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BioBam at the ECCB 2022

From the 18th to the 21st of September, the BioBam team had the opportunity to take part in one of the largest European conferences on computational biology. The Spanish National Bioinformatics Institute (INB/ELIXIR-ES) and the Barcelona Supercomputing Center (BSC) welcomed bioinformatics and bioscientist from all over the world to the city of Sitges (Barcelona, Spain) to participate in the 21st

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OmicsBox 2.2 Release

We are happy to announce the latest update of OmicsBox 2.2. After several months of intensive work we are finally ready to present the new version of BioBam’s bioinformatics solution. OmicsBox 2.2 comes with new Single Cell and Long Read Data Analysis Features and many other platform improvements. OmicsBox continues improving to become the most efficient, powerful and user-friendly bioinformatics

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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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BAM File Quality Control

Transcriptome sequencing (RNA-Seq) produces big amounts of valuable information on all transcribed elements in the genome. With RNA-Seq, researchers can interrogate the transcriptome to profile gene expression, uncover alternative splicing, and identify novel and discard aberrant transcripts and coding variants, among others. The resulting BAM Files are the source of information for all proceeding step

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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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Long read LongQC

Quality Assessment with LongQC

Specific tools for a new generation of sequencing Third Generation Sequencing (TGS) is getting a notable increase in relevance by surpassing some of the limitations of NGS technologies. In that sense, the main feature of TGS is the capacity to produce much longer reads than NGS. These long reads facilitate the assembly of complex genomes and the study of alternative

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scRNA Seq trajectory inference with Monocle3 in OmicsBox

What is Monocle 3? Monocle 3 is a scRNA-Seq data analysis toolkit developed by Trapnell lab. It is written in R and introduced the notion of pseudotime. Monocle 3 can help perform three major types of scRNA-data analysis: Clustering & classification of cells by putative cell types Assignment of pseudotime to cells and, in turn, construction of single-cell trajectories to

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Long Read Transcriptome with SQANTI3

Transcriptome Analysis with SQANTI3

Transcriptome analysis is a challenging bioinformatic problem. In eukaryotic transcriptomes, alternative splicing and alternative polyadenylation are the most complex issues. Genome-wide analysis of alternative splicing has been studied with short-read RNA sequencing for a while. Nevertheless, this technology needs a subsequent assembly, which is difficult to be resolved in ambiguities in complex loci.

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