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,...
github.com - With the EGAD (Extending ‘Guilt-by-Association’ by Degree) package, we present a series of highly efficient tools to calculate functional properties in networks based on the guilt-by-association principle. These allow rapid controlled...
The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods...
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
bactopia.github.io - Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!
Bactopia was inspired by Staphopia, a...
kiwi.cs.dal.ca - RITA is a standalone software package and Web server for taxonomic assignment of metagenomic sequence reads. By combining homology predictions from BLAST or UBLAST with compositional classifications from a Naive Bayes classifier, RITA is able to...
github.com - Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls...