readscount2deseq: Iniitialize a DESeq2 object from raw reads count matrix.
In Tong-Chen/YSX: For Yishengxin Training

Description Usage Arguments Value Examples

Iniitialize a DESeq2 object from raw reads count matrix.

readscount2deseq(
  count_matrix_file,
  sampleFile,
  design,
  covariate = NULL,
  filter = NULL,
  rundeseq = T
)

`count_matrix_file`	A multiple column file with the first column as gene names (must be unique) and other columns as gene expression reads count in related samples. Gene untrt_N61311 untrt_N052611 ... trt_N61311 trt_N052611 ... GeneA 2 3 ... 10 20 ... GeneB 2 3 ... 100 220 ... GeneC 12 33 ... 10 20 ... GeneD 222 301 ... 10 20 ...
`sampleFile`	A file containing at least two columns. The first column is sample name just like the first column of `salmon_file_list`. Other columns are sample attributes. Normally one of sample attributes should contain the group information each sample belongs to. One simple example (conditions represent group information) Samp conditions untrt_N61311 untrt untrt_N052611 untrt untrt_N080611 untrt untrt_N061011 untrt trt_N61311 trt trt_N052611 trt trt_N080611 trt trt_N061011 trt Another example (3rd column meaning samples from two batches) Samp conditions batch untrt_N61311 untrt A untrt_N052611 untrt A untrt_N080611 untrt B untrt_N061011 untrt B trt_N61311 trt A trt_N052611 trt A trt_N080611 trt B trt_N061011 trt B
`design`	A column name from "sampleFile" like "conditions" in example. This will be used as group variable for DE tests. Currently only simple design is allowed. If one wants to model multiple variables, construct one representation of super variable as indicated in https://support.bioconductor.org/p/67600/#67612 may be useful.
`covariate`	Names of columns containing informations maybe covariates like batch effects or other sample info. Multiple covariates should be supplied as a vector.
`filter`	Filter genes with low read counts. Default genes with total reads count lower than half of number of samples will be filtered out. One can give any number here. Normally default is OK. The DESeq2 will ao auto filter too. Check https://www.bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html.
`rundeseq`	Default `TRUE`. The function will perfrom deseq analysis using `DESeq` and return analyzed DESeqDataSet object. If `FALSE`, just return a DESeqDataSet object and one can run `DESeq`on it with more customed parameters.