Package: CpmERCCutoff 1.0.0

Kristen Steenbergen

CpmERCCutoff: Calculation of Log2 Counts per Million Cutoff from ERCC Controls

Implementation of the empirical method to derive log2 counts per million (CPM) cutoff to filter out lowly expressed genes using ERCC spike-ins as described in Goll and Bosinger et.al (2022)<doi:10.1101/2022.06.23.497396>. This package utilizes the synthetic mRNA control pairs developed by the External RNA Controls Consortium (ERCC) (ERCC 1 / ERCC 2) that are spiked into sample pairs at known ratios at various absolute abundances. The relationship between the observed and expected fold changes is then used to empirically determine an optimal log2 CPM cutoff for filtering out lowly expressed genes.

Authors:Tyler Grimes [aut], Travis L. Jensen [aut], Kristen Steenbergen [ctb, cre], The Emmes Company LLC [cph]), Johannes B. Goll [aut]

CpmERCCutoff_1.0.0.tar.gz
CpmERCCutoff_1.0.0.zip(r-4.7-any)CpmERCCutoff_1.0.0.zip(r-4.6-any)
CpmERCCutoff_1.0.0.tar.gz(r-4.7-any)CpmERCCutoff_1.0.0.tar.gz(r-4.6-any)
CpmERCCutoff_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CpmERCCutoff/json (API)

# Install 'CpmERCCutoff' in R:
install.packages('CpmERCCutoff', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • exp_input - A data frame of expected ERCC1 and ERCC2 ratios
  • mta_dta - A data frame containing sample-level ERCC meta data
  • obs_input - A data frame of observed spike in ERCC normalized LCPM data

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 scripts 423 downloads 1 exports 0 dependencies

Last updated from:53baa9c143. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK101
source / vignettesOK156
linux-releaseOK106
windows-develOK61
windows-releaseOK60
wasm-releaseOK95

Exports:getLowLcpmCutoff

Dependencies: