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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