De novo transcriptome assembly for Heterosigma akashiwo Hak10

Raw reads were pre-processed by removing the adaptors and low-quality reads using BBMap. The filtered reads were normalized for depth based on kmer counts using BBNorm function. De novo transcriptomes were generated using both Trinity and velvet-oases. CD-HIT-EST was used to merge the resulting two de novo transcriptomes and reduce the transcript redundancy to 90% similarity and unique genes were predicted using transdecoder. Raw reads can be found in GenBank PRJNA1072663.本研究使用BBMap工具对原始测序读段（Raw reads）进行预处理，去除其中的接头序列与低质量读段；基于k-mer计数，通过BBNorm工具对过滤后的读段完成测序深度标准化处理。分别采用Trinity与Velvet-Oases（velvet-oases）流程构建从头转录组（De novo transcriptomes），随后使用CD-HIT-EST工具合并两套从头转录组，并将转录本冗余度降至90%相似度阈值；同时通过TransDecoder预测得到唯一基因。原始测序读段可于GenBank数据库的PRJNA1072663登录号下获取。