OmicsAnalyst Pro

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Example Datasets

Diabetes [2]	Human multi-omics data from islet tissue (lipidomics, RNA-seq): no diabetes (ND), impaired glucose tolerance (IGT), type 3c diabetes (T3D), and type 2 diabetes (T2D). See Wigger, L. et al. for more details.	Metadata RNA-seq Lipidomics
Diabetes [2]	Human multi-omics data from islet tissue (RNA-seq，proteomics): no diabetes (None), Prediabetes (PreT2D), and type 2 diabetes (T2D). See Ewald, J. et al. for more details.	Metadata RNA-seq Proteomics
Human pregnancy [2]	Human multi-omics data (proteomics, metabolomics) on modeling the chronology of these adaptations during full-term pregnancy. Multi-omics of pregnancy	Metadata Proteomics Metabolomics
Immune cells	Mouse multi-omics data (transcriptomics, metabolomics, miRNA) on the effect of Ikaros transcription factor on B-cell differentiation from STATegRA	Metadata Transcriptomics Metabolomics miRNA
Brain cancer [2]	Human multi-omics data (transcriptomics, miRNA) on glioblastoma multiforme of four different subtypes from TCGA.	Meta-data Transcriptomics miRNA

Please note

Omics data table should be in .txt or .csv format with features in rows and samples in columns.
Samples from each omics table should match the sample names from metadata table.
Omics data table should be normalized already using methods appropriate for the corresponding omics type.

Upload your Metadata File

Specify organism
Metadata file

Metadata table should be in .txt or .csv format with samples in rows and factors in columns.
Samples IDs in each omics table should match the sample names in the metadata table.
Please check your data for missing values, they may cause some malfunctions in downstream analysis.

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