SinProVirP: a signature protein-based tool for accurate and rapid profiling of human gut virome

SinProVirP is a signature protein-based tool developed for genus-level profiling of the human gut virome. To evaluate the performance of viral identification and quantification at the viral VC-level across different tools, we benchmarked SinProVirP, WGVP, and Phanta using simulated metagenomic datasets.

Accuracy dataset: Each dataset consists of 10 million 150-bp reads derived from 100 viral and 100 bacterial genomes, with exponentially decreasing relative abundance and a 9:1 bacterial-to-viral reads ratio. To assess tool performance on datasets with varying viral proportions, we also simulated datasets with 1%, 2%, 5%, 10%, 20%, and 30% viral reads, each with ten replications.

Comprehensiveness dataset: To detect both within-database (within-DB) species and novel species, we aligned 8,424 assembled viral genomes from the human gut, sourced from Lou et al., against the SinProVirP and Phanta databases. This resulted in the identification of 2,361 within-DB species and 198 novel species. We then generated ten simulated datasets for both novel and within-DB species, each containing 150-bp paired-end reads at ten-fold depth from 100 randomly selected species, generated using insilicoseq.

SinProVirP是一款基于特征蛋白开发的工具，用于人类肠道病毒组（human gut virome）的属水平分型分析。为评估不同工具在病毒VC级层面的病毒识别与定量性能，我们采用模拟宏基因组数据集（simulated metagenomic datasets）对SinProVirP、WGVP及Phanta三款工具开展了基准测试。

准确性测试数据集：每套数据集包含源自100个病毒基因组与100个细菌基因组的1000万条150 bp读段，其相对丰度呈指数递减趋势，且细菌读段与病毒读段的比例为9:1。为评估工具在病毒占比各异的数据集上的性能表现，我们还模拟了病毒读段占比分别为1%、2%、5%、10%、20%与30%的数据集，每套数据集均设置10次重复实验。

全面性测试数据集：为同时检测数据库内（within-DB）物种与新物种，我们将源自Lou等人研究的8424条人类肠道组装病毒基因组与SinProVirP及Phanta数据库进行序列比对，最终鉴定出2361个数据库内物种与198个新物种。随后我们针对新物种与数据库内物种分别生成了10套模拟数据集，每套数据集均包含从100个随机挑选的物种中获取的10倍深度的150 bp配对末端读段（paired-end reads），且通过insilicoseq工具生成。

搜集汇总

背景与挑战

背景概述

该数据集围绕SinProVirP工具展开，这是一个基于签名蛋白质的工具，专为人类肠道病毒组的属水平分析设计。它包含准确性数据集，通过模拟宏基因组数据评估工具在不同病毒比例下的性能，以及全面性数据集，用于检测数据库内和新物种，基于大量组装病毒基因组进行模拟。数据集旨在支持工具的性能基准测试和病毒组分析研究，突出其在准确性和快速性方面的优势。