Merge pull request #40 from fhdsl/microbiome-draft

Microbiome empty files

11b-sc-ATAC-Seq.Rmd

@@ -60,7 +60,6 @@ Trajectory analysis, which is used to infer and visualize the developmental or d
 Trajectory inference algorithms, such as:
 
 - [Monocle](https://cole-trapnell-lab.github.io/monocle3/docs/trajectories/) @Qiu2017
-- [Slingshot](https://bioconductor.org/packages/devel/bioc/vignettes/slingshot/inst/doc/vignette.html) @Street2018
 - [Palantir](https://github.com/dpeerlab/Palantir) @Setty2019
 - [PAGA](https://github.com/theislab/paga) @Wolf2019
 

11d-CUT-and-RUN.Rmd

@@ -81,7 +81,7 @@ CUT&RUN has been automated using a Beckman Biomek FX liquid-handling robot so th
 
 ### CUT&Tag
 
-**Cleavage Under Targets and Tagmentation**, **CUT&Tag** for short, is an enzyme tethering approach to profiling chromatin proteins, including histone marks and RNA Pol II. CUT&Tag generates sequence-ready libraries without the need for end polishing and adaptor ligation. It uses a proteinA-Tn5 fusion to tether Tn5 transposase near the site of an antibody to a chromatin protein of interest. A secondary antibody, such as guinea pig anti-rabbit antibody, is used to increase the efficiency of tethering the pA-Tn5 to the target primary antibody. The pA-Tn5 complex is pre-loaded with sequencing adapters that insert into adjacent DNA upon activation with magnesium. CUT&Tag has a very low background and can be performed in a single tube in as little as a day, though primary antibodies are typically incubated overnight. It can also be used with the ICELL8 nano dispensation system to profile single cells.
+**Cleavage Under Targets and Tagmentation**, **CUT&Tag** for short, is an enzyme tethering approach to profiling chromatin proteins, including histone marks and RNA Pol II. CUT&Tag generates sequence-ready libraries without the need for end polishing and adapter ligation. It uses a proteinA-Tn5 fusion to tether Tn5 transposase near the site of an antibody to a chromatin protein of interest. A secondary antibody, such as guinea pig anti-rabbit antibody, is used to increase the efficiency of tethering the pA-Tn5 to the target primary antibody. The pA-Tn5 complex is pre-loaded with sequencing adapters that insert into adjacent DNA upon activation with magnesium. CUT&Tag has a very low background and can be performed in a single tube in as little as a day, though primary antibodies are typically incubated overnight. It can also be used with the ICELL8 nano dispensation system to profile single cells.
 
 A streamlined CUT&Tag protocol was introduced by the [Henikoff Lab](https://research.fredhutch.org/henikoff/en.html) that suppresses DNA accessibility artifacts to ensure high-fidelity mapping of the antibody-targeted protein and improves the signal-to-noise ratio over current chromatin profiling methods. Streamlined CUT&Tag can be performed in a single PCR tube, from cells to amplified libraries, providing low-cost genome-wide chromatin maps. By simplifying library preparation, CUT&Tag-direct requires less than a day at the bench, from live cells to sequencing-ready barcoded libraries. As a result of low background levels, barcoded and pooled CUT&Tag libraries can be sequenced for as little as $25 per sample. This enables routine genome-wide profiling of chromatin proteins and modifications and requires no special skills or equipment.  
 

13-microbiome.Rmd

@@ -0,0 +1,65 @@
+
+```{r, include = FALSE}
+ottrpal::set_knitr_image_path()
+```
+
+# Microbiome Sequencing
+
+<div class = "warning">
+This chapter is incomplete! If you wish to contribute, please [go to this form](https://forms.gle/dqYgmKH8XXE2ohwD9) or our [GitHub page](https://github.com/fhdsl/Choosing_Genomics_Tools).
+</div>
+
+## Learning Objectives
+
+```{r, fig.alt = "Learning Objectives", out.width = "100%", echo = FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY/edit#slide=id.g2668d07d0b9_0_0")
+```
+## A Brief Introduction to Microbiomes
+
+
+Microbes are everywhere. We have found these tiny organisms in the deepest regions of the ocean and in the upper atmosphere. We have found them in:
++ water that has been solid ice for millennia in the Antarctic
++ boiling water in the geysers of Yellowstone National Park.
++ the driest natural environments on Earth, including the Atacama Desert in Chile, where desiccation resistant microbes hide in the soil sometimes waiting ten years for the drop of rain that will jump start their metabolism long enough for them to reproduce before they return to dormancy.
++ perpetually damp environments, like the intestinal tract of the human body where they are constantly the subject of inspection by our diligent immune cells, and where they impact our health in positive and negative ways that we are only beginning to understand.
++ our nuclear reactors, prompting questions about whether we could harness them as tiny machines to help us remediate environmental disasters of the past, present, and future.
+
+ If we looked hard enough, I think we’d find them on the surface of the moon and Mars, though they are probably microbes who stowed away on our spacecraft and are now patiently waiting for a drop of water that may or may not ever show up. If we ever colonize those worlds, microbes will be an indispensable ally in creating an environment that could sustain us.
+
+```{r, fig.alt = "Learning Objectives", out.width = "100%", echo = FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY/edit#slide=id.g26ebab787e9_0_0")
+```
+This figure is adapted from [@Tignat-Perrier2022] under Creative Commons license.
+
+Microbes almost never live alone in the real world (i.e., outside of a laboratory). Rather they exist in communities of different species who are interacting with each other and their environment. Some of these communities will have many different types of organisms, and some will have only a few. Because of the large number of species and individuals involved, no two communities will ever be exactly alike, and quantifying differences between microbial communities is an important area of research at the moment. The types of interactions between organisms are also highly varied. These can include mutualistic relationships, where both organisms benefit from the interaction; parasitic relationships, where one organism exclusively benefits to the detriment of the other; and the full gradient in between.
+
+Microbiome science is everywhere. There are tens of articles published daily in the scientific literature, and many popular science articles and books present these findings to the world of non-scientists. Understanding the promises and limitations of the methods of microbiome science can help avoid misconceptions about microbiome research, and it’s important for practitioners of microbiome science to understand and convey the promise and limitations of our field. Misconceptions abound, frequently arising from the same sources as high-quality popular science microbiome reporting.
+
+    For example, on 5 Feb 2015 an article appeared in the New York Times noting (almost offhand) that Yersinia pestis, the organism responsible for Bubonic plague, had been found in multiple locations throughout the New York City subway system as part of its normal built environment microbiome. This was rapidly followed up on 6 Feb 2015 with an article noting that there was probably not Bubonic plague on the subway system after all, but rather that the approaches used by the research team are limited in their taxonomic resolution, and that likely a harmless close relative of Y. pestis was observed: “What the researchers probably found, [a spokesman for the university where the study originated] said, was bacteria from an unknown species or from organisms that happened to share some gene sequences with the plague bacterium…”.
+
+ As microbiome services and products are increasingly marketed directly to the public, consumers of microbiome research findings, products, and services need to know how to critically evaluate these offerings and their associated claims. As practitioners in the field, we can help by ensuring that the methods we apply are appropriate and reliable, and that we make our work accessible.
+
+## Goals of Amplicon analysis
+
+The technologies that are enabling work in microbiome science are the same that are driving the data revolution in biology. Primarily this work is driven by high-throughput DNA sequencing, which is applied for profiling microbial community composition:
+
++ marker gene profiling (such as 16S or ITS sequencing)
++ functional potential (such as shotgun metagenomic sequencing)
++ functional activity (such as metatranscriptome sequencing)
+
+Other “omics” technologies are now playing an increasing role in microbiome research, such as:
+
++ mass-spectrometry-based metabolomics, which provides profiles of small molecule metabolites in an environment.
++ metaproteomics which provides more detailed descriptions of functional activities of microbes (and their hosts, if applicable).
+
+ As a result, bioinformatics software tools are essential to microbiome research. For many microbiome researchers, bioinformatics is an intimidating and challenging aspect of their projects.
+
+
+## Microbiome Analysis with QIIME 2
+QIIME 2 is an all in one bioinformatics microbiome analysis platform. This platform allows for users to go from sequenced microbiome data to publication ready visualizations. The original QIIME, now referred to as QIIME 1, was published in 2010 [@Caporaso2010] and has been cited tens of thousands of times in the primary literature. QIIME 2, which was published in July of 2019 [@Bolyen2019], succeeded QIIME 1 on 1 January 2018. QIIME 2 is better than QIIME 1 in all ways, and QIIME 1 is no longer actively supported. If you have previously used QIIME 1, you should invest time in learning and switching to QIIME 2. If you’re new to QIIME, start with QIIME 2. (When I refer to QIIME in this book, without specifying whether I’m referring to QIIME 1 or QIIME 2, I’m referring to the platform generally.)
+
+QIIME 2 has large and growing user and developer communities, and these communities make QIIME 2 possible. The epicenter of the community is the QIIME 2 Forum. The forum is primarily known as a place where users can get technical support with QIIME 2 for no charge. Developers of QIIME 2 moderate the forum, and typically respond to technical support questions within a couple of business days. The forum is also a great place to discuss general topics in microbiome bioinformatics, or microbiome research methods generally. There are many active discussions on these topics on the forum. Keeping up with the discussions on the forum is a great way to learn about current topics in microbiome research methods. There’s also a free job board on the forum - you can use the forum to find jobs, or post your own job ads there to find employees who are well-versed in QIIME 2 and other bioinformatics tools. If you’re not already a member of the QIIME 2 Forum, you should consider joining. It’s a great way for you to get help, and as you develop your QIIME 2 skills helping others on the forum is a great way to reenforce your learning and to get involved in the community.
+
+[Here](https://gregcaporaso.github.io/q2book/front-matter/preface.html) is a high-level introduction to microbiome analysis using QIIME 2. This introduction will go over common methods, metrics and approaches used for microbiome science.
+So grab a cup of your favorite hot beverage and let’s get started! ☕
+

_bookdown.yml

@@ -22,7 +22,8 @@ rmd_files: ["index.Rmd",
             "11c-ChIP-Seq.Rmd",
             "11d-CUT-and-RUN.Rmd",
             "12-methylation.Rmd",
-            "13-tool-glossary.Rmd",
+            "13-microbiome.Rmd",
+            "14-tool-glossary.Rmd",
             "About.Rmd",
             "References.Rmd"]
 new_session: yes

book.bib

@@ -141,6 +141,58 @@ @article{Booth2013
   journal = {Nature Protocols}
 }
 
+@ARTICLE{Bolyen2019,
+  title    = "Reproducible, interactive, scalable and extensible microbiome
+              data science using {QIIME} 2",
+  author   = "Bolyen, Evan and Rideout, Jai Ram and Dillon, Matthew R and
+              Bokulich, Nicholas A and Abnet, Christian C and Al-Ghalith,
+              Gabriel A and Alexander, Harriet and Alm, Eric J and Arumugam,
+              Manimozhiyan and Asnicar, Francesco and Bai, Yang and Bisanz,
+              Jordan E and Bittinger, Kyle and Brejnrod, Asker and Brislawn,
+              Colin J and Brown, C Titus and Callahan, Benjamin J and
+              Caraballo-Rodr{\'\i}guez, Andr{\'e}s Mauricio and Chase, John and
+              Cope, Emily K and Da Silva, Ricardo and Diener, Christian and
+              Dorrestein, Pieter C and Douglas, Gavin M and Durall, Daniel M
+              and Duvallet, Claire and Edwardson, Christian F and Ernst,
+              Madeleine and Estaki, Mehrbod and Fouquier, Jennifer and
+              Gauglitz, Julia M and Gibbons, Sean M and Gibson, Deanna L and
+              Gonzalez, Antonio and Gorlick, Kestrel and Guo, Jiarong and
+              Hillmann, Benjamin and Holmes, Susan and Holste, Hannes and
+              Huttenhower, Curtis and Huttley, Gavin A and Janssen, Stefan and
+              Jarmusch, Alan K and Jiang, Lingjing and Kaehler, Benjamin D and
+              Kang, Kyo Bin and Keefe, Christopher R and Keim, Paul and Kelley,
+              Scott T and Knights, Dan and Koester, Irina and Kosciolek, Tomasz
+              and Kreps, Jorden and Langille, Morgan G I and Lee, Joslynn and
+              Ley, Ruth and Liu, Yong-Xin and Loftfield, Erikka and Lozupone,
+              Catherine and Maher, Massoud and Marotz, Clarisse and Martin,
+              Bryan D and McDonald, Daniel and McIver, Lauren J and Melnik,
+              Alexey V and Metcalf, Jessica L and Morgan, Sydney C and Morton,
+              Jamie T and Naimey, Ahmad Turan and Navas-Molina, Jose A and
+              Nothias, Louis Felix and Orchanian, Stephanie B and Pearson,
+              Talima and Peoples, Samuel L and Petras, Daniel and Preuss, Mary
+              Lai and Pruesse, Elmar and Rasmussen, Lasse Buur and Rivers, Adam
+              and Robeson, Michael S and Rosenthal, Patrick and Segata, Nicola
+              and Shaffer, Michael and Shiffer, Arron and Sinha, Rashmi and
+              Song, Se Jin and Spear, John R and Swafford, Austin D and
+              Thompson, Luke R and Torres, Pedro J and Trinh, Pauline and
+              Tripathi, Anupriya and Turnbaugh, Peter J and Ul-Hasan, Sabah and
+              van der Hooft, Justin J J and Vargas, Fernando and
+              V{\'a}zquez-Baeza, Yoshiki and Vogtmann, Emily and von Hippel,
+              Max and Walters, William and Wan, Yunhu and Wang, Mingxun and
+              Warren, Jonathan and Weber, Kyle C and Williamson, Charles H D
+              and Willis, Amy D and Xu, Zhenjiang Zech and Zaneveld, Jesse R
+              and Zhang, Yilong and Zhu, Qiyun and Knight, Rob and Caporaso, J
+              Gregory",
+  journal  = "Nat. Biotechnol.",
+  volume   =  37,
+  number   =  8,
+  pages    = "852--857",
+  month    =  aug,
+  year     =  2019,
+  keywords = "Microbiome, Software"
+}
+
+
 @misc{Bruning2021,
 	title = {Comparative {Analysis} of common alignment tools for single cell {RNA} sequencing},
 	copyright = {© 2021, Posted by Cold Spring Harbor Laboratory. The copyright holder for this pre-print is the author. All rights reserved. The material may not be redistributed, re-used or adapted without the author's permission.},
@@ -322,6 +374,28 @@ @article{Kochmanski2019
   issn={1664-8021},
 }
 
+@ARTICLE{Caporaso2010,
+  title    = "{QIIME} allows analysis of high-throughput community sequencing
+              data",
+  author   = "Caporaso, J Gregory and Kuczynski, Justin and Stombaugh, Jesse
+              and Bittinger, Kyle and Bushman, Frederic D and Costello,
+              Elizabeth K and Fierer, Noah and Pe{\~n}a, Antonio Gonzalez and
+              Goodrich, Julia K and Gordon, Jeffrey I and Huttley, Gavin A and
+              Kelley, Scott T and Knights, Dan and Koenig, Jeremy E and Ley,
+              Ruth E and Lozupone, Catherine A and McDonald, Daniel and Muegge,
+              Brian D and Pirrung, Meg and Reeder, Jens and Sevinsky, Joel R
+              and Turnbaugh, Peter J and Walters, William A and Widmann, Jeremy
+              and Yatsunenko, Tanya and Zaneveld, Jesse and Knight, Rob",
+  journal  = "Nat. Methods",
+  volume   =  7,
+  number   =  5,
+  pages    = "335--336",
+  month    =  may,
+  year     =  2010,
+  language = "en"
+}
+
+
 @website{Hadfield2016,
   url={https://bitesizebio.com/13542/what-everyone-should-know-about-rna-seq/},
   author = {James Hadfield},
@@ -750,6 +824,19 @@ @article{Tarca2006
   url     = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2435252/}
 }
 
+@ARTICLE{Tignat-Perrier2022,
+  title     = "Microorganisms floating through the air",
+  author    = "Tignat-Perrier, Romie and T{\'e}cher, Nathalie and Vogel,
+               Timothy M and Larose, Catherine and Dommergue, Aur{\'e}lien",
+  journal   = "Front. Young Minds",
+  publisher = "Frontiers Media SA",
+  volume    =  10,
+  month     =  mar,
+  year      =  2022,
+  copyright = "https://creativecommons.org/licenses/by/4.0/"
+}
+
+
 @article{Taylor2006,
   title={ESPERR: Learning strong and weak signals in genomic sequence alignments to identify functional elements},
   volume={16},