title: SAMstrt: statistical test for differential expression in single-cell transcriptome with spike-in normalization.
abstract: BACKGROUND
  Recent transcriptome studies have revealed that total transcript numbers vary by cell type and condition; therefore, the statistical assumptions for single-cell transcriptome studies must be revisited. SAMstrt is an extension code for SAMseq, which is a statistical method for differential expression, to enable spike-in normalization and statistical testing based on the estimated absolute number of transcripts per cell for single-cell RNA-seq methods.
  
  
  METHODS
  SAMstrt is implemented on R and available in github (https://github.com/shka/R-SAMstrt).
  
  
  BACKGROUND
  shintaro.katayama@ki.se
authors.affiliation: Department of Biosciences and Nutrition, Karolinska Institutet, 141 83 Huddinge, Sweden, Science for Life Laboratory, Karolinska Institutet Science Park, 171 21 Solna, Sweden and Department of Medical Biochemistry and Biophysics, Karolinska Institutet, 171 77 Stockholm, Sweden.
authors.forename: Shintaro
authors.initials: S
authors.lastname: Katayama
authors.forename: Virpi
authors.initials: V
authors.lastname: Töhönen
authors.forename: Sten
authors.initials: S
authors.lastname: Linnarsson
authors.forename: Juha
authors.initials: J
authors.lastname: Kere
mesh_terms: D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D017423:Sequence Analysis, RNA / Q000379:methods*; D059010:Single-Cell Analysis