Resultado de búsqueda
Hace 5 días · Cluster and Network Analysis Methods. 2 minute read. RNA-Seq Workflow. Read quality assessment, filtering and trimming; Map reads against reference genome; Perform read counting for required ranges (e.g. exonic gene ranges) Normalization of read counts; Identification of differentially expressed genes (DEGs) Clustering of gene ...
Hace 2 días · Next, to identify clusters of tightly connected genes within the network, we performed Markov clustering analysis followed by enrichment analysis of the genes in the clusters. Three of the clusters showed enrichment for pathways related to ribosome biogenesis, RNA processing and translation: clusters 1, 3, and 4 (Fig. 6 ).
Hace 4 días · Using short chain fatty acids as a targeted response, we identified genetic features, consisting of carbohydrate active enzymes, transcription factors and sugar transporters, from metagenomic sequencing of in vitro fermentations for three prebiotic substrates: xylooligosacharides, fructooligosacharides, and inulin.
ConsensusClusterPlus implements the Consensus Clustering algorithm of Monti, et al (2003) and extends this method with new functionality and visualizations. Its utility is to provide quantitative stability evidence for determing a cluster count and cluster membership in an unsupervised analysis.
Hace 22 horas · Here we performed a phenotypic CRISPR–Cas9 scan targeting 17,065 genes in ... which sought to cluster genes with similar ... K. et al. Target-enriched nanopore sequencing and de novo assembly ...
Hace 3 días · DGE analysis using DESeq2. The standard workflow for DGE analysis involves the following steps. RNA-seq with a sequencing depth of 10-30 M reads per library (at least 3 biological replicates per sample) aligning or mapping the quality-filtered sequenced reads to respective genome (e.g. HISAT2 or STAR). You can read my article on how to map RNA ...
Hace 4 días · The identification of orthologous genes in an increasing number of fully sequenced genomes is a challenging issue in recent genome science. Here we present KEGG OC (http://www.genome.jp/tools/oc/), a novel database of ortholog clusters (OCs).
