www.ncbi.nlm.nih.gov - NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).
Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional...
github.com - An interactive data analysis tool for selection, aggregation and visualization of metagenomic data is presented. Functional analysis with a SEED hierarchy and pathway diagram based on KEGG orthology based upon MG-RAST annotation results is...
github.com - What is PhyloHerb: PhyloHerb is a wrapper program to process genome skimming data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs...
Detecting piRNAs involves a combination of computational and analytical methods to identify these unique small RNAs and their roles in gene regulation and transposable element suppression. By following this step-by-step guide, you can confidently...
A major breakthrough (replaced microarrays) in the late 00’s and has been widely used since
Measures the average expression level for each gene across a large population of input cells
Useful for comparative transcriptomics,...
http://mgcv.cmbi.ru.nl/ - MGcV is an interactive web-based visalization tool tailored to facilitate small scale genome analysis. To start using MGcV:
Supply your genes/genomic segments/phylogenetic tree of interest in the input-box by
selecting the type of identifier...
github.com - KAT is a suite of tools that analyse jellyfish hashes or sequence files (fasta or fastq) using kmer counts. The following tools are currently available in KAT:
hist: Create an histogram of k-mer occurrences from a sequence file. Adds metadata in...
github.com - ProteoClade is a Python library for taxonomic-based annotation and quantification of bottom-up proteomics data. It is designed to be user-friendly, and has been optimized for speed and storage requirements.
ProteoClade helps you analyze two...
master.bioconductor.org - Here we walk through an end-to-end gene-level RNA-seq differential expression workflow using Bioconductor packages. We will start from the FASTQ files, show how these were quantified to the reference transcripts, and prepare gene-level count...
the sequenced reads can be mapped to the organism’s genes to assess how differently the genes are expressed under the experimental circumstances as opposed to the control scenario. This is known as differential expression (DE) analysis