BOL

github.com - This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in: Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes Mads...

amp.pharm.mssm.edu - Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse...

A new “Download assemblies” button is now available in the Assembly database. This makes it easy to download data for multiple genomes without having to write scripts.

www.sequenceontology.org - We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers...

RNA-Seq analysis is a cornerstone of modern transcriptomics, offering bioinformaticians a versatile toolkit for unraveling gene expression and regulation. Mastering RNA-Seq workflows and tools empowers researchers to transform raw sequencing data...

github.com - SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large...

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

Bioinformatics tools

1. Ktrim: An extra-fast, accurate adapter trimmer for sequencing data. It processes FASTQ files from multiple lanes with minimal mismatching and over-trimming of adapters.2. BWA MEM: A reliable alignment tool (particularly for mapping ALT contigs...

The bioinformatics landscape for RNA sequence analysis is vast, with tools catering to specific needs. Whether you’re studying coding RNAs, non-coding RNAs, or exploring RNA-protein interactions, the right tools can transform your data into...