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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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About me
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A collection of my notes for getting started with random forest for genomics research.
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A collection of data science, programming, and data visualization tutorials I have found on the internet. Sources referenced.
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A brief primer on heritability and estimating heritability using phenotype (any observable trait such as height, eye color, or a health condition) data from twins.
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I want to introduce sed in a quick and informal way for anyone who just wants to get a taste of what sed can do.
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If you are tired of typing out the same long command over and over again, it’s time to set up a few bash aliases. Aliases allow you to create shortcut commands for longer ones. For example, instead of typing out ls -l
, you could type ll
+ Enter
to save time.
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The standard pipeline that we use in the Brito Lab for quality control, alignments, and gene abundance calculations for metagenomic data.
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LSA was developed as a pre-assembly tool for partitioning metagenomic reads. It uses a hyperplane hashing function and streaming SVD in order to find covariance relations between k-mers. The code, and the process outline in LSFScripts in particular, have been optimized to scale to massive data sets in fixed memory with a highly distributed computing environment. For resources on LSA, see the following: Manual Github Useful Tips Reference
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How to get started using my favorite text editor.
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Are you tired of typing in a password every time you log into the lab’s server? Follow this tutorial to set up SSH keys so that you never have to type in your password again while logging in!
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We now have RStudio Server installed on all CBSU machines! This means that you can run a hosted RStudio session in your browser and not worry about copying over files from the server, or running out of memory on your own machine. Here are the steps you need to follow to use it.
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Disclaimer: This blog post will only be relevant to members of the Brito Lab.
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Welcome to my academic page. While working as a computational geneticist in graduate school, I’ve collected a lot of notes about how various programs/methods/fun little tricks work. I want to use this blog to share those insights, frustrations, and solutions. Some of them may only be useful to members of the Brito Lab, but my hope is that most will be general enough that anyone in the bioinformatics world could find them interesting.
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Published in G3, 2016
In this study, we focus on the mechanisms used by doublesex (dsx) to generate sexual dimorphism in gene expression, and address the relationship between dsx regulation and consistent sex-differential gene expression across strains. These results provide insights into a more complete pool of potential DSX targets, as well as revealing the molecular flexibility of DSX regulation.
Recommended citation: Arbeitman MN, New FN, Fear JM, Howard TS, Dalton JE, Graze RM. (2016). "Sex Differences in Drosophila Somatic Gene Expression: Variation and Regulation by doublesex." G3. 6(7).
Published in G3, 2016
Male and female reproductive behaviors in Drosophila melanogaster are vastly different, but neurons that express sex-specifically spliced fruitless transcripts (fru P1) underlie these behaviors in both sexes. How this set of neurons can generate such different behaviors between the two sexes is an un- resolved question. These results suggest a possible global mechanism for how distinct behaviors can arise from a shared set of neurons.
Recommended citation: Newell NR*, New FN*, Dalton JE, McIntyre LM, Arbeitman MN. (2016). "Neurons That Underlie Drosophila melanogaster Reproductive Behaviors: Detection of a Large Male-Bias in Gene Expression in fruitless-Expressing Neurons." G3. 6(8).
Published in Genome Res., 2017
This paper is about the substantial, and previously underrecognized, role for alternative splicing in the pathogenesis of autoimmune disorders and particularly for Type I Diabetes. Our findings highlight a substantial, and previously underrecognized, role for alternative splicing in the pathogenesis of autoimmune disorders and particularly for Type I Diabetes.
Recommended citation: Newman JRB, Conesa A, Mika M, New FN, Onengut-Gumuscu S, Atkinson MA, Rich SS, McIntyre LM, Concannon P. (2017). "Disease-specific biases in alternative splicing and tissue-specific dysregulation revealed by multitissue profiling of lymphocyte gene expression in type 1 diabetes." Genome Res.. 27(11).
Published in Genome Biol Evol., 2018
This paper describes the population genetics of a large panel of Drosophila simulans inbred lines.
Recommended citation: Signor SA, New FN, Nuzhdin S. (2018). "A Large Panel of Drosophila simulans Reveals an Abundance of Common Variants." Genome Biol Evol.. 10(1).
Published in Annual Reviews Microbiology, 2020
Review article focusing on the many benefits of using metagenomics and outlining the breadth of conclusions that can be made using currently available tools, while also highlighting the challenges of metagenomic data analysis.
Recommended citation: New FN, Brito IL. (2020). "What Is Metagenomics Teaching Us, and What Is Missed?" Annual Reviews Microbiology. 74:117-35.
Published in eLife, 2021
In this study, we put forth a robust, accessible, and high-throughput platform for sensitively surveying the bacterial hosts of mobile genes in complex microbial communities.
Recommended citation: Diebold, P. J., New, F. N., Hovan, M., Satlin, M. J., & Brito, I. L. (2021). Linking plasmid-based beta-lactamases to their bacterial hosts using single-cell fusion pcr. ELife, 10. https://doi.org/10.7554/elife.66834
Published in Scientific Reports, 2022
In this work, we examine the collective impact of human host genetics on gut microbiome composition and functions using a flexible computational and statistical framework for analyzing host-microbiome genetic interactions.
Recommended citation: New, F. N., Baer, B. R., Clark, A. G., Wells, M. T., & Brito, I. L. (2022). Collective effects of human genomic variation on microbiome function. Scientific Reports, 12. https://doi.org/10.1038/s41598-022-07632-3
Published in Cancer Research Communications, 2023
We describe ultra high-plex spatial proteogenomics; profiling whole transcriptome and high-plex proteomics on a single FFPE tissue section with spatial resolution. Investigation of gcGBM versus GBM revealed distinct protein and RNA expression profiles.
Recommended citation: Bonnett SA, Rosenbloom AB, Ong GT, Conner M, Rininger ABE, Newhouse D, New F, Phan CQ, Ilcisin S, Sato H, Lyssand JS, Geiss G, Beechem JM. Ultra High-plex Spatial Proteogenomic Investigation of Giant Cell Glioblastoma Multiforme Immune Infiltrates Reveals Distinct Protein and RNA Expression Profiles. Cancer Res Commun. 2023 May 3;3(5):763-779. doi 10.1158/2767-9764.CRC-22-0396. PMID 37377888; PMCID PMC10155752.
Published in American Journal of Respiratory and Critical Care Medicine, 2023
Characterization of the transcriptomic signatures from lymphoid follicles (LFs) in ever-smokers without COPD and COPD patients with varying degrees of emphysema using proteomic and transcriptomic profiling.
Recommended citation: Rojas-Quintero J, Ochsner SA, New F, Divakar P, Yang CX, Wu TD, Robinson J, Shimoga Chandrashekar D, Banovich NE, Rosas IO, Sauler M, Kheradmand F, Gaggar A, Margaroli C, San Jose Estepar R, McKenna NJ, Polverino F. Spatial Transcriptomics Resolve an Emphysema-specific Lymphoid Follicle B Cell Signature in COPD. Am J Respir Crit Care Med. 2023 Nov 7. doi 10.1164/rccm.202303-0507LE. Epub ahead of print. PMID 37934672.
Brief description of my research interests.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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