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.tar.gz(r-4.5-noble)CpmERCCutoff_1.0.0.tar.gz(r-4.4-noble)
CpmERCCutoff_1.0.0.tgz(r-4.4-emscripten)CpmERCCutoff_1.0.0.tgz(r-4.3-emscripten)
CpmERCCutoff.pdf |CpmERCCutoff.html✨
CpmERCCutoff/json (API)

# Install 'CpmERCCutoff' in R:
install.packages('CpmERCCutoff', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

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

1.00 score 5 scripts 665 downloads 1 exports 0 dependencies

Last updated 2 years agofrom:53baa9c143. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 11 2024
R-4.5-linuxOKNov 11 2024

Exports:getLowLcpmCutoff

Dependencies: