cubfits (version 0.1-2)

Yassour2009: Yassour 2009 Yeast Experiment Dataset

Description

Experiments and data are obtained from Yassour et. al. (2009).

Usage

yassour

Format

A data.frame contains 6303 rows and 5 columns: ORF is for gene names in character, and YPD0.1, YPD0.2, YPD15.1, and YPD15.2 are gene expressions in positive double corresponding to 4 controlled Yeast experiments.

Source

http://www.pnas.org/content/early/2009/02/10/0812841106 http://www.pnas.org/content/vol0/issue2009/images/data/0812841106/DCSupplemental/SD3.xls Yassour M, Kaplan T, Fraser HB, Levin JZ, Pfiffner J, Adiconis X, Schroth G, Luo S, Khrebtukova I, Gnirke A, Nusbaum C, Thompson DA, Friedman N, Regev A. (2009) ``Ab initio construction of a eukaryotic transcriptome by massively parallel mRNA sequencing.'' Proc Natl Acad Sci USA 106(9):3264-9. [PMID:19208812]

Details

The original data are available as the URL of the section of Source next. As the section of Examples next, data are selected from SD3.xls and reordered by ORF.

For further analysis, the Examples section also provides how to convert them to phi.Obs values either in geometric means or individually.

References

Wallace E.W.J., Airoldi E.M., and Drummond D.A. ``Estimating Selection on Synonymous Codon Usage from Noisy Experimental Data'' Mol Biol Evol (2013) 30(6):1438--1453.

Examples

## Not run: 
# ### SD3.xls is available from the URL provided in the References.
# da <- read.table("SD3.xls", header = TRUE, sep = "\t", quote = "",
#                  stringsAsFactors = FALSE)
# 
# ### Select ORF, YPD0.1, YPD0.2, YPD15.1, YPD15.2.
# da <- da[, c(1, 8, 9, 10, 11)]
# colnames(da) <- c("ORF", "YPD0.1", "YPD0.2", "YPD15.1", "YPD15.2")
# 
# ### Drop inappropriate values (NaN, NA, Inf, -Inf, and 0).
# tmp <- da[, 2:5]
# id.tmp <- rowSums(is.finite(as.matrix(tmp)) & tmp != 0) >= 3
# tmp <- da[id.tmp, 1:5]
# yassour <- tmp[order(tmp$ORF),]    # cubfits::yassour
# 
# ### Get geometric mean of phi.Obs and scaling similar to Wallace (2013).
# GM <- apply(yassour[, -1], 1, function(x) exp(mean(log(x[x != 0]))))
# phi.Obs <- GM / sum(GM) * 15000
# 
# ### Get individual of phi.Obs.
# GM <- apply(yassour[, -1], 1, function(x) exp(mean(log(x[x != 0]))))
# phi.Obs.all <- yassour[, -1] / sum(GM) * 15000
# phi.Obs.all[phi.Obs.all == 0] <- NA
# ## End(Not run)