Computational protocol: Integrated Characterization of MicroRNA and mRNA Transcriptome in Papillary Thyroid Carcinoma

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Protocol publication

[…] Preprocessing of miRNA sequencing data was executed in BaseSpace software (Illumina, USA), and FASTQ files were generated. MiRNA Analysis app version 1.0.0 was used for determination of differentially expressed (DE) miRNAs using the workflow described by Cordero et al. (). Briefly, the pipeline includes 3′ end adapter removal using cutadapt (), annotation to miRBase v21 (), mapping using SHRIMP aligner (), and differential analysis of miRNAs using DESeq2 (). In addition, Rank Product statistics were used to detect 3p/5p ratio changes on the same miRNA in two different conditions (). Unsupervised hierarchical clustering and heatmaps were performed and created using Morpheus from Broad Institute (https://software.broadinstitute.org/morpheus/).Pathway enrichment analysis were executed using DIANA-miRPath v3.0 () and significance was determined using Fisher’s Exact Test.For mRNA sequencing, preprocessing of data were conducted on Torrent Server using Torrent Suite v4.4.2 software (Life Technologies, USA) and FASTQ files were generated and then exported for data analysis using CLCBio Genomics Workbench v8.3 (CLC Bio, Denmark). The manufacturer’s analysis pipeline for transcriptome sequencing was used for differential expression of mRNA. Briefly, the pipeline includes removal of 3′ adapter, mapping to reference transcript (hg19) and differential expression analysis using the Empirical analysis of DGE (EDGE) (). Only DE miRNAs or genes with p-value <0.05 and log2-fold change ≤−1.0 or ≥1.0 were subjected to further analysis.Integrated miRNA and mRNA analysis were performed using MAGIA2 (). Log2 normalized reads from the significant DE miRNAs and mRNAs were uploaded into MAGIA2 and positive and negative correlation analyses between miRNAs, transcription factors, and target mRNA were performed. Skip variability filter option was selected because the data uploaded only contain the significant miRNAs or mRNAs. miRNA targets were predicted using DIANA microT () (score threshold at 2.0, top 75% of the predictions distribution) and Spearman correlation coefficient was used as correlations measure (threshold <0.05). In addition, prediction of miRNA-transcription factor was also performed based on mirGen v2.0 () and TransmiR () databases. […]

Pipeline specifications

Software tools BaseSpace, cutadapt, DESeq2, DIANA-miRPath, CLC Assembly Cell, geWorkbench, Magia
Databases miRBase miRGen TransmiR
Organisms Homo sapiens
Diseases Neoplasm Metastasis, Neoplasms, Tuberculosis, Lymph Node