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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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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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Single Cell RNA-Seq analysis of Arabidopsis thaliana roots

  Single-cell RNA-Seq (scRNA-Seq) analysis has been widely used to investigate animal tissue heterogeneity, principally with human and mouse data. However, this technique is increasingly being used to study plant tissues as well with comparable results. Despite the challenges it faces due to the plant cell wall, researchers have been able to perform single-cell analysis with plant protoplasts, bringing the

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STARsolo Single-cell Quantification in OmicsBox

  What is scRNA-Seq Quantification? The first step for any Single-cell RNA-Seq analysis is to perform the quantification or, in other words, to obtain the gene expression values by cell. It is the input data for further analysis like Clustering, Trajectory, Cell-Cell Communication, Differential Expression, etc. Briefly, in order to obtain the expression values the sequencing reads are aligned to

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Quality Assessment of DNA-Seq De Novo Assemblies using QUAST

Genetic Variation studies often involve analyzing samples from a previously studied species. For instance, it is of interest to examine genomes of various cultivars, strains, or populations of the same species. In such cases, it may be necessary to perform de novo DNA-Seq assembly to obtain the genome of the sequenced organisms, even if a reference genome is available. To

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Cell-Type Identification via Functional Enrichment Analysis of Single-Cell RNA-Seq Data

  Single-cell RNA sequencing (scRNA-seq) has proven its usefulness in deciphering biological processes. Since it allows the study of samples at the cell level, it provides a more detailed view of the underlying biology.  A nearly mandatory step in any scRNA-seq analysis is to identify the cell types present in the analyzed samples so further biological insights can be obtained.

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Single-Cell Differential Expression Analysis

Tutorial: Single-Cell RNA-Seq Differential Expression Analysis

The differential expression (DE) analysis has been used in bulk RNA-seq analysis for many years. It allows us to statistically measure changes in gene expression levels between different groups. With bulk RNA-seq analysis many cells are sequenced at the same time, so gene expression levels are commonly measured at the tissue level. Thus, the differences between samples and conditions are

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scRNA-seq Differential Expression with EdgeR

Why Differential Expression Analysis with Single-cell RNA-seq data? The differential expression (DE) analysis has been used in bulk RNA-seq analysis for many years. It statistically measures changes in gene expression levels between different groups. With bulk RNA-seq analysis many cells are sequenced at the same time, so gene expression levels are commonly measured at the tissue level. Thus, the differences

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Single Cell Clustering Seurat

Single Cell Clustering With Seurat in OmicsBox

Introduction Single-cell RNA sequencing (scRNA-seq) is a technology that aims to study the expression profiles of individual cells, in contrast with the typical bulk RNA sequencing that analyses the expression of large populations of cells together. scRNA-seq allows the identification of different cell types within the same sample, so it is possible to study tissues with more detail. One of

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