github.com - AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on text,...
www.nasa.gov - The NASA Open Science Data Repository (OSDR) enables access to space-related data from experiments and missions that investigate biological and health responses of terrestrial life to spaceflight. The goal of OSDR is to enable multi-modal and...
github.com - MGSE can harness the power of files generated in genome sequencing projects to predict the genome size. Required are the FASTA file containing a high continuity assembly and a BAM file with all available reads mapped to this assembly. The script...
github.com - Trinity, developed at the Broad Institute and the Hebrew University of Jerusalem, represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules:...
ncbi.github.io - Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of...
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...
Pathway Analysis is usually performed with aim to enrich the genes with their functional information and reveal the underlying biological mechanisms pursue by genes. Pathway Analysis is not only limited to what biological pathways a particular set...
Webinar on Unique Molecular Identifier-powered Ultra-sensitive Variant Calling using Strand NGS - Case Study
by Dr. Pandurang Kolekar, Bioinformatics Engineer, Strand Life Sciences
Abstract:
Unique Molecular Identifiers (UMIs) are short...
Choosing the right normalization method depends on the specific objectives of your RNA-Seq analysis. TPM’s proportionality and robustness make it the preferred choice for most applications, while CPM serves well for differential expression...