本文へ移動
cccskills
無料GitHub で公開

bioconductor-flowcore

Provides S4 data structures and basic functions to deal with flow cytometry data.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md5.0 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

flowCore

Dependencies & Environment

Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.

  • Version: 2.24.0 · Bioconductor: 3.23 · R: ≥ 4.6
  • Imports: Biobase, BiocGenerics, Rcpp, matrixStats, cytolib, S4Vectors
  • System requirements: GNU make, C++17
  • Install: BiocManager::install("flowCore")

When to Use

  • FCS3.0 Standard Parsing: Reading and interpreting Flow Cytometry Data File Standard Version FCS3.0 files.
  • Segment Extraction: Locating and extracting HEADER, TEXT, DATA, and ANALYSIS segments from flow cytometry data sets.
  • Large File Handling: Processing data sets of 100 megabytes and larger where byte offsets exceed standard limits.
  • Compensation Matrix Retrieval: Extracting the fluorescence compensation matrix ($COMP) applied to the data.

When NOT to Use

  • Automated Cell Clustering: For automated cell clustering, use flowMeans instead because flowCore focuses on file standard specifications and data structures.
  • Probability Binning: For generating multivariate probability distribution fingerprints, use flowFP instead because flowCore only handles the raw file segments.

Data Requirements

  • Input Format: FCS3.0 conformant files.
  • Structure: Must contain HEADER, TEXT, and DATA segments.
  • Storage Mode: List mode data storage or histograms.

Key Parameters

  • $BEGINDATA (required): Byte-offset from the beginning of the data set to the beginning of the DATA segment.
  • $DATATYPE (required): Type of data in the DATA segment (ASCII 'A', integer 'I', single precision floating point 'F', or double precision 'D').
  • $BYTEORD (required): Byte order for the data acquisition computer (e.g., 4,3,2,1 or 1,2,3,4).
  • $COMP (optional): Fluorescence compensation matrix elements stored in row-major order.
  • $PnB (required): Number of bits reserved for parameter number n.
  • $PnR (required): Range for parameter number n.

Best Practices

  • Primary TEXT Segment Placement: Ensure the primary TEXT segment is located entirely within the first 99,999,999 bytes of the data set.
  • ANALYSIS Segment Verification: Check the $BEGINANALYSIS and $ENDANALYSIS keywords to determine if an ANALYSIS segment is present, especially if HEADER offsets are zero.
  • Internationalization: Use the $UNICODE keyword to support multi-byte characters for string type keyword values.
  • Data Integrity: Utilize the cyclic redundancy check (CRC) word placed at the end of each FCS3.0 data set to confirm file integrity after network transfers.

Common Pitfalls

  • Large Data Set Offsets: Data sets exceed the 99,999,999 byte limit, causing standard HEADER offsets to fail. Fix: Substitute '0's in the HEADER and place the true byte offsets in the $BEGINDATA and $ENDDATA keyword values in the TEXT segment.
  • Delimiter Collisions: The delimiter character appears within a keyword or keyword value. Fix: Immediately follow the delimiter with a second identical delimiter character to escape it.
  • Missing Zero Values in Free Format ASCII: Free format ASCII data ($DATATYPE/A/ with $PnB/*/) misinterprets consecutive delimiters. Fix: Explicitly specify zero values with the zero (0) character rather than leaving empty space between delimiters.

Alternatives

  • flowMeans: For downstream non-parametric clustering of the extracted flow cytometry data.
  • flowFP: For fingerprinting and probability binning of the extracted flow cytometry data.

Citations

  • Data File Standards Committee of the International Society for Analytical Cytology (ISAC). FCS version 2.0 can be found in Cytometry 1990;11(3):323-32.

References

<!-- biomate-cta -->

Run this on BioMate

This skill is the knowledge layer — when, why, and how to use flowcore. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.

▶ Open flowcore on BioMate →

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.

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。

bioMate-AI/biomate-bioconductor-kb8042026年6月21日 更新

This tool uses the label-tree function from HyPhy to annotate a phylogenetic tree. It allows users to select a subset of leaves using either a regular expression or a list of sequence names, and then apply a specified label to these selecte

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。

bioMate-AI/biomate-bioconductor-kb8042026年6月21日 更新

This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, En

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。

bioMate-AI/biomate-bioconductor-kb8042026年6月21日 更新

apeglm provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.

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。

bioMate-AI/biomate-bioconductor-kb8042026年6月21日 更新

ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).

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。

bioMate-AI/biomate-bioconductor-kb8042026年6月21日 更新

AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules...) in single-cell RNA-seq data. AUCell uses the "Area Under the Curve" (AUC) to calculate whether a critical subset of the input gene set is enriched with

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。

bioMate-AI/biomate-bioconductor-kb8042026年6月21日 更新

bioMate-AI のスキルをすべて見る

このスキルの問題を報告する