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LPE

Bioc current

Methods for analyzing microarray data using Local Pooled Error (LPE) method

v1.86.0 · software · LGPL

Release Lineage

Entered 1.4 · May 17, 2004

Current · Requires R 4.6

1.0 In 45 of 49 releases 3.23

Description

This LPE library is used to do significance analysis of microarray data with small number of replicates. It uses resampling based FDR adjustment, and gives less conservative results than traditional 'BH' or 'BY' procedures. Data accepted is raw data in txt format from MAS4, MAS5 or dChip. Data can also be supplied after normalization. LPE library is primarily used for analyzing data between two conditions. To use it for paired data, see LPEP library. For using LPE in multiple conditions, use HEM library.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

16 16 exported

Complexity

5.2 avg / 14 max

Call network

16 nodes / 19 edges

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

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Lowest coverage

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

Code

Structure

Lines of code

2,558

Files

40

Compiled share

0%

Has compiled src

No

Language breakdown

R 783 (30.6%)Docs 1,210 (47.3%)Vignettes 565 (22.1%)

API

Exported functions

16

Internal functions

0

Testing & CI

Has tests

No

Test-to-code ratio

0.00

testthat edition

CI present

No

CI type

[]

PR gated

No

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

Unsafe pattern score

0

Dep constraint coverage

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

2.10

System requirements

C++ standard

License

LGPL

License flags

not SPDX, not OSI

History

Versions

45

First release

2004-08-23

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

Dep drift

9

LOC over versions

v1.4: 1,889 LOCv1.5: 1,825 LOCv1.6: 1,825 LOCv1.7: 1,950 LOCv1.8: 1,989 LOCv1.9: 1,989 LOCv2.0: 1,989 LOCv2.1: 1,989 LOCv2.2: 1,989 LOCv2.3: 1,989 LOCv2.4: 1,993 LOCv2.5: 1,993 LOCv2.6: 1,993 LOCv2.7: 1,993 LOCv2.8: 1,993 LOCv2.9: 1,993 LOCv2.10: 1,993 LOCv2.11: 1,993 LOCv2.12: 1,993 LOCv2.13: 1,993 LOCv2.14: 2,558 LOCv3.0: 2,558 LOCv3.1: 2,558 LOCv3.2: 2,558 LOCv3.3: 2,558 LOCv3.4: 2,558 LOCv3.5: 2,558 LOCv3.6: 2,558 LOCv3.7: 2,558 LOCv3.8: 2,558 LOCv3.9: 2,558 LOCv3.10: 2,558 LOCv3.11: 2,558 LOCv3.12: 2,558 LOCv3.13: 2,558 LOCv3.14: 2,558 LOCv3.15: 2,558 LOCv3.16: 2,558 LOCv3.17: 2,558 LOCv3.18: 2,558 LOCv3.19: 2,558 LOCv3.20: 2,558 LOCv3.21: 2,558 LOCv3.22: 2,558 LOCv3.23: 2,558 LOC

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

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
99%
Return-value docs
88%
References docs
100%

Topics

Depended on by (3)

Bioconductor (3)

People

Nitin Jain

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