生物
染色质
虚假关系
染色质免疫沉淀
芯片排序
DNA
计算生物学
DNA测序
基因组
遗传学
基因
基因表达
计算机科学
染色质重塑
发起人
机器学习
作者
Jinrui Xu,Michelle Kudron,Alec Victorsen,Jiahao Gao,Haneen Ammouri,Fábio C. P. Navarro,Louis Gevirtzman,R Waterston,Kevin P. White,V Reinke,Mark Gerstein
摘要
Abstract Chromatin immunoprecipitation (IP) followed by sequencing (ChIP-seq) is the gold standard to detect transcription-factor (TF) binding sites in the genome. Its success depends on appropriate controls removing systematic biases. The predominantly used controls, i.e. DNA input, correct for uneven sonication, but not for nonspecific interactions of the IP antibody. Another type of controls, ‘mock’ IP, corrects for both of the issues, but is not widely used because it is considered susceptible to technical noise. The tradeoff between the two control types has not been investigated systematically. Therefore, we generated comparable DNA input and mock IP experiments. Because mock IPs contain only nonspecific interactions, the sites predicted from them using DNA input indicate the spurious-site abundance. This abundance is highly correlated with the ‘genomic activity’ (e.g. chromatin openness). In particular, compared to cell lines, complex samples such as whole organisms have more spurious sites—probably because they contain multiple cell types, resulting in more expressed genes and more open chromatin. Consequently, DNA input and mock IP controls performed similarly for cell lines, whereas for complex samples, mock IP substantially reduced the number of spurious sites. However, DNA input is still informative; thus, we developed a simple framework integrating both controls, improving binding site detection.
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