Yassour2009 {cubfits} | R Documentation

## 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.

### 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.

### 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]

### 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)

[Package cubfits version 0.1-3 Index]