'quality filtering' 검색 결과

Review code for bugs, logic errors, security vulnerabilities, code quality issues, and adherence to project conventions, using confidence-based filtering to report only high-priority issues that truly matter. Use this skill when reviewing a small set of changes locally (such as unstaged diff), when dispatched as a sub-task during feature-dev quality review, or when the user wants a critique of a specific file or function.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

DepMap CRISPR gene effect (Chronos) analysis: sign convention for essentiality, per-gene NaN-safe Spearman correlation, data loading/alignment. For general NaN-safe correlation see nan-safe-correlation; for quality filtering see degenerate-input-filtering.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Screen US stocks for high-quality dividend opportunities combining value characteristics (P/E ratio under 20, P/B ratio under 2), attractive yields (3% or higher), and consistent growth (dividend/revenue/EPS trending up over 3 years). Supports two-stage screening using FINVIZ Elite API for efficient pre-filtering followed by FMP API for detailed analysis. Use when user requests dividend stock screening, income portfolio ideas, or quality value stocks with strong fundamentals.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Download media (images/videos/GIFs/audio) from Twitter/X using gallery-dl. Supports single tweet URLs, user timelines, date filtering, post count limiting, retweet filtering, video quality selection, and various media types. Use when users want to download media from Twitter/X accounts with proxy support (HTTP/SOCKS4/SOCKS5) and cookie authentication. Supports downloading tweet text with links alongside media.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

NeMo Curator로 LLM 학습 데이터의 중복과 저품질 내용을 제거하고 개인정보를 삭제하거나 대체합니다. 처리 흐름 구성과 이미지, 영상, 음성 정리도 다룹니다.

• 웹 수집 문장을 학습용으로 정리합니다
• 완전 일치, 유사, 의미 기반 중복을 제거합니다
• 텍스트의 개인정보를 삭제하거나 대체합니다

Read, query, filter, and write genomic files with pysam in Python. Extract regions, summarize variants, and count aligned bases while handling coordinate conventions, file indexes, headers, and the reference sequences needed to decode CRAM files.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Inspect genomic file formats, headers, and indexes
• Filter alignment records by quality and flags
• Summarize variants and genotypes in a genomic region

Design hybrid search on AlloyDB by combining meaning-based search, keywords, and SQL filters. Turn requirements into architecture diagrams, database setup scripts, deployment guidance, and validation plans for search applications on Google Cloud.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing product search with meaning-based matching and attribute filters
• Planning result reranking and AI quality checks
• Preparing AlloyDB and Cloud Run deployment guidance

Create or improve unit tests for Apache ShardingSphere classes. Cover the target class’s behavior and affected branches, verify explicitly requested coverage goals, and consolidate suitable scenarios into parameterized tests, which run the same checks with different inputs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add missing unit tests for a target class
• Verify an explicitly requested coverage target
• Consolidate suitable tests with different input data

All-in-one read preprocessing with fastp including adapter trimming, quality filtering, deduplication, base correction, and HTML report generation. Use when preprocessing Illumina data and wanting a single fast tool instead of separate Cutadapt, Trimmomatic, and FastQC steps.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Amplicon sequence variant (ASV) inference from 16S rRNA or ITS amplicon sequencing using DADA2. Covers quality filtering, error learning, denoising, and chimera removal. Use when processing demultiplexed amplicon FASTQ files to generate an ASV table for downstream analysis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Preprocesses cell-free DNA sequencing data including adapter trimming, alignment optimized for short fragments, and UMI-aware duplicate removal using fgbio. Applies cfDNA-specific quality thresholds and fragment length filtering. Use when processing plasma cfDNA sequencing data before downstream analysis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Convert raw Nanopore signal data (FAST5/POD5) to nucleotide sequences using Dorado basecaller. Covers model selection, GPU acceleration, modified base detection, and quality filtering. Use when processing raw Nanopore data before alignment. Guppy is deprecated; use Dorado for all new analyses.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when building a weighted gene co-expression network from a bulk expression matrix and a sample group file, filtering variable genes by MAD, identifying co-expression modules with WGCNA, correlating modules with traits, and exporting module-level plots and gene tables. NOT for single-cell RNA-seq, differential expression testing, methylation analysis, or datasets that are too small for WGCNA after quality control.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Cross-encoder reranking and MMR diversity filtering for improved retrieval quality

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Calculates tumor mutational burden from WES/WGS/panel data with Friends of Cancer Research harmonization equations, per-assay calibration (FDA 10/Mb = 7.8 TSO500 = 8.4 OncomineTML), synonymous/indel/germline filtering, hypermutator tiering, blood TMB, and integration with HLA-LOH and neoantigen quality (Luksza 2017 fitness). Use when assessing ICI eligibility under tumor-specific cutoffs (McGrail 2021), comparing tissue vs bTMB, or auditing TMB-H reporting against ESMO 2024 and FDA pembrolizumab pan-tumor 2020.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Load this first for any task involving images, pictures, photos, scans, frames, volumes, or visual data — including reading, writing, filtering, enhancing, denoising, sharpening, deblurring, thresholding, segmenting, masking, detecting, finding or counting objects, removing backgrounds, measuring, comparing, registering, stitching, aligning, cropping, resizing, transforming, or analyzing. Use for image I/O (TIFF, PNG, JPEG, RAW, HDR), histograms, edge detection, color processing, morphology, geometric transforms, deep learning for images, quality assessment, and 3-D volume processing. Also triggers when users describe image problems (dark, noisy, blurry, low contrast, uneven lighting, hazy, color cast) or data exploration tasks (folder of images, characterize data, understand format). Handles microscopy (cells, particles) and general scientific imaging. Routes to sibling skills for medical imaging (DICOM, NIfTI), hyperspectral data, and visual inspection.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

This package implements sampling, iteration, and input of FASTQ files. The package includes functions for filtering and trimming reads, and for generating a quality assessment report. Data are represented as DNAStringSet-derived objects, an

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

CLI for VCF/BCF: filter, merge, annotate, query, normalize, compute stats. Core post-variant-calling: quality filtering, multi-sample merging, rsID annotation, genotype extraction. Samtools companion in HTSlib. Use GATK for complex indel realignment during calling; use VCFtools for population genetics stats.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.