Welcome to NormSeq web manual
The continuous development of various RNA sequencing (RNA-seq) methods has drastically increased the possibilities of performing diverse direct quantitative analysis of the transcriptome in large biological datasets. This has revealed compelling details about various small RNA populations like miRNAs and tRNAs. The selection of appropriate processing pipelines and normalization strategies for these large datasets are key to preserve the complexity of gene expression patterns in biological samples. However, experimental noise resulting from the inherent variability in the generation of RNA-seq data, often hinders accurate quantification and analysis of true biological differences. Data normalization, in particular, is a critical step enabling the meaningful comparison and interpretation of these high-throughput datasets.
NormSeq is developed as a webserver tool dedicated to the systematic evaluation and comparison of most commonly used data normalization methods for RNA-seq based expression datasets. Our platform enables rapid evaluation and selection between eight normalization methods of user-supplied datasets and increase flexibility for downstream analysis. The tool is available through a user-friendly, freely available webserver that reports results for the data normalization method of choice, batch-effect correction and differential expression analyses with multiple visualization options.
NormSeq features include:
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Dedicated data normalization platform: NormSeq is dedicated to RNA-seq data normalization that can be generally used for any kind of RNA data analysis by researchers that are less comfortable with programming.
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Easy and user-friendly selection of input data: .txt/.csv/.tsv/.xls formats can be uploaded directly or via URL link.
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Systematic evaluation of data normalization methods: evaluation of data normalization methods can be achieved by information gain analysis, heatmaps and PCA visualization.
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Batch-effect correction: batch-effect correction by ComBat-seq is used to remove variability in the data.
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Differential Expression (DE) analysis: four different DE methods and consensus are used to discover quantitative differences between groups.
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Summary report: Normseq includes several types of visualization and top expressed features.
Availability
To use NormSeq please visit https://arn.ugr.es/normSeq This website is free and open to all users and there is no login requirement.
Browser compatibility
| OS | Version | Chrome | Firefox | Microsoft Edge | Safari |
|---|---|---|---|---|---|
| Linux | Ubuntu 18 | 108 | not tested | not tested | not tested |
| MacOS | Ventura | 107 | 108 | not tested | 16 |
| Windows | 10 | 108 | 108 | 108 | not tested |