Qiita (canonically pronounced cheetah)
Advances in sequencing, proteomics, transcriptomics and metabolomics are giving us new insights into the microbial world and dramatically improving our ability to understand their community composition and function at high resolution. These new technologies are generating vast amounts of data, even from a single study or sample, leading to challenges in storage, representation, analysis, and integration of the disparate data types. Qiita was designed to allow users address these new challenges by keeping track of multiple studies with multiple 'omics data. Additionally, Qiita is capable of supporting multiple analytical pipelines through a 3rd-party plugin system, allowing the user to have a single entry point for all their analyses. Qiita's main site provides database and compute resources to the global community, alleviating the technical burdens, such as familiarity with the command line or access to compute power, that are typically limiting for researchers studying microbial ecology.
Qiita is currently in beta status. We are very open to community contributions and feedback. If you're interested in contributing to Qiita, see CONTRIBUTING.md. If you'd like to report bugs or request features, you can do that in the Qiita issue tracker.
To install and configure your own Qiita server, see INSTALL.md.
For more specific details about qiita visit the Qiita main site tutorial.
- Full study management: Create, delete, update samples in the sample and multiple preparation information files.
- Upload files via direct drag & drop from the web interface or via scp from any server that allows these connections.
- Study privacy management: Sandboxed -> Private -> Public.
- Easy long-term sequence data deposition to the European Nucleotide Archive (ENA), part of the European Bioinformatics Institute (EBI) for private and public studies.
- Raw data processing for:
- Target gene data: we support deblur against GreenGenes (13_8) and close reference picking against GreenGenes (13_8) and Silva.
- Metagenomic and Metatranscriptomic data: we support Shogun processing.
- biom files can be added as new preparation templates for downstream analyses; however, this cannot be made public.
- Basic downstream analyses using Qiime2.
- Basic study search in the study listing page.
- Complex metadata search via redbiom.
Accepted raw files
- Multiplexed SFF
- Multiplexed FASTQ: forward, reverse (optional), and barcodes
- Per sample FASTQ: forward and reverse (optional)
- Multiplexed FASTA/qual files
The following is a non-exhaustive list of features that we plan to add in the future.
- Integration of other pipelines via artifacts. Processing of raw data in external sources. For example, metabolomics processing in GNPS and data visualization in Qiita.
- Creation of a REST API to query and access the data hosted by Qiita.
- Improved analysis pipeline for target gene datasets.
- Crowd-sourced metadata curation of existing studies: improve the metadata of existing studies by submitting a fix proposals to the authors of the study.