2012年1月31日星期二

course material on evolution and genomics

Evolution and Genomics, here collected many different courses on evolution and genomics.

plotSimmap - plot node numbers

here it is.

find video of various courses in Khan academy

http://www.khanacademy.org/

2012年1月29日星期日

Transform list to matrix and convert back

http://cos.name/cn/topic/105864

http://cos.name/cn/topic/101372

Cultural history holds back Chinese research

We can not freely choose culture for ourself in China now. Everything has been controlled, especially those of culture. So how do you conclude as this, Peng Gong, a so-called intellectual in China? It is not the right time to think if cultural hold back research. It is the time for us to think how/at what level the communism politic depleted our freedom of ....

Do you know what happened in the period of the Cultural Evolution? We have already no culture for at least tens of years.

Python for Non-Programmers

(1) Python for Non-Programmers

(2) tutorial from Pasteur Institute

http://www.pasteur.fr/formation/infobio/python/

(3) a guide from PLoS Computational Biology

http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030199

(4) programming for biologists

http://www.programmingforbiologists.org/programming-resources

Programming Resources

Install Python on your own computer

Download page for Python
Download page for Numpy & Scipy
- 64-bit installation packages for Windows can be downloaded here
Download page for Biopython
Download page for Wing IDE (go to the bottom of the page for the free version - Wing IDE 101)
Installing Nose on Windows (Linux and Mac folks can install from the appropriate repositories)

Programming in Python

Online Python Tutor - see how Python is executing your program line by line
A gentle introduction to programming using Python
A primer on Python for life science researchers
Programming Course for Biologists at the Pasteur Institute
Python course in bioinformatics at the Pasteur Institute
Google's Python Class
Division operators in Python
Software Carpentry - This online course is a great introduction to more advanced concepts in scientific programming
BioPython Tutorial and Cookbook

Scientific Tools in Python

Phylogenetic Tools in Python

ANGUS

ANGUS, a number of detailedtutorials on mapping, assembly, mRNAseq, ChIP-seq, and resequencing analysis

(1) how to do basic scientific data analysis on UNIX

UNIX, ssh, and scp

Renting a computer from Amazon

Running BLASTs on UNIX

UNIX, BLAST, and long-running jobs

Working with CSV files and Python

Plotting with matplotlib

Scripts, Reciprocal Best-Hits BLAST, and some more Python

Mapping with bowtie

Visualizing mappings with Samtools

Other mappers

Short Read Assembly

Visualizing NGS data on UCSC genome browser

Simple mRNAseq: mapping reads to gene sets and doing quantile normalization

Gene differential expression using DEGseq

Analyzing bacterial resequencing data with breseq

Storing data persistently with Amazon

Writing Python scripts incrementally

Aligning ChIP-seq reads and detecting enriched peaks

Using MEME to identify TF binding motif from ChIP-seq data

Slightly more advanced scripting with Python

Using the Nano editor

Using ‘top’ to monitor running jobs

Setting a password rather than using your key

(2) Course Schedule (2010)

Day 1 (Tue, June 1)

Lecture: Introduction to the course (Titus Brown)

Tutorial 1: UNIX, ssh, and scp

Tutorial 2: Renting a computer from Amazon

An Exercise in Reflection (Stage 1)

Day 2 (Wed, June 2)

Lecture: Computational Basics (Titus Brown)

Tutorial 1: Running BLASTs on UNIX

Tutorial 2: UNIX, BLAST, and long-running jobs

Tutorial 3: Working with CSV files and Python

Day 3 (Th, June 3)

Lecture: Thinking Statistically (Ian Dworkin)

Tutorial 1: Plotting with matplotlib

Tutorial 2: Scripts, Reciprocal Best-Hits BLAST, and some more Python

Entertainment: Brewery outing for dinner.

(No tutorial #3.)

Day 4 (Fri, June 4)

Lecture: Mapping Reads to Known Genomes (Titus Brown)

Tutorial 1: Mapping with bowtie

Tutorial 2: Visualizing mappings with Samtools (Rose)

Tutorial 3: Other mappers and Bowtie parameters

Bonfire!

Day 5 (Sat, June 5)

Lecture: Assembly. (Titus Brown)

Tutorial 1: Short Read Assembly (Jason)

Tutorial 2: Visualizing NGS data on UCSC genome browser (Likit)

BBQ on Windmill Island.

Day 6 (Sun, June 6)

Take a break - day of rest! Swim, sleep, make merry.

(Only lunch served.)

Day 7 (Mon, June 7)

Lecture: mRNAseq analysis. (Titus Brown)

Tutorial 1 (11:30am): Simple mRNAseq: mapping reads to gene sets and doing quantile normalization

Tutorial 2 (1:30pm): Gene differential expression using DEGseq (Likit)

Tutorial 3 (3:30pm): UNIX directories and files - a quick introduction

Evening lecture: Doing science on software engineering (Greg Wilson)

Day 8 (Tue, June 8

Lecture: Resequencing analysis. (Jeff Barrick)

Tutorials: Analyzing bacterial resequencing data with breseq

Bonfire!

Day 9 (Wed, June 9)

Tutorial, 11am: Storing data persistently with Amazon

Tutorial, 2:30pm: Writing Python scripts incrementally

Lecture, 8pm: ChIP-seq analysis. (Mark Robinson)

Day 10 (Th, June 10)¶

Tutorial, 9am: Aligning ChIP-seq reads and detecting enriched peaks

Tutorial, 2pm: Using MEME to identify TF binding motif from ChIP-seq data

Tutorial, 1:30pm: more-advanced-python-scripting

(3) tutorials of 2011
http://ged.msu.edu/angus/tutorials-2011/index.html

制作流程图 - linux, mac, windows

http://www.yworks.com/en/index.html

2012年1月28日星期六

two papers on analyzing whole genome resequencing with objective of detecting selections

This group output some good case of analyzing whole genome resequencing with objective of detecting selections.

2011

Matteo Fumagalli, Manuela Sironi, Uberto Pozzoli, Anna Ferrer-Admettla, Linda Pattini, Rasmus NielsenSignatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure throughhuman evolution. PLoS Genetics in Press Supplementary material, 给出了数据和 Rcode。

Cagliani R, Riva S, Pozzoli U, Fumagalli M, Comi GP, Bresolin N, Clerici M, Sironi M. Balancing selection is common in the extended MHC region but most alleles with opposite risk profile for autoimmune diseases are neutrally evolving. BMC Evolutionary Biology 11:171

Common population genetic tests based on the site frequency spectrum (SFS) include Tajima's D (D_T) [14] and Fu and Li's D* and F* [15]. D_Ttests the departure from neutrality by comparing two nucleotide diversity indexes: θ_W[16], an estimate of the expected per site heterozigosity, and π[17], the average number of pairwise sequence nucleotide differences. Positive values of D_Tindicate an excess of intermediate frequency variants and are a signature of balancing selection.Fu and Li's F* and D* are also based on SNP frequency spectra and differ from D_Tin that they also take into account whether mutations occur in external or internal branches of a genealogy[15]. As an empirical comparison, θ_W, π, as well as D_T, F* and D* were calculated for 5 kbwindows (thereafter referred to as reference windows) deriving from 238 genes resequenced bythe NIEHS program in CEU. Additionally, the statistical significance of neutrality tests wasevaluated by performing coalescent simulations with a population genetic model that incorporatesdemographic scenarios [18].

Rachele Cagliani, Matteo Fumagalli, Franca R. Guerini, Stefania Riva, Daniela Galimberti, Giacomo P. Comi, Cristina Agliardi, Elio Scarpini, Uberto Pozzoli and Diego Forni, et al. Identification of a new susceptibility variant for multiple sclerosis in OAS1 by population genetics analysis. Human Genetics Jul 7

Cereda M, Sironi M, Cavalleri M, Pozzoli U. GeCo++: a C++ library for genomic features computation and annotation in the presence of variants. Bioinformatics 2011 Mar 12. [Epub ahead of print]

Magri F, Del Bo R, D'Angelo MG, Govoni A, Ghezzi S, Gandossini S, Sciacco M, Ciscato P, Bordoni A, Tedeschi S, Fortunato F, Lucchini V, Cereda M, Corti S, Moggio M, Bresolin N, Comi GP. Clinical and molecular characterization of a cohort of patients with novel nucleotide alterations of the Dystrophin gene detected by direct sequencing. BMC Med Genet. 2011 Mar 11;12:37.

Tollervey JR, Curk T, Rogelj B, Briese M, Cereda M, Kayikci M, Konig J, Hortobágyi T, Nishimura AL, Zupunski V, Patani R, Chandran S, Rot G, Zupan B, Shaw CE, Ule J. Characterizing the RNA targets and position-dependent splicing regulation by TDP-43. Nat Neurosci. 2011 Apr;14(4):452-8.

Cagliani R, Fruguglietti ME, Berardinelli A, D'Angelo MG, Prelle A, Riva S, Napoli L, Gorni K, Orcesi S, Lamperti C, Pichiecchio A, Signaroldi E, Tupler R, Magri F, Govoni A, Corti S, Bresolin N, Moggio M, Comi GP. New molecular findings in congenital myopathies due to selenoprotein N gene mutations. J Neurol Sci.

important reference of computational/statistical application in Evo and Eco

These references are mostly recommended by my friend, Jinlong.

1. Phylogeography and Phylogenetics
http://www.utsc.utoronto.ca/~jweir/

2. Statistical method in Ecology
http://www.unc.edu/courses/2010fall/ecol/563/001/index.html
http://www.unc.edu/courses/2010fall/ecol/563/001/docs/lectures.html

3. principals of phylogenetics
http://ib.berkeley.edu/courses/ib200b/IB200B_SyllabusHandouts.shtml

4. phylogenetic comparative methods
http://www2.unil.ch/phylo/teaching/pmc.html

5. Bodega phylogenetic wiki
http://bodegaphylo.wikispot.org/Topics

6. wild evolution group
http://wildevolution.biology.ed.ac.uk/

7. Quantitative Methods in Ecology and Evolution
http://www.zoology.ubc.ca/~schluter/bio548/

8. how to a quantitative ecologist
http://greenmaths.st-andrews.ac.uk/index.aspx

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evolving all we are