Additional file 1 of GFICLEE: ultrafast tree-based phylogenetic profile method inferring gene function at the genomic-wide level
Creators: name: Fang, Yang
name: Li, Menglong
name: Li, Xufeng
name: Yang, Yi
Publisher: name: figshare
Year: 2021
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 1: Supplementary Fig. S1. The performance of different classifies methods. The performance of naïve Bayesian method compares with Random Forest, Support Vector Machines and Nearest Neighbors classify methods. In the figure, NB: naïve Bayesian, SVC: Support Vector Machines classification, NC: Nearest Neighbors classification and RF: Random Forest classification. Supplementary Fig. S2. The common ancestor of genes in different databases. a) The common ancestor of genes in the human pathway with CORUM database. b) The common ancestor of genes in the human pathway with GO database. c) The common ancestor of genes in the human pathway with KEGG database. Supplementary Fig. S3. The comparison of genes functions appeared in later or earlier than input genes. a) Setting the search node is same with input genes node (1), Setting the search node later and earlier than input gene node (2), Setting the search node later than input genes node (3), Setting the search node earlier than input genes node (4). b) The performance of setting the different search gain node. Supplementary Fig. S4. The performance of GFICLEE compares with existing approaches by different genomes. a) The A. thaliana metabolic and signaling pathways. b) The T. brucei metabolic and signaling pathways. Supplementary Fig. S5. The computational time of three different databases. The test used the human genome with the GO database that contains 911 pathways, CORUM contains 1056 pathways and KEGG with 116 pathways. The test parallel running with 10 cores for CLIME and GFILEE software, respectively. Supplementary Fig. S6. The HGT events occurred in the human phylogenetic profile. a) The HGT events occurred in each subgroup. b) The example of the revised HGT profile. Supplementary Fig. S7. The performance of GFICLEE by phylogenetic profile compares with the revised phylogenetic profile in three databases. Supplementary Fig. S8. The performance of GFICLEE compares with CLIME by the phylogenetic profile that removes suspected HGT genes. Supplementary Fig. S9. GFICLEE algorithm corresponding four scenarios for the evolution of states of characters gene X and Y. a) The replicated co-distributions contain single and continuous loss events. b) Darwin’s scenario only contains continuous loss events. c) and d) The scenarios of Replicated bursts and Unreplicated burst, respectively. Supplementary Fig. S10. The performance of GFICLEE with different software reconstruct species tree and random topology tree. FastTree, IQ-TREE, MEGA_ML and PhyML are maximum likelihood method reconstruct species tree. The MEGA_ML is the Neighbor-Joining method reconstruct species tree. Supplementary Fig. S11. The performance of GFICLEE with different threshold generate phylogenetic matrix. The various BLASTP threshold to (E-value &lt; 10–2, E-value &lt; 10–3, E-value &lt; 10–4 and E-value &lt; 10–5) generate ortholog matrix and test the performance of GFICLEE. Supplementary Fig. S12. The taxon sampling effect on the performance of GFICLEE. We extract species from each phylum classification at a ratio of 20, 40, 60, and 80% to generate subtrees. The contains each phylum only also extracted for the performance test.