Wednesday, June 29, 2016

statistical tests on two arrays of dependent data (time series)

For two list of dependent data X and Y, we want to test X < Y.

The pairwised t-test is inappropriate because it violates independence assumption.

Bootstrap or permutation can only be used when there the list of observations are long.
For our H2O2-LOH dataset, we have only 10 time points (H2O2 doses), so bootstrap and permutation is inappropriate as well.

W Wu suggests that Fisher's exact test can be applied for each time point, and then apply Bonferroni correction. We think 3/4 LOH suggest a positive dependence between 1/2 and 1/4 LOH.



fisher exact test in R, test with proportion input data (not working)

#Q: Does R's default fisher's exact test function handle proportion input data?

mat = matrix(nrow=2,ncol=2)
mat[1,1]=30
mat[2,2]=45
mat[1,2]=5
mat[2,1]=6
mat;
fisher.test(mat)

mat = mat/sum(mat)
mat;
fisher.test(mat)

#conclusion: NO. R's defaulty fisher.test() does not handle proportion input.

Tuesday, June 28, 2016

time series comparison



http://stats.stackexchange.com/questions/25228/testing-for-statistically-significant-difference-in-time-series

https://en.wikipedia.org/wiki/Bland%E2%80%93Altman_plot

http://www.r-bloggers.com/how-to-compare-two-blackbox-timeseries-generators/

Difference DID?
https://www.researchgate.net/post/How_do_I_compare_two_time_series_trends_in_terms_of_magnitude_of_decline_or_increase

binomial aging to Rmd, BY4742 glucose does effect


Byte-4:0a.rls.fitting hqin$ pwd

/Users/hqin/github/0.network.aging.prj.bmc/0a.rls.fitting

$  open 0.BY4742_glucosedose.Rmd


http://hongqinlab.blogspot.com/2014/07/glucose-dose-effect-on-rls-in-by4742.html

Wednesday, June 22, 2016

install CCLE RPackage, version problems, fixed using binary files

install.packages("ggplot2", "scales")

install.packages("gplots", "RColorBrewer", "vioplot", "dplyr", "reshape2", "plyr")

'glmnet' not available for R 3.0.3
Fix this problem by installing the binary tar.gz file r-release: glmnet_2.0-5.tgz from 

install.packages("~/github/JZ_compound/CCLE/RPackage/DRANOVA_1.0.tar.gz", repos = NULL, type = "source")


 install.packages("~/github/JZ_compound/CCLE/RPackage/CCLE.GDSC.compare_1.0.4.tar.gz", repos = NULL, type = "source")

OR

install.packages("~/github/JZ_compound/CCLE/RPackage/CCLE.GDSC.compare_1.0.4.tar.gz", repos = NULL, type = "source", dependencies = TRUE)




Tuesday, June 21, 2016

CCLE, cancer cell cline encyclopedia

Cancer cell line encyclopedia

http://www.broadinstitute.org/ccle/data/browseData?conversationPropagation=begin

After login, there are "published" and "in process" data available for download. These data can also be sent to Genospace (though it did not work for me).

CCLE R codes
http://www.broadinstitute.org/ccle/Rpackage/

From the 2015 nature publications, Elastic nets and Ridge line regressions were used there.

Genomespace:
https://gsui.genomespace.org/jsui/


http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse36139

Friday, June 17, 2016

Measurement and Modeling of Drugs in Tissues (Organized in Cooperation with International Society of Anti-Infective Pharmacology (ISAP))


http://www.abstractsonline.com/pp8/#!/4060/session/147


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SESSION 044-C - Measurement and Modeling of Drugs in Tissues (Organized in Cooperation with International Society of Anti-Infective Pharmacology (ISAP))

 June 17, 2016, 12:45 - 4:15 PM Westin, Grand Ballroom A
Anti-infective pharmacokinetics and pharmacodynamic (PK/PD) modeling traditionally relies on serum or plasma concentration-time data to define exposure-response relationships. Data derived from the blood compartment may or may not accurately reflect target tissue data. This course aims to review current and novel approaches to better quantify target tissue PK/PD. An improved understanding of tissue PK/PD measurement and modeling can help to optimize dosage regimen selection for infections in accessible and restricted compartments.

7 Presentations

12:45 - 4:15 PMWorkshop Convener
David R. Andes; Wisconsin Univ., Madison, WI
12:45 - 4:15 PMWorkshop Convener
Jodi Lestner; Univ. of Liverpool, Liverpool, United Kingdom
12:45 - 4:15 PMWorkshop Faculty
David R. Andes; Wisconsin Univ., Madison, WI
12:45 - 4:15 PMWorkshop Faculty
Jodi Lestner; Univ. of Liverpool, Liverpool, United Kingdom
12:45 - 4:15 PMWorkshop Faculty
Markus Zeitlinger; Med. Univ. Vienna, Vienna, Austria
12:45 - 4:15 PMWorkshop Faculty
George L. Drusano; Univ. of Florida, Lake Nona, FL
12:45 - 4:15 PMWorkshop Speaker
Keith A. Rodvold; Univ. of Illinois at Chicago, Chicago, IL

KBASE, ornl, oak ridge



http://www.abstractsonline.com/pp8/#!/4060/session/58

Robert Cottingham; Oak Ridge Natl. Lab., Oak Ridge, TN
http://computing.ornl.gov/SC08/speakers/cottingham.html



019-WS - Genome-scale Metabolic Modeling of Environmental Isolates and Communities using the DOE Systems Biology Knowledgebase (KBase)

 Itinerary
 June 16, 2016, 8:15 - 4:15 PM BCEC, Meeting Room 252A

The Department of Energy Systems Biology Knowledgebase (KBase, http://kbase.us ) is a software and data platform designed to meet the grand challenge of systems biology: predicting and designing biological function. KBase integrates data, tools, and their associated interfaces into one unified, scalable environment, so users do not need to access them from numerous sources or learn multiple systems in order to perform sophisticated systems biology analyses. Users can perform large-scale analyses and combine multiple lines of evidence to model plant and microbial physiology and community dynamics. KBase is the first large-scale bioinformatics system that enables users to upload their own data, analyze it (along with collaborator and public data), build increasingly realistic models, and share and publish their workflows and conclusions. KBase aims to provide a knowledgebase: an integrated environment where knowledge and insights are created and multiplied.

Monday, June 13, 2016

bioscreen C test run

=> Try to use USB adapter for the COM interface using the original installation. It did not work, because the EasyBioscreen software was configured to the old COM port.

=> Heat transfer tube were mixed with many bubbles. I left the lid screw open, and run the instrument for 25C incubation. After about 30 minutes, large bubbles disappeared. At the same time, I kept adding transfer liquid to fill the volume left by airs.






mixed -80 glycerol stocks at Spelman

Samples in two boxes were mixed. One box is yellow #101. The other is Microbiology lab.

Box 101 is my bacterials stocks. Microbiology stocks is probably also bacterials stocks.


Monday, June 6, 2016

Jo, Dang, Qin PNAS, yeast RLS microfluidic measure

High-throughput analysis of yeast replicative aging using a microfluidic system
Myeong Chan Joa,b, Wei Liuc, Liang Gua, Weiwei Dangc,1, and Lidong Qina,b,1

http://www.pnas.org/content/112/30/9364.abstract

Findings show cell cycle slowed down (cycle time increases dramatically) near the end of survival curve. The author did not quantify the mode of these increase. (The model of increase may be hard due to small number of observations).

TODO: contact the author, asking for original data


Sunday, June 5, 2016

conferences on systems biology, quantitative biology 2017



2017 Annual Meeting of the Society for Mathematical Biology
July 17-21, 2017
University of Utah, Salt Lake City, UT, USA 

Winter QBIO 




References:  https://en.wikipedia.org/wiki/List_of_systems_biology_conferences

http://www.conference-service.com/conferences/mathematical-biology.html

http://www.siam.org/meetings/calendar.php




APBC2017 — The Fifteenth Asia Pacific Bioinformatics Conference
ID
810677
Dates
16 Jan 2017 - 18 Jan 2017
Location
Shenzhen, China
Abstract
The Asia Pacific Bioinformatics Conference (APBC) series, founded in 2003, is an annual international forum for exploring research, development and applications of Bioinformatics and Computational Biology. The Fifteenth Asia-Pacific Bioinformatics Conference, APBC2017, will be held in Shenzhen, China from 16-18 Jan 2017.
Contact
Professor Yi-Ping Phoebe Chen;     Email: Phoebe.Chen@latrobe.edu.au
Topics
Bioinformatics, Computational Biology, Biostatistics, Genomics, Epigenetics, Metagenomics, Transcriptomics, Proteomics, Metabolomics, RNA structure and function, Comparative genomics, Population genetics, Evolution and phylogeny, Protein structure analysis, Systems biology, Synthetic biology, Quantitative biology
Related subject(s)