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Table 4 Bioinformatics pipelines and gene models used for RNA-Seq data analysis

From: An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

Data set Pipeline Aligner Counting and normalization Reference genome Gene annotation Mapping approach
SEQC NB P2 Novo align v2.08.01 Global scaling to RPM UCSC hg19 Human RefSeq RNA v51 ID mapping
NCTR rat toxicogenomics [20] P2 Novo align v2.08.01 Global scaling to RPM UCSC rn4 Rat RefSeq RNA v52 Location mapping
SEQC main [16] P2 Novo align v1.7.01 Global scaling to RPM UCSC hg19 Human RefSeq RNA v51 Location mapping
SEQC rat toxicogenomics [22] P1 Magic Magic index RGSC v3.4 Ace View 2008 gene models ID mapping
  P2 Novo align v2.08.01 Global scaling to RPM UCSC rn4 Rat RefSeq RNA v52 ID mapping
  P3 Bwa 0.5.9-r16 Samtools 0.1.13   Rat RefSeq RNA v50 ID mapping
  P4 To phat HTSeq-count 0.53p3 UCSC rn4 Rat RefSeq RNA v50 ID mapping
  P5 Bowtie v0.12.7 RSEM v1.1.18 Ensemble rat genome 66 Ensemble genes build 66 Location mapping
  P6 To phat 2.0 Cufflinks + Cuffdiff UCSC rn4 Cufflinks de novo assembly Location mapping
TCGA AML [17]   Bwa 0.5.7 In-house program hg18 + exon junction Ensembl v59 ID mapping