- AgBioData-LIST - Main Bioinformatics Lab

REMINDER - Monthly Webinar TOMORROW at 12 PM CT

by Annarita Marrano

Hi everybody, Join us *tomorrow*, Oct. 2nd, *at 12 PM CDT*. Montana Smith will discuss the National Microbiome Data Collaborative (NMDC) initiative and its work on advancing microbiome science through FAIR and standardized metadata and data. I have included more details about the webinar and the Zoom link to attend the webinar below. I hope you will join us. Best, Annarita :-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-: *Abstracts:* *NMDC: Advancing microbiome science through FAIR and standardized metadata and data* The National Microbiome Data Collaborative (NMDC)’s mission is to support a FAIR microbiome data-sharing network through infrastructure, data standards, and community building that addresses pressing challenges in environmental sciences. In this webinar, we will dive into what the NMDC is and how standardized metadata capture enables FAIR data. We will walk through the 4 NMDC products and how they’re lowering barriers for experimental scientists to conduct their research in a way that ensures data re-use. *| 1P ET | 12P CT | 11A MT | 10A PT |* Find your local time here <https://www.timeanddate.com/worldclock/fixedtime.html?msg=AgBioData+Monthly…> *Join Zoom Meetinghttps://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09 <https://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09>* Meeting ID: 820 3835 6125 Passcode: 160683

5 days, 3 hours

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REMINDER - Monthly Webinar Next Wed, Oct, 2nd, at 12 PM CT

by Annarita Marrano

Hi everybody, Join us for our monthly webinar next Wednesday, Oct. 2nd, at 12 PM CDT. Montana Smith will talk about the National Microbiome Data Collaborative (NMDC) initiative and their work on advancing microbiome science through FAIR and standardized metadata and data. I have included more details about the webinar and the Zoom link to attend the webinar below. I hope you will join us. Best, Annarita :-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-: *Abstracts:* *NMDC: Advancing microbiome science through FAIR and standardized metadata and data* The National Microbiome Data Collaborative (NMDC)’s mission is to support a FAIR microbiome data-sharing network through infrastructure, data standards, and community building that addresses pressing challenges in environmental sciences. In this webinar, we will dive into what the NMDC is and how standardized metadata capture enables FAIR data. We will walk through the 4 NMDC products and how they’re lowering barriers for experimental scientists to conduct their research in a way that ensures data re-use. *| 1P ET | 12P CT | 11A MT | 10A PT |* Find your local time here <https://www.timeanddate.com/worldclock/fixedtime.html?msg=AgBioData+Monthly…> *Join Zoom Meetinghttps://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09 <https://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09>* Meeting ID: 820 3835 6125 Passcode: 160683

1 week, 4 days

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REMINDER - Monthly Webinar Next Wed, Sept. 4th, at 12 PM CT

by Annarita Marrano

Hi everybody, Join us for our monthly webinar tomorrow at 12 PM CDT! *Dr. David Emms from InstaDeep* will discuss AgroNT, a foundational large language model for plant genomics. I have included more details about the webinar and the Zoom link to attend the webinar below. I hope you will join us. Best, Annarita :-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-: *Abstracts:* *AgroNT: A Foundational Large Language Model for Plant Genomics* Foundational large language models can be pre-trained on large unlabelled datasets and subsequently fine-tuned to a wide range of specific tasks. We’ll present AgroNT (Agro Nucleotide Transformer), a foundational DNA large language model pre-trained on reference genomes from 48 plant species with a predominant focus on crops. We have shown that AgroNT can be fine-tuned to obtain state-of-the-art predictions of many genomic elements, including polyadenylation sites, splice sites, open chromatin and enhancer regions. Furthermore, AgroNT can be fine-tuned to e.g. predict tissue-specific gene expression levels or to prioritize functional variants. Building on our Nucleotide Transformer, the novel SegmentNT model is able to make nucleotide resolution predictions, well suited to tasks such as de novo genome annotation of previously unseen species. Both our AgroNT and SegmentNT models are open-sourced for academic research and non-commercial uses on our GitHub repository https://github.com/instadeepai/nucleotide-transformer and HuggingFace space https://huggingface.co/InstaDeepAI. *| 1P ET | 12P CT | 11A MT | 10A PT |* Find your local time here <https://www.timeanddate.com/worldclock/fixedtime.html?msg=AgBioData+Monthly…> *Join Zoom Meetinghttps://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09 <https://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09>* Meeting ID: 820 3835 6125 Passcode: 160683

1 month

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REMINDER - Monthly Webinar Next Wed, Sept. 4th, at 12 PM CT

by Annarita Marrano

Hi everybody, Join us for our monthly webinar next Wednesday, Sept. 4th, at 12 PM CDT. Dr. David Emms from InstaDeep will discuss AgroNT, a foundational large language model for plant genomics. I have included more details about the webinar and the Zoom link to attend the webinar below. I hope you will join us. Best, Annarita :-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-: *Abstracts:* *AgroNT: A Foundational Large Language Model for Plant Genomics* Foundational large language models can be pre-trained on large unlabelled datasets and subsequently fine-tuned to a wide range of specific tasks. We’ll present AgroNT (Agro Nucleotide Transformer), a foundational DNA large language model pre-trained on reference genomes from 48 plant species with a predominant focus on crops. We have shown that AgroNT can be fine-tuned to obtain state-of-the-art predictions of many genomic elements, including polyadenylation sites, splice sites, open chromatin and enhancer regions. Furthermore, AgroNT can be fine-tuned to e.g. predict tissue-specific gene expression levels or to prioritize functional variants. Building on our Nucleotide Transformer, the novel SegmentNT model is able to make nucleotide resolution predictions, well suited to tasks such as de novo genome annotation of previously unseen species. Both our AgroNT and SegmentNT models are open-sourced for academic research and non-commercial uses on our GitHub repository https://github.com/instadeepai/nucleotide-transformer and HuggingFace space https://huggingface.co/InstaDeepAI. *| 1P ET | 12P CT | 11A MT | 10A PT |* Find your local time here <https://www.timeanddate.com/worldclock/fixedtime.html?msg=AgBioData+Monthly…> *Join Zoom Meetinghttps://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09 <https://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09>* Meeting ID: 820 3835 6125 Passcode: 160683

1 month, 1 week

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REMINDER - Monthly Webinar TOMORROW, August 7th, at 12 PM CT

by Annarita Marrano

Hi everybody, This is a friendly reminder of tomorrow's webinar at 12 PM CDT. *Seth Murray <https://soilcrop.tamu.edu/people/murray-seth-c/> *(Texas A&M University, TAMU) will present on temporal field phenomics. I have included below more details about the webinar and the Zoom link to attend the webinar. I hope you will join us. Best, Annarita :-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-: *Abstracts:* *Capturing Nature AND Nurture with Temporal Field Phenomics to Breed Better Crops* An organism’s phenome results from genotype (nature), environment and management effects (nurture) and their interactions, as well as measurement error. For over 30 years, DNA sequencing and genomics tools have advanced genotyping to where genomes can now be routinely saturated with measurements. In contrast, most focus in high throughput phenotyping and phenomics to date has been on automating previously known “traits” as measurable and interpretable phenotypes; akin to focusing on measuring a single DNA marker rather than measuring a saturated genome. Tools such as unoccupied aerial systems (UAS, aka UAVs, drones) collecting temporal phenomic measurements in the field now allow novel methods in plant breeding and new insights into plant biology. Viewing phenomics as a platform for discovery, similar to genomics, opens new methods for capturing phenomena in nature and nurture. To date, our experience with phenomic prediction from UAS in maize breeding for cumulative, complex phenotypes such as grain yield suggests it’s possible to predict organismal performance in untested environments; in fact possibly better than gold-standard genomic methods. Surprising insights into biology have also been made in through these activities predicting plant disease and resistance, evaluating genotypic resilience to stress, and identifying early season growth periods for crop improvement that have not been able to be selected. Method development and data analytics in phenomics are large investments, but worth making. Successfully measuring the phenome will impact every aspect of science and society, in biological disciplines from germplasm curators, physiologists to breeders, to education, the courtroom and policy. *| 1P ET | 12P CT | 11A MT | 10A PT |* Find your local time here <https://www.timeanddate.com/worldclock/fixedtime.html?msg=AgBioData+Monthly…> *Join Zoom Meetinghttps://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09 <https://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09>* Meeting ID: 820 3835 6125 Passcode: 160683

2 months

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REMINDER - Monthly Webinar Next Wed, August 7th, at 12 PM CT

by Annarita Marrano

Hi everybody, Join us next Wednesday, August 7th, at 12 PM CDT for our monthly webinar. *Seth Murray <https://soilcrop.tamu.edu/people/murray-seth-c/> *(Texas A&M University, TAMU) will present on temporal field phenomics. I have included below more details about the webinar and the Zoom link to attend the webinar. I hope you will join us. Best, Annarita :-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-: *Abstracts:* *Capturing Nature AND Nurture with Temporal Field Phenomics to Breed Better Crops* An organism’s phenome results from genotype (nature), environment and management effects (nurture) and their interactions, as well as measurement error. For over 30 years, DNA sequencing and genomics tools have advanced genotyping to where genomes can now be routinely saturated with measurements. In contrast, most focus in high throughput phenotyping and phenomics to date has been on automating previously known “traits” as measurable and interpretable phenotypes; akin to focusing on measuring a single DNA marker rather than measuring a saturated genome. Tools such as unoccupied aerial systems (UAS, aka UAVs, drones) collecting temporal phenomic measurements in the field now allow novel methods in plant breeding and new insights into plant biology. Viewing phenomics as a platform for discovery, similar to genomics, opens new methods for capturing phenomena in nature and nurture. To date, our experience with phenomic prediction from UAS in maize breeding for cumulative, complex phenotypes such as grain yield suggests it’s possible to predict organismal performance in untested environments; in fact possibly better than gold-standard genomic methods. Surprising insights into biology have also been made in through these activities predicting plant disease and resistance, evaluating genotypic resilience to stress, and identifying early season growth periods for crop improvement that have not been able to be selected. Method development and data analytics in phenomics are large investments, but worth making. Successfully measuring the phenome will impact every aspect of science and society, in biological disciplines from germplasm curators, physiologists to breeders, to education, the courtroom and policy. *| 1P ET | 12P CT | 11A MT | 10A PT |* Find your local time here <https://www.timeanddate.com/worldclock/fixedtime.html?msg=AgBioData+Monthly…> *Join Zoom Meetinghttps://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09 <https://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09>* Meeting ID: 820 3835 6125 Passcode: 160683 ReplyForward

2 months, 1 week

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REMINDER: Please participate to the AgBioData survey on FAIR data management

by Annarita Marrano

Dear all, Thank you for being part of the AgBioData community. We are almost at the end of a three-year National Science Foundation (NSF) RCN project. We want to estimate the impact of these years' efforts on increasing the awareness and implementation of FAIR practices in the ag research community. *If you haven't already*, we invite you to participate in a *brief survey* *on the impact of AgBioData activities on FAIR data management awareness*. This survey, which follows up on one we ran in 2022, will help us quantify any significant change in the implementation of FAIR practices since the beginning of the project. Click here <https://tinyurl.com/AgBioData24> to participate in this survey. Your participation in this survey is crucial for our mission to enhance FAIR data in agricultural research. It will provide insights to help us define the consortium's directions and secure future funding. We want to emphasize that your participation is entirely voluntary and anonymous. Best, Annarita

2 months, 2 weeks

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Webinar TOMORROW at 10 AM CST "Building a FAIR data ecosystem for incorporating single-cell genomics data into agricultural G2P research"

by Annarita Marrano

Dear all, A friendly reminder of *tomorrow's appointment* with the scRNA Biocuration WG *at 8 a.m. PST / 10 a.m. CST / 11 a.m. EST / 5 p.m. CET* (Zoom link <https://us06web.zoom.us/j/85091905235?pwd=Oqhn0Pvy3iXd5jObJi0JyacJy0bgmf.1> ). Muskan Kapoor, a graduate research assistant in Tuggle's lab, will discuss the current state of developing a single-cell data portal for farm animals. There are more details on the talk at the bottom of this email. I hope you will join us. Best, Annarita ---------------------------------------------------------------------------------------------------------------- *Abstract*: *Building a FAIR data ecosystem for incorporating single-cell genomics data into agricultural G2P research* The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA-seq) data are comparatively underdeveloped. To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate, co-developed by the Broad Institute of MIT and Harvard, Microsoft, and Verily. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species. ReplyForward

2 months, 3 weeks

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RFI and Open Meeting of the Standards for Genetic Variation Working Group - July 18th (11 AM Eastern Time)

by Annarita Marrano

Dear all, The AgBioData Standards for Genetic Variation Working Group (SGV) is preparing a white paper to support the adoption of rsIDs for agriculture and seeks your valuable input and data to further our research efforts. They invite the AgBioData community to join them on* July 18 at 11:00 ET *to review the material and *discuss collaboration opportunities*. In particular, the SGV is looking for the following information: 1. Genetic Markers Linked to Traits: - A list of genetic markers associated with specific traits used by the breeding and research community across various agricultural species, including plants, animals, and insects. See an example here <https://docs.google.com/spreadsheets/d/167DaYxbdKejoL0l6UhGqMPu-GbGsW6vIok7…> . - Information on the species and traits these markers are linked to and the methodologies/platforms employed for genotyping in your community. 2. Functional Validation and Fitness Outcomes: - Examples of genetic variations that have been functionally validated, including descriptions of the phenotypic differences these variations lead to. - Case studies or data demonstrating these genetic variations have resulted in measurable fitness outcomes for the species in question. - Information on related publications and any supporting data available. - We would like to request examples from each of the different species/database providers for review at the upcoming GV working group meeting in July. 3. Standards and Data Access for Genetic & Phenotypic Variation: FAIR/ Interoperability - Standard formats for exchanging information, identifiers, formats, and controlled vocabulary on: - Germplasm - Genetic Variation - Phenotypes - Types of views and files provided for data access. - Future targets for operating, displaying, or providing access to these data types. - Usage of rsIDs and potential barriers to their adoption in your resource. - For more information on RSIDs, please look at the following document RefSNPs: Clustered Variants <https://docs.google.com/document/d/1PHXqW7M50mE5SSl4Zprd904KCr9nWzSR4L8sx3U…> 4. Collaboration Opportunities: - Barriers encountered when working with these data types. - Opportunities for collaboration or data standards, sharing, and interoperability. We really appreciate your support and look forward to your positive response to the request for information in any of the four categories. *If you are willing to participate or are interested in contributing to our initiative and would like to collaborate, please complete this form (https://forms.gle/jcjWnLibHEKuESJe6 <https://forms.gle/jcjWnLibHEKuESJe6>) by July 16. *We will follow up with you with the Zoom link and other resources. Best, The AgBioData Standards for Genetic Variation WG

2 months, 4 weeks

1
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Webinar on July 17th at 10 AM CST "Building a FAIR data ecosystem for incorporating single-cell genomics data into agricultural G2P research"

by Annarita Marrano

Dear all, The scRNA Biocuration WG invites you to an open meeting on *July 17th at 8 a.m. PST / 10 a.m. CST / 11 a.m. EST / 5 p.m. CET* (Zoom link <https://us06web.zoom.us/j/85091905235?pwd=Oqhn0Pvy3iXd5jObJi0JyacJy0bgmf.1> ). Muskan Kapoor, a graduate research assistant in Tuggle lab, will discuss the current state of developing a single-cell data portal for farm animals. More details on the talk at the bottom of this email. I hope you will join us. Best, Annarita ---------------------------------------------------------------------------------------------------------------- *Abstract*: *Building a FAIR data ecosystem for incorporating single-cell genomics data into agricultural G2P research* The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA-seq) data are comparatively underdeveloped. To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate, co-developed by the Broad Institute of MIT and Harvard, Microsoft, and Verily. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

2 months, 4 weeks

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AgBioData-LIST