16 resources for re-analyzing public expression data.

1.  https://rnama.com/docs/search-evaluation  RNA meta Analysis has ~26,700 studies (5,717 RNA-Seq and 20,955 Microarray)

2.  [refine.bio](https://www.refine.bio/) will have harmonized over 60,000 gene expression experiments

3.  BioJupies https://maayanlab.cloud/biojupies/

4.  [Recount2-FANTOM](https://www.biorxiv.org/content/10.1101/659490v1) Recounting the FANTOM Cage Associated Transcriptome. Long non-coding RNAs.

5.  Recount3 https://rna.recount.bio/

6.  [dee2](http://dee2.io/) Digital Expression Explorer 2. Digital Expression Explorer 2 (DEE2) is a repository of uniformly processed RNA-seq data mined from public data obtained from NCBI Short Read Archive. By Ziemann Mark et.al! Version 2 of dee.

7.  Extracting allelic read counts from 250,000 human sequencing runs in Sequence Read Archive https://www.biorxiv.org/content/10.1101/386441v1?rss=1

8.   [MetaSRA: normalized sample-specific metadata for the Sequence Read Archive](http://biorxiv.org/content/early/2016/11/30/090506)

9.   [ARCHS4: Massive Mining of Publicly Available RNA-seq Data from Human and Mouse](https://amp.pharm.mssm.edu/archs4/) ARCHS4 provides access to gene counts from HiSeq 2000, HiSeq 2500 and NextSeq 500 platforms for human and mouse experiments from GEO and SRA.

10.  [DEP-reads: Uniformlly processed public RNA-Seq data](http://bioinformatics.sdstate.edu/reads/) Read counts data for 5,470 human and mouse datasets from ARCHS4 v6 and 12,670 datasets from DEE2 for 9 model organisms by steven Ge.

11.  [SRA-explorer](https://ewels.github.io/sra-explorer/) This tool aims to make datasets within the Sequence Read Archive more accessible. 

12.  [intropolis](https://github.com/nellore/intropolis) is a list of exon-exon junctions found across **21,504** human RNA-seq samples on the Sequence Read Archive (SRA) from spliced read alignment to hg19 with Rail-RNA.

13.   [batch recompute ~20,000 RNA-seq samples from larget sequencing project such as TCGA, TARGET and GETEX](https://genome-cancer.soe.ucsc.edu/proj/site/xena/datapages/?host=https://toil.xenahubs.net). Used `hg38` and `gencode v21` as annotation.

14.   [A cloud-based workflow to quantify transcript-expression levels in public cancer compendia](http://biorxiv.org/content/early/2016/07/12/063552) used kallisto for TCGA/CCLE datasets and gencode v24 as annotation.

15.   [MiPanda](http://www.mipanda.org/) is an online resource for the interrogation and visualization of gene expression data from the myriad of publicly available cancer and normal next generation sequencing datasets.

16.   [Curation of over 10,000 transcriptomic studies to enable data reuse](https://www.biorxiv.org/content/10.1101/2020.07.13.201442v1)