Effects of transcriptional noise on estimates of gene and transcript expression in RNA sequencing experiments.
Effects of transcriptional noise on estimates of gene and transcript expression in RNA sequencing experiments.
复制标题
RNA测序实验中转录噪音对基因和转录本表达估计的影响。
DOI：
10.1101/gr.266213.120
复制
发表时间：
2021-03
期刊：
影响因子：
7
通讯作者：
Pertea M
中科院分区：
文献类型：
--
作者：
Varabyou A;Salzberg SL;Pertea M
RNA测序被广泛用于测量广泛范围的动物和植物组织和条件下的基因表达。大多数基因表达分析的计算方法的研究使用模拟数据来评估这些方法的准确性。这些模拟通常包括从不同表达水平的已知基因产生的读数。到目前为止，模拟还没有包括来自嘈杂转录本的读数，这可能包括错误的转录、错误的剪接和其他影响活细胞转录的过程。在这里，我们研究了现实量的转录噪音的能力领先的计算方法组装和量化的基因和转录在RNA测序实验的影响。我们发现，噪声的列入导致这些程序的能力，以测量表达的系统性错误，包括系统低估的转录丰度水平和大量增加的假阳性基因和转录本。我们的研究结果还表明，无干扰的计算方法有时无法检测到相对低水平表达的转录本。
RNA sequencing is widely used to measure gene expression across a vast range of animal and plant tissues and conditions. Most studies of computational methods for gene expression analysis use simulated data to evaluate the accuracy of these methods. These simulations typically include reads generated from known genes at varying levels of expression. Until now, simulations did not include reads from noisy transcripts, which might include erroneous transcription, erroneous splicing, and other processes that affect transcription in living cells. Here we examine the effects of realistic amounts of transcriptional noise on the ability of leading computational methods to assemble and quantify the genes and transcripts in an RNA sequencing experiment. We show that the inclusion of noise leads to systematic errors in the ability of these programs to measure expression, including systematic underestimates of transcript abundance levels and large increases in the number of false-positive genes and transcripts. Our results also suggest that alignment-free computational methods sometimes fail to detect transcripts expressed at relatively low levels.
登录
查看更多内容
影响因子：
9.8
作者：
van Bakel H;Nislow C;Blencowe BJ;Hughes TR
通讯作者：
Hughes TR
影响因子：
4.5
作者：
Pickrell JK;Pai AA;Gilad Y;Pritchard JK
通讯作者：
Pritchard JK
影响因子：
46.9
作者：
Patro, Rob;Mount, Stephen M.;Kingsford, Carl
通讯作者：
Kingsford, Carl
影响因子：
46.9
作者：
Trapnell C;Williams BA;Pertea G;Mortazavi A;Kwan G;van Baren MJ;Salzberg SL;Wold BJ;Pachter L
通讯作者：
Pachter L
影响因子：
12.3
作者：
Maretty L;Sibbesen JA;Krogh A
通讯作者：
Krogh A