-
Notifications
You must be signed in to change notification settings - Fork 24
TOPIC: Networks
Code associated will all lessons can be found on the github page
- Some familiarity with R
- For Lesson 1 - a familiarity with 16S rRNA gene amplicon datasets (Not Required for Lessons 2+)
- Lesson 1: Building a network from abundance data
- Lesson 2: Visualizing Your Network
- Lesson 3: Analyzing Your Network
Date posted: 09 April 2020
Author(s): Dr. Jacob A. Cram
Instructor(s): Dr. Joy Buongiorno, Dr. Jacob A. Cram, Dr. Jake L. Weissman
- Building a correlation network from amplicon data
- Dealing with compositional data
- Centered log-ratio transform
- SparCC
Primary tools/programs used:
- SparCC (implemented in SpiecEasi)
- The compositionality problem inherent in microbiome data
Date posted: 16 April 2020
Author(s): Dr. Jake L. Weissman
Instructor(s): Dr. Joy Buongiorno, Dr. Jacob A. Cram, Dr. Jake L. Weissman
- Issues with correlation networks
- The graphical lasso
- SpiecEasi
Primary tools/programs used:
Date posted: 09 April 2020
Author(s): Dr. Jacob A. Cram
Instructor(s): Dr. Jacob A. Cram
- Building time-lagged networks in R (no LSA/eLSA needed)
- Correcting for compositionality with SparCC when building time-lagged networks
Primary tools/programs used:
Date posted: 6 June 2020
Author(s): Dr. Jacob A. Cram
Instructor(s): Dr. Jacob A. Cram
- Building time-lagged networks with eLSA
Primary tools/programs used:
Date posted: 23 April 2020
Author(s): Dr. Joy Buongiorno
Instructor(s): Dr. Joy Buongiorno, Dr. Jacob A. Cram, Dr. Jake L. Weissman
- A tour of cytoscape's visualization capabilities
Primary tools/programs used:
Date posted: 30 April 2020
Author(s): Dr. Jake L. Weissman
Instructor(s): Dr. Joy Buongiorno, Dr. Jacob A. Cram, Dr. Jake L. Weissman
- A tour of igraph's visualization capabilities
Primary tools/programs used:
Date posted: 07 May 2020
Author(s): Dr. Joy Buongiorno
Instructor(s): Dr. Joy Buongiorno, Dr. Jacob A. Cram, Dr. Jake L. Weissman
- An introduction to network clustering with the igraph package in R
Primary tools/programs used:
Date posted: 22 May 2020
Author(s): Dr. Jake L. Weissman
Instructor(s): Dr. Joy Buongiorno, Dr. Jacob A. Cram, Dr. Jake L. Weissman
- An introduction to random network models
- Degree distributions
- Erdos-Reyni Networks
- Barabasi-Albert Algorithm
- Stochastic Block Models
Primary tools/programs used:
- Course: Understanding and Exploring Network Epidemiology in the Time of Coronavirus
- Textbook (free):Network Science by Barabasi
- Textbook (not free but very popular): Networks by Newman
- List of Netsci Tools
- Course Website (UMD grad course): Networks Across Scales
- Netsci Readings (somewhat more advanced)
- Tool: Robust Regression with Compositional Covariates (may be useful for building networks with non-compositional covariates such as environmental measurements)
- Power-law distributions in empirical data and companion page
- SFI Introductory Course on Networks: Complexity Explorer
- SFI Graduate Course on NetSci: CSCI 5352
Home -- Topics -- Unix -- R -- Amplicons -- Metagenomics -- Functional Annotation -- Transcriptomics -- Networks -- Python -- Reproducibility Challenge -- BVCN Conference 2021 -- Infrastructure Used -- Jupyter -- MyBinder -- Get Involved!