Parses microscopy channel and marker names from KINTSUGI metadata files using automatic format detection.
This skill provides a robust framework for parsing microscopy channel names from CHANNELNAMES.txt files, a critical step in bio-imaging pipelines like KINTSUGI. It automatically detects and processes multiple file formats, including simple CODEX-style lists, cycle-prefixed lines, tab-separated values, and CSVs. By utilizing intelligent regex patterns, it can extract cycle numbers directly from DAPI markers and handle common real-world data issues such as case-insensitive naming, varied whitespace, and comment-heavy files, ensuring accurate data labeling for downstream image analysis.
主要功能
01Support for multiple filename conventions including channelnames.txt and markers.txt
02Regex-based cycle extraction from DAPI marker patterns (e.g., DAPI-01, DAPI_02)
03Configurable parameters for custom channel counts per microscopy cycle
040 GitHub stars
05Automatic format detection for Simple List, CSV, TSV, and Cycle-Prefixed formats
06Robust error handling with automatic comment stripping and missing file fallbacks
使用场景
01Normalizing channel labeling across different CODEX and microscopy system outputs
02Automating metadata ingestion for bio-imaging and spatial proteomics pipelines
03Validating and cleaning marker lists before high-throughput image processing
