12864_2019_6360_MOESM7_ESM.xls (52.5 kB)
MOESM7 of Network analysis uncovers putative genes affecting resistance to tick infestation in Braford cattle skin
dataset
posted on 2019-12-20, 06:27 authored by Daniela Moré, Fernando Cardoso, Maurício A. Mudadu, Wilson Malagó-Jr, Claudia Gulias-Gomes, Bruna Sollero, Adriana Ibelli, Luiz Coutinho, Luciana RegitanoAdditional file 7: Table S7. Transcription factors (TFs) prediction for resistant hosts. Network analysis predicted potential TFs underlying the regulation of gene expression, based on the variation of TopDEGs. The output file was manually-curated, and only TFs found in cattle were classified according to their z-score. TopDEGs TFs were also indicated with their respective modulation and statistical significance. Network object name: network object name in MetaBase®; Actual: number of network objects in the activated dataset(s) which interact with the chosen object; n: number of network objects in the activated dataset(s); R: number of network objects in the complete database or background list which interact with the chosen object; N: total number of gene-based objects in the complete database or background list; Expected: mean value for hypergeometric distribution (n*R/N); Ratio: connectivity ratio (Actual/Expected); z-score: ((Actual-Expected)/sqrt(variance)); p-value: probability to have the given value of Actual or higher (or lower for negative z-score); Input IDs: original probe/gene IDs in the activated dataset(s); Signal: variation of gene expression in log2 FC; p-value2: statistical significance in the differential expression analysis. (XLS 52 kb)