Computational protocol: Transcriptome analysis of pecan seeds at different developing stages and identification of key genes involved in lipid metabolism

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Protocol publication

[…] Low-quality reads with Phred scores < 20 were trimmed using Fastq_clean [], and the data quality was assessed using FASTQC []. The filtered reads were assembled using Trinity (version 2.0.6) with default parameters [, ]. The paired-end reads from each library were mapped to de novo assemblies using bowtie (version 1.1.1) []. The transcript abundance was estimated using Corset (version 1.03) []. The count data generated from Corset were processed using the edgeR package []. Transcripts with less than one count per million reads (CPM) for at least three libraries were removed, and the remaining data were used for the next analysis. A matrix was constructed using the single factor style. Effective library sizes were determined using the trimmed mean of M values (TMM) normalization method. The common dispersion and tag wise dispersion were estimated using the quantile-adjusted conditional maximum likelihood (qCML) method. The exact test was performed to compute the expression of genes between the treatment and mock groups. Raw P values were adjusted for multiple testing using a false discovery rate (FDR) []. Genes with an FDR of less than 0.05 and fold-changes greater than 2 were regarded as DEGs. GO analysis of the DEGs and pathways were processed using DAVID []. Hierarchical clustering of the genes was performed using the pheatmap R package (version 1.0.7) []. […]

Pipeline specifications

Software tools Fastq_clean, FastQC, Trinity, Bowtie, Corset, edgeR, DAVID, PHeatmaps
Application Transcriptome data visualization
Organisms Caenorhabditis elegans
Chemicals Fatty Acids