FPKM, RPKM, CPM, TPM, TMM in RNA-Seq

RNA-seq expression normalization is the process of adjusting the raw gene expression counts to account for differences in sequencing depth and other technical factors. It is important to perform normalization to enable comparisons between samples and increase the accuracy and reproducibility of downstream analyses. Common normalization methods include TPM, FPKM, and DESeq. Who sad this?
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Gene Set Enrichment Analysis (GESA) in R© Karobben

Gene Set Enrichment Analysis (GESA) in R

Gene Set Enrichment Analysis (GSEA) is a powerful tool for interpreting gene expression data in the context of predefined biological pathways and gene sets. It allows researchers to identify enriched gene sets, discover new relationships between genes, and gain insights into the underlying biological mechanisms. Who sad this?
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Find novo transcripts based on Trinity de-nove assembly© Karobben
Single Cell RNA-Seq Notes© Karobben
Single cell RNA-Seq Practice: Seurat© Karobben
VCF processing
BatMeth2
QIIME2
RNA-seq with Trinity
Trinity

Trinity

Trinity RNA-seq is a de novo transcriptome assembly software that uses RNA-seq data to reconstruct transcript sequences and estimate expression levels. It allows for comprehensive analysis of gene expression and isoform diversity in non-model organisms without a reference genome. Who said this?
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FastQC

FastQC

FastQC is a quality control tool used to analyze high-throughput sequencing data. It provides detailed graphs and reports that help assess the quality of the data before further downstream analysis.
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fastp

fastp

fastp is a fast and efficient tool for quality control and preprocessing of high-throughput sequencing data. It can perform adapter trimming, quality filtering, and read correction in a single pass, and supports various sequencing platforms and data formats.
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