Additional file 1: of Matataki: an ultrafast mRNA quantification method for large-scale reanalysis of RNA-Seq data

Supplementary methods (pseudocode and mapping) and figures. (DOCX 1581 kb

Additional file 3: of Matataki: an ultrafast mRNA quantification method for large-scale reanalysis of RNA-Seq data

Table S1. Numbers of indexed k-mer for each transcript. Table S2. List of paralogous genes and number of indexed k-mers. Table S3. List of enriched biological process GO terms in uncovered genes. Table S4. List of enriched molecular function GO terms in uncovered genes. Table S5: Details of the uncovered genes in GENCODE transcripts. (XLSX 3579 kb

Enriched-GO-Terms

The list of all enriched GO terms when SCS = 3, 4 and

Comparison between the conserved coexpression-based modules and those based on coexpression without conservation.

<p>(A) The number of detected gene modules against MR for the coexpression-based method (left 6 bars) and the conservation-based method (right bar). The modules are colored according to whether a module had enriched GO terms. (B) The ratio of enriched gene modules. (C) A box plot of the gene module size distribution.</p

Detected gene modules.

<p>Summary of detected gene modules and representative GO terms when SCS = 4.</p

Detected gene networks (A) Gene networks based on coexpression conservation.

<p>We generated networks with 3,776 genes. The largest gene network contained 2,717 genes. Genes (nodes) were colored when they were a member of the top 20 largest modules with SCS = 4. Gray nodes were parts of some smaller modules, and black nodes were not parts of any modules. We prepared this picture of the network with Cytoscape ([<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132039#pone.0132039.ref031" target="_blank">31</a>]). (B) The largest gene modules with SCS = 3 and the large modules with SCS = 5 are colored. This module has the representative term “immune system process”, but not all of the sub-modules with SCS = 5 have immune-related GO terms, as discussed in the text. (C) The gene network without a turning point. Since some gene networks had high coexpression conservation, no flat region was found. We used 100 instead of a turning point, because turning points cannot be defined for these genes. This network was generated from these highly conserved genes.</p

Example of the correspondence between the conservation-based method modules and the COXPRESdb-based modules.

<p>The three module pairs with the largest numbers of intersecting genes are shown. The list of all similar module pairs is provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132039#pone.0132039.s009" target="_blank">S7 Table</a>.</p

Comparison of Gene Coexpression Profiles and Construction of Conserved Gene Networks to Find Functional Modules

<div><p>Background</p><p>Computational approaches toward gene annotation are a formidable challenge, now that many genome sequences have been determined. Each gene has its own function, but complicated cellular functions are achieved by sets of genes. Therefore, sets of genes with strong functional relationships must be identified. For this purpose, the similarities of gene expression patterns and gene sequences have been separately utilized, although the combined information will provide a better solution.</p><p>Result & Discussion</p><p>We propose a new method to find functional modules, by comparing gene coexpression profiles among species. A coexpression pattern is represented as a list of coexpressed genes with each guide gene. We compared two coexpression lists, one from a human guide gene and the other from a homologous mouse gene, and defined a measure to evaluate the similarity between the lists. Based on this coexpression similarity, we detected the highly conserved genes, and constructed human gene networks with conserved coexpression between human and mouse. Some of the tightly coupled genes (modules) showed clear functional enrichment, such as immune system and cell cycle, indicating that our method could identify functionally related genes without any prior knowledge. We also found a few functional modules without any annotations, which may be good candidates for novel functional modules. All of the comparisons are available at the <a href="http://v1.coxsimdb.info" target="_blank">http://v1.coxsimdb.info</a> web database.</p></div

data-repository

data-repositor

How to use COXSIMdb.

<p><b>(A)</b> First, search for a gene by its symbol or entrez gene ID. <b>(B)</b> Second, select a gene of interest. <b>(C)</b> View of the coexpression conservation results. This view provides a summary of the genes, a list of CC genes, the detected gene modules, and a comparison of coexpression.</p