Tips, Tricks and Video Tutorial

Mini-tutorials for common use-cases and to address frequently asked questions FAQs

Reference-free analysis of long-read RNA sequencing for non-model species

  With improvements in accuracy and steadily decreasing costs, long-read sequencing technologies, such as the platforms provided by Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), have revolutionized the field of transcriptomics in recent years. Compared to short-read sequencing, which requires RNA fragmentation, long-read sequencing technologies can sequence RNA molecules in their entirety. This allows researchers to study the transcriptome

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Cell Type Prediction with CellKb

Single-cell transcriptomics has revolutionized the way we understand complex biological systems. By enabling researchers to study gene expression at the resolution of individual cells, it uncovers cellular heterogeneity, reveals intricate developmental pathways, and provides insights into disease mechanisms. However, as powerful as single-cell RNA sequencing (scRNA-Seq) is, translating its immense data into meaningful biological insights remains a great challenge. One

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Genome Completeness Assessment with BUSCO

Constructing a high-quality genome assembly is a complex and challenging process. De novo assemblies often suffer from fragmentation, gaps, and various types of assembly errors, which can compromise downstream analyses. Ensuring the completeness and accuracy of these assemblies is essential for robust biological insights. This is where BUSCO (Benchmarking Universal Single-Copy Orthologs) comes into play. BUSCO is a widely used

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New Taxonomy Databases in OmicsBox

One of the new additions in OmicsBox 3.3 is the non-NCBI taxonomy databases for Kraken2. With this new feature, we provide users with a broader range of options for taxonomic classification, meeting diverse research needs. Taxonomic Classification with Kraken2 Kraken2 is a taxonomic sequence classifier that assigns taxonomic labels to DNA reads. It achieves this by examining the k-mers within

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Combining Transcriptomes with TAMA Merge

In analyzing long-read RNA-sequencing data, defining a custom transcriptome by identifying novel isoforms is a complex yet essential task that can have far-reaching consequences for any downstream analyses. As long reads allow researchers to examine isoform diversity in significantly greater detail than short reads, long-read sequencing often reveals a large variety of isoforms not yet present in reference annotations, even

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Understanding maSigPro Timecourse Results

Understanding how gene expression changes over time and in response to different conditions is crucial in biological research. On this matter, timecourse differential expression analysis allows researchers to track gene expression at multiple time points, uncovering dynamic patterns that provide insights into complex biological processes such as development, disease progression, and response to treatments.

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IsoQuant: Long-Read Isoform Identification and Quantification

  Defining transcript models to characterize isoforms from aligned reads is a crucial step in analyzing transcriptomics data, particularly when dealing with long reads originating from technologies such as Pacific Biosciences (PacBio) or Oxford Nanopore Technologies (ONT). In the past few years, so many algorithms to achieve this task have been published, that it is challenging to keep an overview

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Using BWA for DNA and RNA Alignment in OmicsBox

The Burrows-Wheeler Alignment algorithm (BWA) is a tool designed to align short DNA and RNA reads. BWA is based on the Burrows-Wheeler Transform (BWT), an algorithm designed to rearrange sequences into runs of similar characters to improve data compression and efficient sequence alignment in Bioinformatics. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads

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Differences Between GTF and GFF Files in Genomic Data Analysis

In the field of bioinformatics and genomic research, data representation is a critical aspect that influences the ease and accuracy of analysis. Two common file formats used in genomic data representation are Gene Transfer Format (GTF) and General Feature Format (GFF). While they may seem similar at a glance, there are distinct differences between these two formats that are crucial

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