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EMERGE-BII

EMergent Ecosystem Response to ChanGE Biology Integration Institute

EMERGE Biology Integration Institute

Predictive understanding of ecosystem response to change has become a pressing societal need in the Anthropocene, and requires integration across disciplines, spatial scales, and timeframes. Developing a framework for understanding how different biological systems interact over time is a major challenge in biology. The National Science Foundation-funded EMergent Ecosystem Responses to ChanGE (EMERGE) Biology Integration Institute aims to develop such a framework by integrating research, training, and high-resolution field and laboratory measurements across 15 scientific subdisciplines–including ecology, physiology, genetics, biogeochemistry, remote sensing, and modeling–across 14 institutions, in order to understand ecosystem-climate feedbacks in Stordalen Mire, a thawing permafrost peatland in arctic Sweden. Rapid warming in the Arctic is driving permafrost thaw, and new availability of formerly-frozen soil carbon for cycling and release to the atmosphere, representing a potentially large but poorly constrained accelerant of climate change. This material is based upon work supported by the National Science Foundation under Grant Number 2022070.

Listed below are a number of the tools that members have developed for better understanding and integration of these datasets.

EMERGE tools

Tool Description Developers Citation
CoverM Metagenomic coverage calculator / BAM file generator Ben Woodcroft (CMR)
Lorikeet Microbial strain resolver, coverage calculator, variant caller, selective pressure calculator Rhys Newell (CMR)
Rosella Metagenomic binning and bin refinement tool Rhys Newell (CMR)
Aviary (incorporated SlamM) Microbial genome recovery pipeline with novel methods for long/short read assembly Rhys Newell (CMR)
Galah Genome dereplication Ben Woodcroft (CMR)
Kingfisher Public sequence and metadata gatherer Ben Woodcroft (CMR)
SingleM De-novo OTUs from shotgun metagenomes Ben Woodcroft (CMR)
GraftM Meta-omic tool that identifies and classifies marker and functional genes Ben Woodcroft (CMR) https://doi.org/10.1093/nar/gky174
DRAM Annotates MAGs and summarizes metabolic potential Mikayla Borton (CSU), Mike Shaffer (CSU), Kelly Wrighton https://doi.org/10.1093/nar/gkaa621
Phylogenetic Null Modeling partitioning variation in phylogenetic data and attributing to assembly processes Stacey Doherty (UNH alum), Jessica Ernakovich (based on Stegen et al., 2013)
vConTACT2 Classifies and clusters viral sequences into approx. genus groups Ben Bolduc (OSU), Sullivan Lab https://doi.org/10.1038/s41587-019-0100-8
VirSorter1 Identifies viral sequences in microbial and viral sequence data Simon Roux (JGI), Sullivan Lab https://doi.org/10.7717/peerj.985
VirSorter2 As VirSorter1, but uses ML and expands viral types detected Jiarong Guo (OSU), Sullivan Lab https://doi.org/10.1186/s40168-020-00990-y
metaPop calculates macro- and micro-diversity metrics Ann Gregory (OSU alum), Sullivan Lab https://doi.org/10.1186/s40168-022-01231-0
ecosys site, landscape, and continental-scale land model Riley, Zhen, Grant
CheckM 2 Microbial genome Q/A Alex Chklovski (CMR) https://doi.org/10.1038/s41592-023-01940-w

Popular repositories Loading

  1. emerge-bii.github.io emerge-bii.github.io Public

    EMERGE-BII website.

    HTML 3

  2. test-zenodo test-zenodo Public

    testing zenodo releases

  3. DRAM_product_refined_pipeline DRAM_product_refined_pipeline Public

    Forked from WrightonLabCSU/emerge_pipline

    Snakemake pipeline to produce DRAM product refined based on temporal paper metabolic definitions

    Python

  4. Burkeetal_ThawPondRSPaper Burkeetal_ThawPondRSPaper Public

    R

  5. .github .github Public

    Python

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