Primary sequencing data produced by RNA-Seq (raw reads) were subjected to quality control (QC). The information of total reads and mapping ratio reads are shown in Table Table1.1. The sequencing data was filtered with SOAPnuke (v1.5.2) [31] by removing reads containing sequencing adapter; removing reads whose low-quality base ratio (base quality less than or equal to 5) is more than 20%; and removing reads whose unknown base (“N” base) ratio is more than 5%; afterwards, clean reads were obtained and stored in FASTQ format. The clean reads were mapped to the reference genome using HISAT2 (v2.0.4) [32]. After that, Ericscript (v0.5.5) [33] and rMATS (V3.2.5) [34] were used to detect fusion genes and differential splicing genes (DSGs), respectively. Bowtie2 (v2.2.5) was applied to align the clean reads to the gene set [35], a database built by BGI (Beijing Genomic Institute in Shenzhen), in which known and novel, coding and noncoding transcripts were included, then expression level of gene was calculated by RSEM (v1.2.12) [36]. The heatmap was drawn by pheatmap (v1.0.8) according to the gene expression in different samples. Essentially, differential expression analysis was performed using the DESeq2(v1.4.5) with q value ≤ 0.05 [37]. To take insight into the change of phenotype, GO ( and KEGG ( enrichment analysis of annotated different expression gene was performed by Phyper ( based on the hypergeometric test. The significant levels of terms and pathways were corrected by q value with a rigorous threshold (q value ≤0.05) by Bonferroni.

The information of total reads and mapping ratio for control and PIPN groups by RNA-Seq

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