Computational protocol: The importance of tissue specificity for RNA-seq: highlighting the errors of composite structure extractions

Similar protocols

Protocol publication

[…] Low quality bases and adapter contamination were removed with the fastx toolkit and the cutadapt software packages []. Tophat (v2.04) was used for aligning reads to the Apis mellifera genome [] (v4, the most recent officially published version). HTSeq was used for quantifying the number of reads mapping to each gene. NOISEQ, EdgeR and DESeq were used to determine differential expression [,,]. For NOISeq, RPKM normalization was used along with a 0.8 p cutoff (the recommended cut-off level). For EdgeR and DESeq, an adjusted p value (FDR) < 0.05 was used to call differentially expressed genes. All analyses made use of 2 biological samples and 12 million quality controlled paired end reads. Expression levels within biological replicates for the same tissue were highly correlated (mean: 98.3%, range 97.1% -99.6%). […]

Pipeline specifications

Software tools FASTX-Toolkit, cutadapt, TopHat, HTSeq, NOISeq, edgeR, DESeq
Application RNA-seq analysis
Organisms Apis mellifera