The BaMM web server for de-novo motif discovery and regulatory sequence analysis.

The BaMM web server for de-novo motif discovery and regulatory sequence analysis.
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DOI:
10.1093/nar/gky431
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发表时间:
2018-07-02
影响因子:
14.9
通讯作者:
Söding J
Söding J
中科院分区:
生物学2区
文献类型:
--
作者:
Kiesel A;Roth C;Ge W;Wess M;Meier M;Söding J

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BaMM web服务器提供四种工具:(i)在一组核苷酸序列中重新发现富集的基序,(ii)扫描一组具有基序的核苷酸序列以查找基序的出现,(iii)在我们的BaMM数据库中搜索输入基序,其中包含来自GTRD ChIP-seq数据库的bb101000个转录因子的基序,以及(iv)浏览和关键词搜索基序数据库。与大多数其他服务器相比,我们不是通过位置权重矩阵(PWMs)而是通过4阶贝叶斯马尔可夫模型(BaMMs)来表示序列基序,我们之前表明,在ROC分析中,该模型比PWMs或一阶模型表现得更好。为了解决P值和e值作为motif质量度量的不足,我们引入了AvRec分数,即TP-to-FP比率在1到100之间的平均召回率。BaMM服务器可以在https://bammmotif.mpibpc.mpg.de上免费访问,无需注册。
The BaMM web server offers four tools: (i) de-novo discovery of enriched motifs in a set of nucleotide sequences, (ii) scanning a set of nucleotide sequences with motifs to find motif occurrences, (iii) searching with an input motif for similar motifs in our BaMM database with motifs for >1000 transcription factors, trained from the GTRD ChIP-seq database and (iv) browsing and keyword searching the motif database. In contrast to most other servers, we represent sequence motifs not by position weight matrices (PWMs) but by Bayesian Markov Models (BaMMs) of order 4, which we showed previously to perform substantially better in ROC analyses than PWMs or first order models. To address the inadequacy of P- and E-values as measures of motif quality, we introduce the AvRec score, the average recall over the TP-to-FP ratio between 1 and 100. The BaMM server is freely accessible without registration at https://bammmotif.mpibpc.mpg.de.
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