overhead, accounting for empty miles, and using CPM to negotiate rates, build pricing tiers, or evaluate lane profitability.
日本語の概要は準備中です。原文の説明を表示しています。
x3allamerican/skills☆ 32026年5月17日 更新