Fastq-files were quality checked with FastQC (Babraham Bioinformatics) and trimmed for residual adapter sequences. Reads were aligned to the GRCh38 human genome using TopHatR (2.1.0–Johns Hopkins University, Center for Computational Biology) and Bowtie2 (46 (link)). Counts per gene were determined as sum of all reads mapped within a gene region. Principal component (PC) analysis was performed in R (47 ) using the 1,000 top-variable genes within the data set. Differentially expressed genes were identified using negative binomial distributions as implemented in the DESeq2 package (48 (link)) in R. False discovery rates (FDR) were calculated to adjust p-values for multiple testing and FDR-values below 0.05 were considered as significant. Expression data for differentially expressed genes were variance-stabilized transformed and scaled prior to visualization in heat maps. RNA sequencing data are available at the GEO platform with the accession number GSE129196.
Trueseq kits
The TruSeq kits from Illumina are a set of sample preparation kits designed to enable efficient and accurate DNA or RNA sequencing. The kits provide a streamlined workflow for library preparation, allowing users to generate high-quality sequencing libraries from a variety of sample types. The core function of the TruSeq kits is to prepare sequencing-ready libraries from DNA or RNA samples.
Lab products found in correlation
3 protocols using trueseq kits
RNA-seq Workflow for Differential Expression
Fastq-files were quality checked with FastQC (Babraham Bioinformatics) and trimmed for residual adapter sequences. Reads were aligned to the GRCh38 human genome using TopHatR (2.1.0–Johns Hopkins University, Center for Computational Biology) and Bowtie2 (46 (link)). Counts per gene were determined as sum of all reads mapped within a gene region. Principal component (PC) analysis was performed in R (47 ) using the 1,000 top-variable genes within the data set. Differentially expressed genes were identified using negative binomial distributions as implemented in the DESeq2 package (48 (link)) in R. False discovery rates (FDR) were calculated to adjust p-values for multiple testing and FDR-values below 0.05 were considered as significant. Expression data for differentially expressed genes were variance-stabilized transformed and scaled prior to visualization in heat maps. RNA sequencing data are available at the GEO platform with the accession number GSE129196.
Transcriptome Analysis of Cellular Differentiation
Genome-wide Expression and Variation Analysis
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