Reconstruct ancestral states at internal phylogenetic nodes for sequences (PAML codeml, IQ-TREE --ancestral, GRASP, FastML), discrete traits (corHMM hidden-rate Markov, ape::ace, phytools::make.simmap stochastic mapping, BayesTraits), and continuous traits (phytools::fastAnc, geiger Brownian/OU, RPANDA). Use when designing constructs for ancestral protein resurrection, tracing trait evolution along a tree, performing stochastic character mapping, testing models of trait evolution (BM vs OU vs EB), inferring ancestral genome content via Dollo or DTL reconciliation, or quantifying ancestral-state uncertainty for downstream comparative analyses.
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
Normalize read-depth copy-ratio profiles and segment them into copy-number regions using circular binary segmentation (CBS, DNAcopy), hidden Markov models, HaarSeg, and fused-lasso methods. Covers GC-content, mappability, and replication-timing (wave-artifact) bias correction, panel-of-normals/PCA denoising, diploid-baseline centering, and algorithm selection by sequencing depth and event size. Use when choosing a segmentation algorithm, correcting depth bias, diagnosing oversegmentation or a mis-centered baseline, tuning CBS or HMM parameters, or understanding why a downstream CNV caller produced fragmented or shifted segments.
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
Maps GWAS-implicated loci to candidate effector (causal) genes by integrating variant-to-gene (V2G) features via Open Targets L2G (Mountjoy 2021), MAGMA gene-based association (de Leeuw 2015), FUMA SNP2GENE, cS2G combined SNP-to-gene scores (Gazal 2022), Polygenic Priority Scores (PoPS, Weeks 2023), FLAMES, INQUISIT, DEPICT, and enhancer-gene predictors (ABC, ENCODE-rE2G). Use when narrowing a GWAS lead locus to a candidate causal gene, picking between proximity, eQTL-based, and similarity-based prioritizers, integrating multi-evidence streams (fine-mapping, colocalization, ABC enhancer-gene, distance, chromatin), reconciling discordant L2G vs PoPS calls, prioritizing tissue-specific eQTL evidence, or triangulating across at least three independent lines of evidence for a publication-grade effector-gene nomination.
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
Reads, writes, and converts molecular file formats (SMILES, InChI, SDF V2000/V3000, MOL2, PDB, MMTF) using RDKit and Open Babel with rigorous handling of aromaticity perception, stereochemistry, implicit/explicit hydrogens, kekulization, and salt/fragment separation. Use when loading chemical libraries, debugging parse failures, or preparing molecules for downstream standardization, descriptor calculation, or docking.
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 ChIP-seq quality across antibody specificity, fragmentation, enrichment, replicate concordance, and library complexity. Computes FRiP, NSC/RSC (phantompeakqualtools), library complexity (NRF/PBC1/PBC2), deepTools plotFingerprint (JS distance, AUC, synthetic JS), ChIPQC, IDR with ENCODE Nself/Nt rules, and detects hyper-ChIPable artifacts. Use when validating an antibody, diagnosing failed peak calls, deciding whether to proceed with downstream analysis, grading against ENCODE thresholds, or auditing replicate concordance.
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
Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.
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
Call accessible chromatin regions from ATAC-seq BAM files using MACS3, MACS2, Genrich, or HMMRATAC. Use when identifying open chromatin from aligned ATAC-seq, choosing between point-source vs HMM peak callers, applying ENCODE-style pseudoreplicate IDR, removing blacklist regions, or fixing 501bp consensus peaks for downstream differential analysis.
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
Parse and analyze multiple sequence alignments using Biopython. Extract sequences, identify conserved regions, analyze gaps, work with annotations, and manipulate alignment data for downstream analysis. Use when parsing or manipulating multiple sequence alignments.
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
Detect allele-specific chromatin accessibility from ATAC-seq using WASP, GATK ASEReadCounter, or RASQUAL. Use when mapping cis-regulatory genetic variants from heterozygous SNPs, separating cis from trans regulation, building chromatin QTL (caQTL) maps, validating GWAS variant function with allelic imbalance, or detecting reference allele mapping bias before downstream analysis.
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
Creates sashimi-style plots showing RNA-seq read coverage and splice junction counts using ggsashimi (general-purpose, condition-grouped overlays), rmats2sashimiplot (rMATS-output-aware), MAJIQ-VOILA (LSV posteriors interactive HTML), leafviz (leafcutter clusters Shiny), Jutils (tool-agnostic heatmaps and sashimi for rMATS/leafcutter/SUPPA2/MAJIQ output), or pyGenomeTracks (multi-track publication figures). Tool choice depends on the upstream differential-splicing tool's output format and the publication vs interactive use case. Use when visualizing specific splicing events, validating differential splicing calls, or producing publication-quality figures.
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
Perform multiple sequence alignment using MAFFT, MUSCLE5, ClustalOmega, or T-Coffee. Guides tool and algorithm selection based on dataset size, sequence divergence, and downstream application. Use when aligning three or more homologous sequences for phylogenetics, conservation analysis, or evolutionary studies.
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 a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative overlap removal, fixed-width re-centering, and majority-rule overlap. Use when generating a stable peak coordinate system for downstream differential accessibility, ML feature engineering, cross-sample comparison, or fixed-width peak counts; covers Corces 2018 iterative overlap (501 bp), DiffBind summit re-centering, and ENCODE consistency rules.
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
Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues before phylogenetic inference, HMM building, or selection analysis.
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
RichDocument action toolkit for markdown and interactive content outside live chat. Use when adding an action or content source, wiring a remote action surface, putting actions on a MarkdownStream/BasicMarkdownContent preview, or touching features/rich-document/**, <RichDocument>, <RichDocumentActionSurface>, registerAction, ContentSourceAdapter, or enableContextMenu. NOT for the live chat message bar (use overlay-system).
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。
armanisadeghi/ai-matrx☆ 32026年10月13日 更新
Redux state for agent execution and firing agent shortcuts. Use when editing features/agents/redux/, building agent UI, creating a conversation, touching assembleRequest or NDJSON stream state, wiring agent-state selectors, adding a per-conversation capability, or triggering a shortcut from a button, menu, or code (useShortcutTrigger, launchAgentExecution).
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。
armanisadeghi/ai-matrx☆ 32026年10月13日 更新
Integrate Convex static self hosting into existing apps using the latest upstream instructions from get-convex/self-hosting every time. Use when setting up upload APIs, HTTP routes, deployment scripts, migration from external hosting, or troubleshooting static deploy issues across React, Vite, Next.js, and other frontends.
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。
waynesutton/waynesutton-ai☆ 22026年9月8日 更新
Generates PSR-7 HTTP Message implementations for PHP 8.5. Creates Request, Response, Stream, Uri, and ServerRequest classes with immutability. Includes unit tests.
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。
MikeCheng1208/BattleTree☆ 22026年7月22日 更新
Generates PSR-17 HTTP Factories implementation for PHP 8.5. Creates RequestFactoryInterface, ResponseFactoryInterface, StreamFactoryInterface, UriFactoryInterface, ServerRequestFactoryInterface, UploadedFileFactoryInterface. Includes unit tests.
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。
MikeCheng1208/BattleTree☆ 22026年7月22日 更新
Comprehensive Agent2Agent (A2A) JavaScript SDK skill for building A2A-compliant agents and clients. Use when implementing or integrating @a2a-js/sdk, creating A2A servers/clients, using JSON-RPC/REST/gRPC transports, streaming task updates, handling tasks/artifacts, authentication, or push notifications.
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。
MikeCheng1208/BattleTree☆ 22026年7月22日 更新
Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.
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。
sayasaya8039/ZWG_Terminal☆ 22026年6月8日 更新
Apple FoundationModels framework for on-device LLM — text generation, guided generation with @Generable, tool calling, and snapshot streaming in iOS 26+.
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。
sayasaya8039/ZWG_Terminal☆ 22026年6月8日 更新
Java coding standards for Spring Boot services: naming, immutability, Optional usage, streams, exceptions, generics, and project layout.
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。
sayasaya8039/ZWG_Terminal☆ 22026年6月8日 更新
High-throughput event streaming and real-time data ingestion.
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。
MMEHDI0606/ai-agent-foundation-template☆ 22026年5月21日 更新
Azure Event Hubs SDK for Rust. Use for sending and receiving events, streaming data ingestion.
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。
MMEHDI0606/ai-agent-foundation-template☆ 22026年5月21日 更新