生物
钥匙(锁)
计算生物学
基因组测序
进化生物学
基因组
遗传学
数据科学
基因
计算机科学
生态学
作者
David Sims,Ian Sudbery,Nicholas E. Ilott,Andreas Heger,Chris P. Ponting
摘要
Sequencing technologies have placed a wide range of genomic analyses within the capabilities of many laboratories. However, sequencing costs often set limits to the amount of sequences that can be generated and, consequently, the biological outcomes that can be achieved from an experimental design. In this Review, we discuss the issue of sequencing depth in the design of next-generation sequencing experiments. We review current guidelines and precedents on the issue of coverage, as well as their underlying considerations, for four major study designs, which include de novo genome sequencing, genome resequencing, transcriptome sequencing and genomic location analyses (for example, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and chromosome conformation capture (3C)).
科研通智能强力驱动
Strongly Powered by AbleSci AI