「trace」の検索結果

Use when users need bioinformatics analysis on the NCPGR cluster, especially when converting analysis requests into local software choices, resource plans, and LSF job scripts.

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。

Mark and remove PCR/optical duplicates using samtools fixmate and markdup. Use when preparing alignments for variant calling or when duplicate reads would bias 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。

Audit required bioinformatics command-line tools against Lmod or Environment Modules on Linux HPC clusters, resolve executable and version requirements, and reproducibly deploy missing software through a site-approved EasyBuild, Spack, Bioconda/micromamba, Apptainer, binary, or source-build workflow. Use when Codex must inspect module availability, diagnose a missing or wrong-version bioinformatics tool, install scientific software on Slurm/PBS clusters, publish or validate modulefiles, or produce an auditable and rollback-ready cluster software deployment.

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。

Installs 425 bioinformatics skills covering sequence analysis, RNA-seq, single-cell, variant calling, metagenomics, structural biology, and 56 more categories. Use when setting up bioinformatics capabilities or when a bioinformatics task requires specialized skills not yet installed.

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。

Filter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific reads, removing low-quality alignments, or subsetting to target regions.

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。

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。

Generate pileup data for variant calling using samtools mpileup and pysam. Use when preparing data for variant calling, analyzing per-position read data, or calculating allele frequencies.

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。

Analyzes differential transcript usage (DTU) and isoform switches with functional consequence prediction (NMD via 50nt rule, ORF disruption, protein domain loss/gain, signal peptide changes, IDR alterations, coding-potential shifts). Tools include IsoformSwitchAnalyzeR v2 (auto-selects satuRn for >5 reps else DEXSeq), the manual DRIMSeq -> DEXSeq/satuRn -> stageR DTU pipeline, and fishpond/swish for inferential-uncertainty-aware DTE. Distinguishes DTU from DGE and DTE; integrates external annotators (CPC2, Pfam, SignalP, IUPred2A or DeepTMHMM). Use when investigating how splicing differences alter protein function or trigger NMD-mediated degradation.

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。

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。

Predicts whether a DNA variant alters mRNA splicing using sequence-based deep-learning tools — SpliceAI (10kb context dilated CNN, clinical default), Pangolin (multi-tissue), MMSplice (modular per-region CNN with calibrated ΔPSI), SpliceTransformer/TrASPr (tissue-aware transformers), SpliceVault (empirical 300K-RNA lookup of likely mis-splicing outcomes), CADD-Splice (composite score). Applies the ClinGen SVI 2023 framework for ACMG/AMP variant interpretation (PVS1, PP3, BP4 evidence codes), HGVS splicing nomenclature (c.123+1G>A, c.123-3T>G, r.spl?), extended-window scoring for deep-intronic pseudoexons, tissue-specific predictions, branchpoint variant detection (BPHunter, LaBranchoR), and splice-switching ASO design. Use when interpreting splice impact of clinical variants, prioritizing VUS, identifying deep-intronic pathogenic variants, or designing ASOs.

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。

Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and other alignment formats for phylogenetics and conservation analysis. Use when reading, writing, or converting alignment file formats.

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。

ATAC-seq library quality control -- TSS enrichment, FRiP, fragment-size periodicity, library complexity (NRF/PBC1/PBC2), mitochondrial fraction, and ENCODE 4 thresholds. Use when assessing whether an ATAC-seq library passes ENCODE acceptance criteria, diagnosing transposition artefacts, comparing Omni-ATAC vs standard prep quality, or selecting which replicates to drop before peak calling.

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。

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。

Map nucleosome center positions, occupancy, and fuzziness from ATAC-seq fragment-size patterns using NucleoATAC, ATACseqQC, DANPOS3, or scprinter. Use when characterizing nucleosome organization at promoters and enhancers, calling +1/-1 nucleosomes flanking NFRs, generating V-plots for chromatin structure visualization, or comparing nucleosome positioning between conditions.

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。

Azure Monitor OpenTelemetry Exporter for Java. Export OpenTelemetry traces, metrics, and logs to Azure Monitor/Application Insights.

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。

Reconstruct workflow behind a past coding-agent artifact using local ax sessions/commits/skills/tool traces. Use when asked how X was built.

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。

Read-only consolidated snapshot of an SDD Composy workspace: lifecycle stage, task contracts, trace integrity, loops, fleets, and the next action, without changing any file. Use for 'em que pé está o SDD', 'status do fluxo', 'qual a próxima ação', 'where are we in the workflow'. Do NOT use for git, CI, infrastructure, or other plugins' status, or to change state.

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。

Create or revise the SDD Composy technical specification (tasks/prd-SLUG/techspec.md) from the approved PRD, resolved stories, and mapped codebase, with DEC/RISK and TU/TI/E2E traceability and a human gate. Use when the product contracts are approved and architecture is needed — 'criar a spec técnica', 'techspec do prd-SLUG', 'design the solution for…'. Do NOT use to change product scope, before PRD and stories approval, or for design notes outside SDD.

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。

Deliver a small bounded change inside an initialized SDD Composy workspace through the quick path: at most five implementation files, a registered TASK, TDD, evidence, trace, and a verified verdict, escalating otherwise. Use for a precise objective with no existing task — 'ajuste rápido via SDD', 'quick fix under SDD', 'small change to X in the SDD flow'. Do NOT use for an already registered task (sdd-execute), for architecture, migrations, or destructive work, or in repositories without SDD Composy (other plugins' quick).

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。

Independent, traceable code review of one SDD Composy task in review_required against its approved PRD, stories, TechSpec, evidence, and project rules, with stable findings and severities. Use when a task passed QA and evidence — 'revisar a TASK-003', 'code review da task', 'review this task's diff'. Do NOT use for code review outside an SDD workspace (use the host code review), for QA (sdd-qa), or for verification (sdd-verify).

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。

Analyze product risk and propose traceable QA coverage, priorities, environments, data, and explicit coverage gaps.

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。

Design traceable accessibility checks that combine scanners with observable keyboard, focus, semantic, and assistive-technology behavior.

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。

Execute explicitly authorized tests and record traceable expected, observed, evidence-bound results.

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。

Design traceable Web and browser checks with explicit browser coverage, observed interactions, isolated sessions, and evidence limitations.

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。