Mapinsights : advanced quality assessment for high-throughput sequencing data

Terabyte scale data generated on today's fast and cheap high-throughput sequencing technology often came with random errors and unwanted biases.It is very crucial to detect these errors and biases which might have an effect on downstream analysis. Several attempts were made in this regard mainly focusing on standard quality-control (QC) metrics such as GC content, base composition, mapping quality etc but none of these algorithms put systematic attention on sequence read mismatches with respect to reference genome in greater depth. We have developed Mapinsights, a command-line tool that perform quality assesment of aligned data.

基于当今快速且低成本的高通量测序技术生成的TB级数据，通常伴随随机错误与非预期偏差。检测这些可能对下游分析造成影响的错误与偏差，至关重要。针对该问题已有多项研究尝试，主要聚焦于GC含量、碱基组成、比对质量等标准质量控制（QC）指标，但现有算法均未对测序读段与参考基因组的错配情况进行深入系统的关注。我们开发了Mapinsights这一款命令行工具，用于对比对后的数据开展质量评估。