Skip to content

HIVcDNAvantWout03

Bioc current

T cell line infections with HIV-1 LAI (BRU)

v1.52.0 · experiment · GPL (>= 2)

Release Lineage

Entered 2.13 · Oct 15, 2013

Current · Requires R 4.6

1.0 In 26 of 49 releases 3.23

Description

The expression levels of approximately 4600 cellular RNA transcripts were assessed in CD4+ T cell lines at different times after infection with HIV-1BRU using DNA microarrays. This data corresponds to the first block of a 12 block array image (001030_08_1.GEL) in the first data set (2000095918 A) in the first experiment (CEM LAI vs HI-LAI 24hr). There are two data sets, which are part of a dye-swap experiment with replicates, representing the Cy3 (green) absorption intensities for channel 1 (hiv1raw) and the Cy5 (red) absorption intensities for channel 2 (hiv2raw).

Code intelligence has not been computed for this package yet.

Code

Structure

Lines of code

95

Files

11

Compiled share

0%

Has compiled src

No

Language breakdown

Docs 95 (100%)

API

Exported functions

0

Internal functions

0

Testing & CI

Has tests

No

Test-to-code ratio

testthat edition

CI present

No

CI type

[]

PR gated

No

Docs

Roxygen coverage

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

Unsafe pattern score

0

Dep constraint coverage

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

System requirements

C++ standard

License

GPL (>= 2)

License flags

SPDX valid, OSI approved

History

Versions

26

First release

2013-12-13

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

Dep drift

0

LOC over versions

v2.13: 95 LOCv2.14: 95 LOCv3.0: 95 LOCv3.1: 95 LOCv3.2: 95 LOCv3.3: 95 LOCv3.4: 95 LOCv3.5: 95 LOCv3.6: 95 LOCv3.7: 95 LOCv3.8: 95 LOCv3.9: 95 LOCv3.10: 95 LOCv3.11: 95 LOCv3.12: 95 LOCv3.13: 95 LOCv3.14: 95 LOCv3.15: 95 LOCv3.16: 95 LOCv3.17: 95 LOCv3.18: 95 LOCv3.19: 95 LOCv3.20: 95 LOCv3.21: 95 LOCv3.22: 95 LOCv3.23: 95 LOC

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

Topics

People

Chris Fraley

Report a problem with this page →