selex


  This data set gives the differential abundance of 1600 enzyme variants
  grown under selective (NS) and selective (S) conditions


datasets

A differential abundance analysis for the comparison of
two or more conditions. For example, single-organism and
meta-RNA-seq high-throughput sequencing assays, or of selected
and unselected values from in-vitro sequence selections. Uses a
Dirichlet-multinomial model to infer abundance from counts,
that has been optimized for three or more experimental
replicates. Infers sampling variation and calculates the
expected false discovery rate given the biological and sampling
variation using the Wilcox rank test or Welches t-test
(aldex.ttest) or the glm and Kruskal Wallis tests (aldex.glm).
Reports both P and fdr values calculated by the Benjamini
Hochberg correction.

Greg Gloor

ALDEx2

Analysis of differential abundance taking sample variation into
account

selex function

A dataframe of 1600 features and 14 samples. The first 7 samples are non-selected, the last 7 are selected.

Format

McMurrough et al (2014) PNAS doi:10.1073/pnas.1322352111

Source

This data set gives the differential abundance of 1600 enzyme variants
  grown under selective (NS) and selective (S) conditions

selex: Selection-based differential sequence variant abundance dataset

Description

Usage

Arguments

Format

Source

References