blase

Bioc current

Bulk Linking Analysis for Single-cell Experiments

v1.2.0 · software · GPL (>= 3)

View on Bioconductor ↗ Source ↗

Release Lineage

Entered 3.22 · Oct 30, 2025

Current · Requires R 4.6

1.0 In 2 of 49 releases 3.23

Description

BLASE is a method for finding where bulk RNA-seq data lies on a single-cell pseudotime trajectory. It uses a fast and understandable approach based on Spearman correlation, with bootstrapping to provide confidence. BLASE can be used to "date" bulk RNA-seq data, annotate cell types in scRNA-seq, and help correct for developmental phenotype differences in bulk RNA-seq experiments.

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

49 15 exported

Complexity

2.7 avg / 10 max

Call network

49 nodes / 43 edges

Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.

Call graph

Open call graph →

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Lowest coverage

Per-function coverage is not measured for this package yet.

Code

Structure

Lines of code

8,001

Files

103

Compiled share

Has compiled src

Language breakdown

R 3,068 (38.3%)Tests 1,243 (15.5%)Docs 2,836 (35.4%)Vignettes 854 (10.7%)

API

Exported functions

Internal functions

Recent export changes

v3.23+3 bulk_name<-, metric, strong_mapping −1 confident_mapping

v3.22+29 genes<-, BlaseData, annotate_sce +26 more

Testing & CI

Has tests

Yes

Test-to-code ratio

0.41

testthat edition

CI present

CI type

[]

PR gated

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

–

Unsafe pattern score

Dep constraint coverage

5.9%

Secret pattern count

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.5.0

System requirements

–

C++ standard

–

License

GPL (>= 3)

License flags

SPDX valid, OSI approved

History

Versions

First release

2025-10-29

Latest release

2026-04-28

Avg cadence

181 days

Cold removal rate

100%

Dep drift

LOC over versions

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.

Documentation

READMEYes · 819 wordsVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 99%
Return-value docs: 100%
References docs: 0%

Topics

Software › ResearchField › Transcriptomics

Software › Technology › SingleCell

Software › Technology › Sequencing

Software › AssayDomain › GeneExpression

Software › AssayDomain › Transcription

Software › Technology › Sequencing › RNASeq

Software › StatisticalMethod › TimeCourse

Software › ResearchField › CellBiology

Software

Software › AssayDomain › CellBasedAssays

People

Andrew McCluskey author maintainer
David A. Gunn author
Toby Kettlewell author
Rhiannon Kundu author
Thomas D. Otto author ths
Adrian M. Smith author

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