Paschold2012: Paschold et. al. (2012) data
In jarad/Paschold2012: Provides data from Paschold et. al. (2012)

Description Usage Format Details References Examples

A data set containing RNAseq counts for 4 replicates of each of 4 genotypes: B73, Mo17, B73xMo17, and Mo17xB73. The total count is provided as well as the count attributed to the B73 and Mo17 genomes based on comparison to the reference B73 genome and known single nucleotide polymorphisms between the B73 and Mo17 genomes.

1	Paschold2012

A data.frame with 634,496 rows and 6 variables:

GeneID: gene identifier
genotype: B73, Mo17, B73xMo17, or Mo17xB73
replicate: 1-4, the replicate sample for that genotype
flow_cell: 1-2, two flow cells were used in the experiment, replicates 1 and 2 are on flow cell 1 and replicates 3 and 4 are on flow cell 2
B73: read count attributed to B73 genome
Mo17: read count attributed to Mo17 genome
total: read count for that gene

Provides RNA sequencing experiment used in Paschold et. al. (2012). The data consist of RNAseq counts for 39,656 "genes" for 4 replicates for two parental varieties of maize and their two crosses: Mo17, B73, Mo17xB73, and B73xMo17. In addition to the count for each replicate-sample combination, the data also contain the counts by parental genotype.

The data have been lengthed so that each gene-sample combination is in a unique row with B73 and Mo17 indicating the count for each gene attributed to B73 and Mo17 genome and the total column indicating the total count for that gene. As some genes can not be attributed to a particular genome, the sum of the B73 and Mo17 columns should be less than or equal to the total column. Non-zero counts in the B73 column for the Mo17 genotype (and the reverse) indicate false positive reads.

Paschold, A., Jia, Y., Marcon, C., Lund, S., Larson, N.B., Yeh, C.T., Ossowski, S., Lanz, C., Nettleton, D., Schnable, P.S. and Hochholdinger, F., 2012. Complementation contributes to transcriptome complexity in maize (Zea mays L.) hybrids relative to their inbred parents. Genome research, 22(12), pp.2445-2454.

## Not run: 

# Reshape to wide format
library(dplyr)
wide = Paschold2012 %>%
  mutate(genotype_replicate = paste(genotype,replicate,sep="_")) %>%
    select(GeneID, genotype_replicate, total) %>%
      tidyr::spread(genotype_replicate, total)
dim(wide)

# Differential expression data set
differential_expression = Paschold2012 %>%
  filter(genotype %in% c("B73","Mo17")) %>%
  rename(count=total) %>%
  select(GeneID, genotype, replicate, count)

# Heterosis data set
heterosis = Paschold2012 %>%
  select(-B73, -Mo17)

# Allele specific expression data set
allele = Paschold2012 %>%
  select(-total) %>%
  filter(genotype %in% c("B73xMo17","Mo17xB73"))

## End(Not run)