Performs Quality Control, Data Normalization, and Batch Effect Correction for 'NanoString nCounter' Data

Provides quality control (QC), normalization, and batch effect correction operations for 'NanoString nCounter' data, Talhouk et al. (2016) . Various metrics are used to determine which samples passed or failed QC. Gene expression should first be normalized to housekeeping genes, before a reference-based approach is used to adjust for batch effects. Raw NanoString data can be imported in the form of Reporter Code Count (RCC) files.


News

nanostringr 0.1.4

  • reduce package dependencies from Imports

  • remove old packages from Suggests

  • performance gains in refMethod()

  • raw parameter in NanoStringQC() now accepts tibbles

nanostringr 0.1.3

  • check for presence of "Positive" and "Negative" genes in NanoStringQC()

  • remove most code lints

  • unit tests for read_rcc() and internal functions check_colnames(), check_genes()

  • fix bug using NanoStringQC() for single sample data

nanostringr 0.1.2

  • sort sample names in HLD and OVD cohorts by numeric order, not lexicographic order

  • tidy up code in HKnorm()

  • use tidy evaluation in NanostringQC()

  • use vapply() over sapply() for input checking functions

nanostringr 0.1.1

  • update citation to link to PLOS paper

nanostringr 0.1.0

  • New submission to CRAN accepted on March 15, 2019

Reference manual

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install.packages("nanostringr")

0.1.4 by Derek Chiu, 7 months ago


https://github.com/OVCARE/nanostringr, https://ovcare.github.io/nanostringr


Report a bug at https://github.com/OVCARE/nanostringr/issues


Browse source code at https://github.com/cran/nanostringr


Authors: Derek Chiu [aut, cre] , Aline Talhouk [aut] , Samuel Leung [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports assertthat, ccaPP, dplyr, epiR, magrittr, purrr, rlang

Suggests covr, knitr, rmarkdown, testthat


See at CRAN