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https://balsa.wustl.edu/

Database for hosting and sharing neuroimaging and neuroanatomical datasets for human and primate species. Includes 1) curated, user created Study datasets, extensively analyzed neuroimaging data associated with published figures/manuscripts, 2) Reference datasets mapped to brain atlas surfaces and volumes in human and nonhuman primates for use as general resources (e.g., published cortical parcellations), and 3) ConnectomeDB powered by BALSA for distributing HCP-Young Adult and related HCP-style processed imaging and phenotypic datasets. Datasets in BALSA may include PMID and/or DOI that links them directly to relevant publications.

Proper citation: BALSA (RRID:SCR_022960) Copy   

•   Source: SciCrunch Registry

http://www.pymvpa.org

A Python package intended to ease statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run. Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. This Python-based, cross-platform, open-source software toolbox software toolbox for the application of classifier-based analysis techniques to fMRI datasets makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages.

Proper citation: PyMVPA (RRID:SCR_006099) Copy   

•   Source: SciCrunch Registry

https://github.com/bmvdgeijn/WASP/

Software allele-specific pipeline for unbiased read mapping and molecular QTL discovery. Allele-specific software for robust molecular quantitative trait locus discovery.

Proper citation: WASP (RRID:SCR_025497) Copy   

•   Source: SciCrunch Registry

https://github.com/SchapiroLabor/histoCAT

Software package to visualize and analyse multiplexed image cytometry data interactively.

Proper citation: histoCAT (RRID:SCR_026499) Copy   

•   Source: SciCrunch Registry

https://github.com/calico/borzoi

Software package to access the Borzoi models, which are convolutional neural networks trained to predict RNA-seq coverage at 32bp resolution given 524kb input sequences.

Proper citation: Borzoi (RRID:SCR_026619) Copy   

•   Source: SciCrunch Registry

https://emberarchive.org/

BRAIN Initiative data archive for multi-modal neurophysiological and behavioral data, supporting the Brain Behavior Quantification and Synchronization (BBQS) Program. Accessible and versatile data archive for storage, processing, and curation of multimodal neurophysiological and behavioral datasets. EMBER extends established BRAIN Initiative data infrastructure, provides new data harmonization and synchronization capabilities, and supports scalable integrations for data coordination and AI driven batch processing to enable the goals of the BBQS program.

Proper citation: Ecosystem for Multi-modal Brain-behavior Experimentation and Research (RRID:SCR_026700) Copy   

•   Source: SciCrunch Registry

https://github.com/SynapseWeb/PyReconstruct

Software successor to the Reconstruct annotation tool. PyReconstruct runs on all major operating systems, breaks through legacy RAM limitations, features intuitive and collaborative curation system, and employs flexible and dynamic approach to image registration. Used to analyze, display, and publish experimental or connectomics data. Suited for generating ground truth to implement in automated segmentation, outcomes of which can be returned to PyReconstruct for proofreading and quality control.

Proper citation: PyReconstruct (RRID:SCR_027562) Copy   

•   Source: SciCrunch Registry

https://pypi.org/project/piano-integration/

Software novel variational autoencoder framework for inferring integrated latent space representations for single cell transcriptomics data that uses a negative binomial generalized linear model for stronger batch correction, and code compilation for ten times faster training than existing tools. Enables superior analyses of multiple atlases, solving challenging integration tasks across sequencing platforms, development, and species, while simultaneously preserving desired biological signals.

Proper citation: PIANO:Probabilistic Inference Autoencoder Networks for multi-Omics (RRID:SCR_027864) Copy   

•   Source: SciCrunch Registry

https://brain-specimenportal.org/unified_resource_browser?resource_type=donor

Neuroanatomy-anchored Information Management Platform for collaborative BICAN data generation developed by UTHealth Houston. Serves as metadata tracking engine to support generation, management, and sharing of brain research data. Integrates data production pipelines across brain banks, laboratories, sequencing centers, and data archives. Platform enables integrative and collaborative, consortium-scale FAIR data generation within the BICAN project. Platform is designed to manage complex dataset, including tissue samples and sequencing data, through Specimen Portal and Sequence Library Portal. Portals provide multiple types of data interfaces through dashboards, APIs, faceted queries, and batch data ingestion and exporting.

Proper citation: NIMP Analytics (RRID:SCR_028218) Copy   

•   Source: SciCrunch Registry

https://github.com/GabrielHoffman/dreamlet

Software R package enables differential expression analysis on multi-sample single cell datasets using linear (mixed) models with precision weights.

Proper citation: dreamlet (RRID:SCR_028168) Copy   

•   Source: SciCrunch Registry

https://github.com/meganhuibregtse/peri-code

Software R code to apply Stages of Reproductive Aging Workshop + 10 stages to prospectively collected vaginal bleeding data among a cohort of Black women aged 40–55 years. Used to apply STRAW+10 stages to prospectively tracked menstrual bleeding data in a longitudinal cohort study of perimenopausal women.

Proper citation: PERI: Prospective Evaluation of Reproductive aging Indicators (RRID:SCR_028698) Copy   

•   Source: SciCrunch Registry