Genome Analysis Wiki - User contributions [en]

VICES

2019-04-15T13:59:08Z

Gzajac: /* Introduction */

[[Category:Software|VICES]]

= Introduction =

'''VICES''' is a program that jointly estimates the proportion of contaminating DNA in samples genotyped on arrays and which other samples in the study the contaminating DNA came from.

= Download =

'''GitHub Repo:''' [https://github.com/gjmzajac/vices https://github.com/gjmzajac/vices]

'''ZIP archive:''' [https://github.com/gjmzajac/vices/zipball/master/ https://github.com/gjmzajac/vices/zipball/master/]

'''Ubuntu 16.04 x64 Binary''' [[File:vices_v1.0.tar.gz|vices_v1.0.tar.gz]]

= Installation =

The easiest way to install VICES is to use cget as follows:
cget install --prefix <install_prefix> gjmzajac/VICES

Alternatively, you can setup a dev environment cmake directly.
cd vices
cget install -f ./requirements.txt # Install dependencies locally.
mkdir build && cd build # Create out of source build directory.
cmake -DCMAKE_TOOLCHAIN_FILE=./cget/cget/cget.cmake .. # Configure project with dependency paths.
make # Build.

= Usage =
To run,
./vices -r reports_list.txt -o contam_estimates.txt

The reports_list.txt file must list the paths of all the Illumina report files (either plaintext or gzipped) you are testing. All files in a single run must be from the same type and version of array with exactly the same markers. Output will be written to the file contam_estimates.txt.

The output consists of a header (with the number of samples, markers, etc.) then three tab-delimited columns:
*'''Recipient_Index''' the index (starting with 0) of the samples being tested. These are in the same order as in the file with paths to report files provided to VICES. If the --sample-list option is used and points to a file containing sample IDs in the same order as the report files, then this column becomes '''Recipient_ID'''.
*'''Estimated_contamination'''
*'''Sources''' A breakdown of the estimated sources of contamination. Most will have only one source (AF for allele frequencies) because VICES does not perform the donor search for samples with estimated contamination proportion < 0.005 by AF.
Example (simulated) report files and output are provided in the section below

We highly recommend running VICES only within the same batches they were genotyped in as the donor estimation can take a long time if you give it a long list of over 1000 samples. Other reasons to run in batches are that samples genotyped in different runs are probably less likely to have traded DNA, and batch effects may influence the calculation of allele frequencies, an important initial step in VICES. Your sequencing core should provide some information on batches. If you don't have any batch information, then running VICES on one (or at most 20) 96-well plate at a time should also work well.

If any duplicate/twin samples are contaminated, this could bias the results. You might want to consider excluding one of each duplicate/twin pair before running/rerunning.

No external allele frequencies are required. VICES calculates these directly from the report files you provide.

= Options =
-r, --report-list <file> File with paths to Illumina report files
-o, --output <file> Write output to a file [standard output]
-f, --maf-threshold <float> Min minor allele frequency for markers
-c, --contam-threshold <float> Threshold for estimating donor samples
-s, --sample-list <file> File with sample ids for report files
-a, --af-only Specify analysis with AF only. No donor estimation
-n, --snp-name-col <string> Name of report file column containing SNP names
-1, --allele1-col <string> Name of report file column containing allele 1
-2, --allele2-col <string> Name of report file column containing allele 2
-b, --b-allele-intensity-col <string> Name of report file column containing B allele intensity
-m, --num-markers <int> Maximum number of markers for contamination estimation
-t, --threads <int> Number of threads for parallel computation
-h, --help This help page

= VICES Example =
'''Download Sample Files''' [[File:vices_test.zip|vices_test.zip]]

'''Basic Command''' from within the directory with the example files:
~/vices/build/vices -r vices.test.report.list.txt -s vices.test.report.iids.txt -o vices.test.report.contam.txt

'''Expected Output''' in vices.test.report.contam.txt:
Recipient_ID Estimated_contamination Sources
iid_01 0.0107758 AF:0.00351165; Donor_iid_02:0.00726419
iid_02 0.0371312 Donor_iid_01:0.0187088; Donor_iid_03:0.0184223
iid_03 0.0791742 Donor_iid_01:0.0236221; Donor_iid_02:0.0165325; Donor_iid_08:0.0390197
iid_04 0.0158945 AF:0.0158945
iid_05 0.0535897 AF:0.025121; Donor_iid_04:0.0284687
iid_06 0.0740575 AF:0.0346833; Donor_iid_04:0.0117261; Donor_iid_10:0.0276482
iid_07 0.00551559 AF:0.00551559
iid_08 -0.00673222 AF:-0.00673222
iid_09 0.000255342 AF:0.000255342
iid_10 9.90153e-05 AF:9.90153e-05
iid_11 -0.00138426 AF:-0.00138426
iid_12 -0.00588946 AF:-0.00588946

= Citation =
A paper is in the works and should be published soon. For now, you can cite our abstract from the 2017 Biology of Genomes meeting
* G. J. M. Zajac, L. G. Fritsche, S. L. Dagenais, R. H. Lyons, C. M. Brummett, & G. Abecasis. ''VICES: Verify Intensity Contamination from Estimated Sources.'' Poster Session presented at: The Biology of Genomes; 2017 May 9-13; Cold Spring Harbor, NY.

= Contact =
For questions or bug reports, email gzajac at umich.edu

= Need Something Else? =
More Software: [[ContaminationDetection]]

VICES

2019-04-12T17:49:49Z

Gzajac: /* VICES Example */

[[Category:Software|VICES]]

= Introduction =

'''VICES''' is a program that jointly estimates the proportion of contaminating DNA in samples genotyped on arrays and which other samples in the study it came from.

= Download =

'''GitHub Repo:''' [https://github.com/gjmzajac/vices https://github.com/gjmzajac/vices]

'''ZIP archive:''' [https://github.com/gjmzajac/vices/zipball/master/ https://github.com/gjmzajac/vices/zipball/master/]

'''Ubuntu 16.04 x64 Binary''' [[File:vices_v1.0.tar.gz|vices_v1.0.tar.gz]]

= Installation =

The easiest way to install VICES is to use cget as follows:
cget install --prefix <install_prefix> gjmzajac/VICES

Alternatively, you can setup a dev environment cmake directly.
cd vices
cget install -f ./requirements.txt # Install dependencies locally.
mkdir build && cd build # Create out of source build directory.
cmake -DCMAKE_TOOLCHAIN_FILE=./cget/cget/cget.cmake .. # Configure project with dependency paths.
make # Build.

= Usage =
To run,
./vices -r reports_list.txt -o contam_estimates.txt

The reports_list.txt file must list the paths of all the Illumina report files (either plaintext or gzipped) you are testing. All files in a single run must be from the same type and version of array with exactly the same markers. Output will be written to the file contam_estimates.txt.

The output consists of a header (with the number of samples, markers, etc.) then three tab-delimited columns:
*'''Recipient_Index''' the index (starting with 0) of the samples being tested. These are in the same order as in the file with paths to report files provided to VICES. If the --sample-list option is used and points to a file containing sample IDs in the same order as the report files, then this column becomes '''Recipient_ID'''.
*'''Estimated_contamination'''
*'''Sources''' A breakdown of the estimated sources of contamination. Most will have only one source (AF for allele frequencies) because VICES does not perform the donor search for samples with estimated contamination proportion < 0.005 by AF.
Example (simulated) report files and output are provided in the section below

We highly recommend running VICES only within the same batches they were genotyped in as the donor estimation can take a long time if you give it a long list of over 1000 samples. Other reasons to run in batches are that samples genotyped in different runs are probably less likely to have traded DNA, and batch effects may influence the calculation of allele frequencies, an important initial step in VICES. Your sequencing core should provide some information on batches. If you don't have any batch information, then running VICES on one (or at most 20) 96-well plate at a time should also work well.

If any duplicate/twin samples are contaminated, this could bias the results. You might want to consider excluding one of each duplicate/twin pair before running/rerunning.

No external allele frequencies are required. VICES calculates these directly from the report files you provide.

= Options =
-r, --report-list <file> File with paths to Illumina report files
-o, --output <file> Write output to a file [standard output]
-f, --maf-threshold <float> Min minor allele frequency for markers
-c, --contam-threshold <float> Threshold for estimating donor samples
-s, --sample-list <file> File with sample ids for report files
-a, --af-only Specify analysis with AF only. No donor estimation
-n, --snp-name-col <string> Name of report file column containing SNP names
-1, --allele1-col <string> Name of report file column containing allele 1
-2, --allele2-col <string> Name of report file column containing allele 2
-b, --b-allele-intensity-col <string> Name of report file column containing B allele intensity
-m, --num-markers <int> Maximum number of markers for contamination estimation
-t, --threads <int> Number of threads for parallel computation
-h, --help This help page

= VICES Example =
'''Download Sample Files''' [[File:vices_test.zip|vices_test.zip]]

'''Basic Command''' from within the directory with the example files:
~/vices/build/vices -r vices.test.report.list.txt -s vices.test.report.iids.txt -o vices.test.report.contam.txt

'''Expected Output''' in vices.test.report.contam.txt:
Recipient_ID Estimated_contamination Sources
iid_01 0.0107758 AF:0.00351165; Donor_iid_02:0.00726419
iid_02 0.0371312 Donor_iid_01:0.0187088; Donor_iid_03:0.0184223
iid_03 0.0791742 Donor_iid_01:0.0236221; Donor_iid_02:0.0165325; Donor_iid_08:0.0390197
iid_04 0.0158945 AF:0.0158945
iid_05 0.0535897 AF:0.025121; Donor_iid_04:0.0284687
iid_06 0.0740575 AF:0.0346833; Donor_iid_04:0.0117261; Donor_iid_10:0.0276482
iid_07 0.00551559 AF:0.00551559
iid_08 -0.00673222 AF:-0.00673222
iid_09 0.000255342 AF:0.000255342
iid_10 9.90153e-05 AF:9.90153e-05
iid_11 -0.00138426 AF:-0.00138426
iid_12 -0.00588946 AF:-0.00588946

= Citation =
A paper is in the works and should be published soon. For now, you can cite our abstract from the 2017 Biology of Genomes meeting
* G. J. M. Zajac, L. G. Fritsche, S. L. Dagenais, R. H. Lyons, C. M. Brummett, & G. Abecasis. ''VICES: Verify Intensity Contamination from Estimated Sources.'' Poster Session presented at: The Biology of Genomes; 2017 May 9-13; Cold Spring Harbor, NY.

= Contact =
For questions or bug reports, email gzajac at umich.edu

= Need Something Else? =
More Software: [[ContaminationDetection]]

VICES

2019-04-12T17:49:27Z

Gzajac: /* VICES Example */

[[Category:Software|VICES]]

= Introduction =

'''VICES''' is a program that jointly estimates the proportion of contaminating DNA in samples genotyped on arrays and which other samples in the study it came from.

= Download =

'''GitHub Repo:''' [https://github.com/gjmzajac/vices https://github.com/gjmzajac/vices]

'''ZIP archive:''' [https://github.com/gjmzajac/vices/zipball/master/ https://github.com/gjmzajac/vices/zipball/master/]

'''Ubuntu 16.04 x64 Binary''' [[File:vices_v1.0.tar.gz|vices_v1.0.tar.gz]]

= Installation =

The easiest way to install VICES is to use cget as follows:
cget install --prefix <install_prefix> gjmzajac/VICES

Alternatively, you can setup a dev environment cmake directly.
cd vices
cget install -f ./requirements.txt # Install dependencies locally.
mkdir build && cd build # Create out of source build directory.
cmake -DCMAKE_TOOLCHAIN_FILE=./cget/cget/cget.cmake .. # Configure project with dependency paths.
make # Build.

= Usage =
To run,
./vices -r reports_list.txt -o contam_estimates.txt

The reports_list.txt file must list the paths of all the Illumina report files (either plaintext or gzipped) you are testing. All files in a single run must be from the same type and version of array with exactly the same markers. Output will be written to the file contam_estimates.txt.

The output consists of a header (with the number of samples, markers, etc.) then three tab-delimited columns:
*'''Recipient_Index''' the index (starting with 0) of the samples being tested. These are in the same order as in the file with paths to report files provided to VICES. If the --sample-list option is used and points to a file containing sample IDs in the same order as the report files, then this column becomes '''Recipient_ID'''.
*'''Estimated_contamination'''
*'''Sources''' A breakdown of the estimated sources of contamination. Most will have only one source (AF for allele frequencies) because VICES does not perform the donor search for samples with estimated contamination proportion < 0.005 by AF.
Example (simulated) report files and output are provided in the section below

We highly recommend running VICES only within the same batches they were genotyped in as the donor estimation can take a long time if you give it a long list of over 1000 samples. Other reasons to run in batches are that samples genotyped in different runs are probably less likely to have traded DNA, and batch effects may influence the calculation of allele frequencies, an important initial step in VICES. Your sequencing core should provide some information on batches. If you don't have any batch information, then running VICES on one (or at most 20) 96-well plate at a time should also work well.

If any duplicate/twin samples are contaminated, this could bias the results. You might want to consider excluding one of each duplicate/twin pair before running/rerunning.

No external allele frequencies are required. VICES calculates these directly from the report files you provide.

= Options =
-r, --report-list <file> File with paths to Illumina report files
-o, --output <file> Write output to a file [standard output]
-f, --maf-threshold <float> Min minor allele frequency for markers
-c, --contam-threshold <float> Threshold for estimating donor samples
-s, --sample-list <file> File with sample ids for report files
-a, --af-only Specify analysis with AF only. No donor estimation
-n, --snp-name-col <string> Name of report file column containing SNP names
-1, --allele1-col <string> Name of report file column containing allele 1
-2, --allele2-col <string> Name of report file column containing allele 2
-b, --b-allele-intensity-col <string> Name of report file column containing B allele intensity
-m, --num-markers <int> Maximum number of markers for contamination estimation
-t, --threads <int> Number of threads for parallel computation
-h, --help This help page

= VICES Example =
'''Download Sample Files''' [[File:vices_test.zip|vices_test.zip]]

'''Basic Command''' from within the directory with the example files:
~/vices/build/vices -r vices.test.report.list.txt -s vices.test.report.iids.txt -o vices.test.report.contam.txt

Expected Output _:
Recipient_ID Estimated_contamination Sources
iid_01 0.0107758 AF:0.00351165; Donor_iid_02:0.00726419
iid_02 0.0371312 Donor_iid_01:0.0187088; Donor_iid_03:0.0184223
iid_03 0.0791742 Donor_iid_01:0.0236221; Donor_iid_02:0.0165325; Donor_iid_08:0.0390197
iid_04 0.0158945 AF:0.0158945
iid_05 0.0535897 AF:0.025121; Donor_iid_04:0.0284687
iid_06 0.0740575 AF:0.0346833; Donor_iid_04:0.0117261; Donor_iid_10:0.0276482
iid_07 0.00551559 AF:0.00551559
iid_08 -0.00673222 AF:-0.00673222
iid_09 0.000255342 AF:0.000255342
iid_10 9.90153e-05 AF:9.90153e-05
iid_11 -0.00138426 AF:-0.00138426
iid_12 -0.00588946 AF:-0.00588946

= Citation =
A paper is in the works and should be published soon. For now, you can cite our abstract from the 2017 Biology of Genomes meeting
* G. J. M. Zajac, L. G. Fritsche, S. L. Dagenais, R. H. Lyons, C. M. Brummett, & G. Abecasis. ''VICES: Verify Intensity Contamination from Estimated Sources.'' Poster Session presented at: The Biology of Genomes; 2017 May 9-13; Cold Spring Harbor, NY.

= Contact =
For questions or bug reports, email gzajac at umich.edu

= Need Something Else? =
More Software: [[ContaminationDetection]]

2019-04-12T15:23:13Z

Gzajac: Gzajac uploaded a new version of File:Vices v1.0.tar.gz

2017-04-18T05:49:03Z

Gzajac:

Biostatistics 866: Main Page

2017-04-18T05:48:05Z

Gzajac: /* Student Presentations */

== Objective ==

Gene mapping studies study the relationship between genetic variation and susceptibility to human disease. These studies are changing rapidly with the availability of techniques for very large scale genetic analysis, whether based on sequencing or on genotyping. Biostatistics 866 is a Ph.D. level course that helps students understand some of the key building blocks of modern genetic analysis tools. It is meant to provide students with a toolkit to facilitate development and implementation of new statistical methods.

For additional information, see also [[Biostatistics 866: Core Competencies|Core Competencies in Biostatistics Program covered by this course]].

== Target Audience ==

It is highly recommended that students registering for Biostatistics 830 should have previously completed [[Biostatistics 666]] and [[Biostatistics 615/815]], which are courses introducing methods for genetic analysis and programming principles, respectively.

== Scheduling ==

For Winter 2017, classes are scheduled for Tuesdays and Thursdays, 8:30 - 10 am in SPH II, room 1152.

== Grading ==

The final grade will take into account your performance in problem sets and worksheets as well as your participation in class.

== Class Worksheets ==

=== Hidden Markov Models ===

Week of January 8 - [[Media:Question_Sheet_-_Li_et_al_(2010)_Gen_Epid.pdf|Li et al (2010)]]

Week of January 15 - [[Media:Question_Sheet_-_Howie_et_al_(2012)_Nat_Genet.pdf|Howie et al (2012)]] (and, [[Media:866_-_Slides_for_Hyun.pdf|Discussion slides for January 19]])

Week of January 22 - [[Media:Question_Sheet_-_Delaneau_et_al_(2013)_Nature_Methods.pdf|Delaneau et al (2013)]]

Week of January 29 - [[Media:Question_Sheet_-_Boehnke_and_Cox_(1997)_AJHG.pdf|Boehnke and Cox (1997)]]

=== Short Read Sequencing ===

February 12 - [[Media:Question_Sheet_-_Li_et_al_(2008)_Genome_Research.pdf|Li et al (2008)]]

February 19 - [[Media:Question_Sheet_-_Li_and_Durbin_(2009)_Bioinformatics.pdf|Li and Durbin (2009)]]

March 5 - [[Media:Question_Sheet_-_Zerbino_and_Birney_(2008)_Bioinformatics.pdf|Zerbino and Birney (2008)]]

March 12 - [[Media:Question_Sheet_-_Iqbal_et_al_(2012)_Nature_Genetics.pdf|Iqbal et al (2012)]]

=== Association Analysis ===

March 19 - [[Media:Question_Sheet_-_2017_-_Kang_et_al_(2010)_Nature_Genetics_.pdf|Kang et al (2010)]]

March 26 - [[Media:Question_Sheet_-_2017_-_Wu_et_al_(2011)_American_Journal_of_Human_Genetics.pdf|Wu et al (2011)]]

April 2 - [[Media:Question_Sheet_-_2017_-_Liu_et_al_(2013)_Nature_Genetics.pdf|Liu et al (2014)]]

=== Adventures in Statistical Genetics ===

April 9 - [[Media:2017.04_-_Adventures_in_Human_Genetics.pdf|Goncalo's Adventure in Human Genetics]]

== Student Presentations ==
[[File:Zajac_Journey_Lecture.pdf | Greg]]

== Standards of Academic Conduct ==

The following is an extract from the School of Public Health's Student Code of Conduct [http://www.sph.umich.edu/academics/policies/conduct.html]:

''Student academic misconduct includes behavior involving plagiarism, cheating, fabrication, falsification of records or official documents, intentional misuse of equipment or materials, and aiding and abetting the perpetration of such acts. The preparation of reports, papers, and examinations, assigned on an individual basis, must represent each student’s own effort. Reference sources should be indicated clearly. The use of assistance from other students or aids of any kind during a written examination, except when the use of books or notes has been approved by an instructor, is a violation of the standard of academic conduct.''

In the context of this course, any work you hand-in should be your own and any material that is a transcript (or interpreted transcript) of work by others must be clearly labeled as such. If you turn in work that is directly copied from another student or from a published or unpublished source without attribution, you risk failing the course.

== Planned Reading ==

* Abecasis GR, Cherny SS, Cookson WO, Cardon LR (2002) Merlin--rapid analysis of dense genetic maps using sparse gene flow trees. ''Nat Genetics'' '''30''':97-101

* Boehnke M and Cox N (1997) Accurate Inference of Relationships in Sib-Pair Linkage Studies. ''Am J Hum Genet'' '''61''':423-429

* Coventry A, Bull-Otterson LM, Liu X, Clark AG, Maxwell TJ, Crosby J, Hixson JE, Rea TJ, Muzny DM, Lewis LR, Wheeler DA, Sabo A, Lusk C, Weiss KG, Akbar H, Cree A, Hawes AC, Newsham I, Varghese RT, Villasana D, Gross S, Joshi V, Santibanez J, Morgan M, Chang K, Iv WH, Templeton AR, Boerwinkle E, Gibbs R, Sing CF (2010) Deep resequencing reveals excess rare recent variants consistent with explosive population growth. ''Nat Commun.'' '''1''':131. PMID: 21119644

* Delaneau O, Zagury JF, Marchini J (2013) Improved whole-chromosome phasing for disease and population genetic studies. ''Nat Methods.'' '''10''':5-6. PMID: 23269371

* Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR (2012) Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. ''Nat Genet.'' '''44''':955-9. PMID: 22820512 [[Biostatistics 830 - Code Snippets|[Code Snippets]]]

* Iqbal Z, Caccamo M, Turner I, Flicek P, McVean G (2012) De novo assembly and genotyping of variants using colored de Bruijn graphs. ''Nat Genet.'' '''44''':226-32. PMID: 22231483

* Field Y, Boyle EA, Telis N, Gao Z, Gaulton KJ, Golan D, Yengo L, Rocheleau G, Froguel P, McCarthy MI, Pritchard JK (2016) Detection of human adaptation during the past 2000 years. ''Science'' '''354''':760-764

* Jun G, Flickinger M, Hetrick KN, Romm JM, Doheny KF, Abecasis GR, Boehnke M, Kang HM (2012) Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data. ''Am J Hum Genet.'' '''91''':839-48. PMID: 23103226

* Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, Sabatti C, Eskin E (2010) Variance component model to account for sample structure in genome-wide association studies. ''Nat. Genet.'' '''42''':348-354

* Kircher M, Witten DM, Jain P, O'Roak BJ, Cooper GM, Shendure J (2014) A general framework for estimating the relative pathogenicity of human genetic variants. ''Nat. Genet.'' '''46''' 310–315

* Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES (1996) Parametric and non-parametric linkage analysis: a unified multipoint approach. ''Am J Hum Genet'' '''58''':1347-63

* Li H, Ruan J, Durbin R (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. ''Genome Res.'' '''18''':1851-8. PMID: 18714091

* Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. ''Bioinformatics.'' '''25''':1754-60. PMID: 19451168

* Li H, Durbin R (2011) Inference of human population history from individual whole-genome sequences. ''Nature.'' '''475''':493-6. PMID: 21753753

* Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR (2010) MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. ''Genet Epidemiol.'' '''34''':816-34. PMID: 21058334 [[Biostatistics 830 - Code Snippets|[Code Snippets]]]

* Lin DY, Zeng D (2010) Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data. ''Genet Epidemiol.'' '''34''':60-6. PMID: 19847795

* Liu DJ, Peloso GM, Zhan X, Holmen OL, Zawistowski M, Feng S, Nikpay M, Auer PL, Goel A, Zhang H, Peters U, Farrall M, Orho-Melander M, Kooperberg C, McPherson R, Watkins H, Willer CJ, Hveem K, Melander O, Kathiresan S, Abecasis GR (2014) Meta-analysis of gene-level tests for rare variant association. ''Nat Genet.'' '''46''':200-4

* Sobel E, Lange K (1996) Descent Graphs in Pedigree Analysis: Applications to Haplotyping, Location Scores, and Marker-Sharing Statistics. ''Am. J. Hum. Genet.'' '''58''':1323-1336

* Wang C, Zhan X, Bragg-Gresham J, Kang HM, Stambolian D, Chew EY, Branham KE, Heckenlively J; FUSION Study, Fulton R, Wilson RK, Mardis ER, Lin X, Swaroop A, Zöllner S, Abecasis GR (2014) Ancestry estimation and control of population stratification for sequence-based association studies. ''Nat Genet. 2014'' '''46''':409-15

* Wen X, Stephens M (2010) Using linear predictors to impute allele frequencies from summary or pooled genotype data. ''Ann Appl Stat.'' '''4''':1158-1182. PMID: 21479081

* Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X (2011) Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet. 89:82-93

* Zerbino DR, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. ''Genome Res.'' '''18''':821-9. PMID: 18349386

== Course History ==

This course is offered occasionally. Typically, Mike Boehnke has taught it. Each instructor gives the course a different flavor, so you may find it worthwhile -- even if you have taken the course with Mike previously.

Biostatistics 866: Main Page

2017-04-18T05:47:25Z

Gzajac: /* Student Presentations */

== Objective ==

Gene mapping studies study the relationship between genetic variation and susceptibility to human disease. These studies are changing rapidly with the availability of techniques for very large scale genetic analysis, whether based on sequencing or on genotyping. Biostatistics 866 is a Ph.D. level course that helps students understand some of the key building blocks of modern genetic analysis tools. It is meant to provide students with a toolkit to facilitate development and implementation of new statistical methods.

For additional information, see also [[Biostatistics 866: Core Competencies|Core Competencies in Biostatistics Program covered by this course]].

== Target Audience ==

It is highly recommended that students registering for Biostatistics 830 should have previously completed [[Biostatistics 666]] and [[Biostatistics 615/815]], which are courses introducing methods for genetic analysis and programming principles, respectively.

== Scheduling ==

For Winter 2017, classes are scheduled for Tuesdays and Thursdays, 8:30 - 10 am in SPH II, room 1152.

== Grading ==

The final grade will take into account your performance in problem sets and worksheets as well as your participation in class.

== Class Worksheets ==

=== Hidden Markov Models ===

Week of January 8 - [[Media:Question_Sheet_-_Li_et_al_(2010)_Gen_Epid.pdf|Li et al (2010)]]

Week of January 15 - [[Media:Question_Sheet_-_Howie_et_al_(2012)_Nat_Genet.pdf|Howie et al (2012)]] (and, [[Media:866_-_Slides_for_Hyun.pdf|Discussion slides for January 19]])

Week of January 22 - [[Media:Question_Sheet_-_Delaneau_et_al_(2013)_Nature_Methods.pdf|Delaneau et al (2013)]]

Week of January 29 - [[Media:Question_Sheet_-_Boehnke_and_Cox_(1997)_AJHG.pdf|Boehnke and Cox (1997)]]

=== Short Read Sequencing ===

February 12 - [[Media:Question_Sheet_-_Li_et_al_(2008)_Genome_Research.pdf|Li et al (2008)]]

February 19 - [[Media:Question_Sheet_-_Li_and_Durbin_(2009)_Bioinformatics.pdf|Li and Durbin (2009)]]

March 5 - [[Media:Question_Sheet_-_Zerbino_and_Birney_(2008)_Bioinformatics.pdf|Zerbino and Birney (2008)]]

March 12 - [[Media:Question_Sheet_-_Iqbal_et_al_(2012)_Nature_Genetics.pdf|Iqbal et al (2012)]]

=== Association Analysis ===

March 19 - [[Media:Question_Sheet_-_2017_-_Kang_et_al_(2010)_Nature_Genetics_.pdf|Kang et al (2010)]]

March 26 - [[Media:Question_Sheet_-_2017_-_Wu_et_al_(2011)_American_Journal_of_Human_Genetics.pdf|Wu et al (2011)]]

April 2 - [[Media:Question_Sheet_-_2017_-_Liu_et_al_(2013)_Nature_Genetics.pdf|Liu et al (2014)]]

=== Adventures in Statistical Genetics ===

April 9 - [[Media:2017.04_-_Adventures_in_Human_Genetics.pdf|Goncalo's Adventure in Human Genetics]]

== Student Presentations ==
[[File:Zajac_Journey_Lecture.pdf] Greg]

== Standards of Academic Conduct ==

The following is an extract from the School of Public Health's Student Code of Conduct [http://www.sph.umich.edu/academics/policies/conduct.html]:

''Student academic misconduct includes behavior involving plagiarism, cheating, fabrication, falsification of records or official documents, intentional misuse of equipment or materials, and aiding and abetting the perpetration of such acts. The preparation of reports, papers, and examinations, assigned on an individual basis, must represent each student’s own effort. Reference sources should be indicated clearly. The use of assistance from other students or aids of any kind during a written examination, except when the use of books or notes has been approved by an instructor, is a violation of the standard of academic conduct.''

In the context of this course, any work you hand-in should be your own and any material that is a transcript (or interpreted transcript) of work by others must be clearly labeled as such. If you turn in work that is directly copied from another student or from a published or unpublished source without attribution, you risk failing the course.

== Planned Reading ==

* Abecasis GR, Cherny SS, Cookson WO, Cardon LR (2002) Merlin--rapid analysis of dense genetic maps using sparse gene flow trees. ''Nat Genetics'' '''30''':97-101

* Boehnke M and Cox N (1997) Accurate Inference of Relationships in Sib-Pair Linkage Studies. ''Am J Hum Genet'' '''61''':423-429

* Coventry A, Bull-Otterson LM, Liu X, Clark AG, Maxwell TJ, Crosby J, Hixson JE, Rea TJ, Muzny DM, Lewis LR, Wheeler DA, Sabo A, Lusk C, Weiss KG, Akbar H, Cree A, Hawes AC, Newsham I, Varghese RT, Villasana D, Gross S, Joshi V, Santibanez J, Morgan M, Chang K, Iv WH, Templeton AR, Boerwinkle E, Gibbs R, Sing CF (2010) Deep resequencing reveals excess rare recent variants consistent with explosive population growth. ''Nat Commun.'' '''1''':131. PMID: 21119644

* Delaneau O, Zagury JF, Marchini J (2013) Improved whole-chromosome phasing for disease and population genetic studies. ''Nat Methods.'' '''10''':5-6. PMID: 23269371

* Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR (2012) Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. ''Nat Genet.'' '''44''':955-9. PMID: 22820512 [[Biostatistics 830 - Code Snippets|[Code Snippets]]]

* Iqbal Z, Caccamo M, Turner I, Flicek P, McVean G (2012) De novo assembly and genotyping of variants using colored de Bruijn graphs. ''Nat Genet.'' '''44''':226-32. PMID: 22231483

* Field Y, Boyle EA, Telis N, Gao Z, Gaulton KJ, Golan D, Yengo L, Rocheleau G, Froguel P, McCarthy MI, Pritchard JK (2016) Detection of human adaptation during the past 2000 years. ''Science'' '''354''':760-764

* Jun G, Flickinger M, Hetrick KN, Romm JM, Doheny KF, Abecasis GR, Boehnke M, Kang HM (2012) Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data. ''Am J Hum Genet.'' '''91''':839-48. PMID: 23103226

* Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, Sabatti C, Eskin E (2010) Variance component model to account for sample structure in genome-wide association studies. ''Nat. Genet.'' '''42''':348-354

* Kircher M, Witten DM, Jain P, O'Roak BJ, Cooper GM, Shendure J (2014) A general framework for estimating the relative pathogenicity of human genetic variants. ''Nat. Genet.'' '''46''' 310–315

* Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES (1996) Parametric and non-parametric linkage analysis: a unified multipoint approach. ''Am J Hum Genet'' '''58''':1347-63

* Li H, Ruan J, Durbin R (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. ''Genome Res.'' '''18''':1851-8. PMID: 18714091

* Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. ''Bioinformatics.'' '''25''':1754-60. PMID: 19451168

* Li H, Durbin R (2011) Inference of human population history from individual whole-genome sequences. ''Nature.'' '''475''':493-6. PMID: 21753753

* Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR (2010) MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. ''Genet Epidemiol.'' '''34''':816-34. PMID: 21058334 [[Biostatistics 830 - Code Snippets|[Code Snippets]]]

* Lin DY, Zeng D (2010) Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data. ''Genet Epidemiol.'' '''34''':60-6. PMID: 19847795

* Liu DJ, Peloso GM, Zhan X, Holmen OL, Zawistowski M, Feng S, Nikpay M, Auer PL, Goel A, Zhang H, Peters U, Farrall M, Orho-Melander M, Kooperberg C, McPherson R, Watkins H, Willer CJ, Hveem K, Melander O, Kathiresan S, Abecasis GR (2014) Meta-analysis of gene-level tests for rare variant association. ''Nat Genet.'' '''46''':200-4

* Sobel E, Lange K (1996) Descent Graphs in Pedigree Analysis: Applications to Haplotyping, Location Scores, and Marker-Sharing Statistics. ''Am. J. Hum. Genet.'' '''58''':1323-1336

* Wang C, Zhan X, Bragg-Gresham J, Kang HM, Stambolian D, Chew EY, Branham KE, Heckenlively J; FUSION Study, Fulton R, Wilson RK, Mardis ER, Lin X, Swaroop A, Zöllner S, Abecasis GR (2014) Ancestry estimation and control of population stratification for sequence-based association studies. ''Nat Genet. 2014'' '''46''':409-15

* Wen X, Stephens M (2010) Using linear predictors to impute allele frequencies from summary or pooled genotype data. ''Ann Appl Stat.'' '''4''':1158-1182. PMID: 21479081

* Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X (2011) Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet. 89:82-93

* Zerbino DR, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. ''Genome Res.'' '''18''':821-9. PMID: 18349386

== Course History ==

This course is offered occasionally. Typically, Mike Boehnke has taught it. Each instructor gives the course a different flavor, so you may find it worthwhile -- even if you have taken the course with Mike previously.

Biostatistics 866: Main Page

2017-04-18T05:47:08Z

Gzajac: /* Student Presentations */

== Objective ==

Gene mapping studies study the relationship between genetic variation and susceptibility to human disease. These studies are changing rapidly with the availability of techniques for very large scale genetic analysis, whether based on sequencing or on genotyping. Biostatistics 866 is a Ph.D. level course that helps students understand some of the key building blocks of modern genetic analysis tools. It is meant to provide students with a toolkit to facilitate development and implementation of new statistical methods.

For additional information, see also [[Biostatistics 866: Core Competencies|Core Competencies in Biostatistics Program covered by this course]].

== Target Audience ==

It is highly recommended that students registering for Biostatistics 830 should have previously completed [[Biostatistics 666]] and [[Biostatistics 615/815]], which are courses introducing methods for genetic analysis and programming principles, respectively.

== Scheduling ==

For Winter 2017, classes are scheduled for Tuesdays and Thursdays, 8:30 - 10 am in SPH II, room 1152.

== Grading ==

The final grade will take into account your performance in problem sets and worksheets as well as your participation in class.

== Class Worksheets ==

=== Hidden Markov Models ===

Week of January 8 - [[Media:Question_Sheet_-_Li_et_al_(2010)_Gen_Epid.pdf|Li et al (2010)]]

Week of January 15 - [[Media:Question_Sheet_-_Howie_et_al_(2012)_Nat_Genet.pdf|Howie et al (2012)]] (and, [[Media:866_-_Slides_for_Hyun.pdf|Discussion slides for January 19]])

Week of January 22 - [[Media:Question_Sheet_-_Delaneau_et_al_(2013)_Nature_Methods.pdf|Delaneau et al (2013)]]

Week of January 29 - [[Media:Question_Sheet_-_Boehnke_and_Cox_(1997)_AJHG.pdf|Boehnke and Cox (1997)]]

=== Short Read Sequencing ===

February 12 - [[Media:Question_Sheet_-_Li_et_al_(2008)_Genome_Research.pdf|Li et al (2008)]]

February 19 - [[Media:Question_Sheet_-_Li_and_Durbin_(2009)_Bioinformatics.pdf|Li and Durbin (2009)]]

March 5 - [[Media:Question_Sheet_-_Zerbino_and_Birney_(2008)_Bioinformatics.pdf|Zerbino and Birney (2008)]]

March 12 - [[Media:Question_Sheet_-_Iqbal_et_al_(2012)_Nature_Genetics.pdf|Iqbal et al (2012)]]

=== Association Analysis ===

March 19 - [[Media:Question_Sheet_-_2017_-_Kang_et_al_(2010)_Nature_Genetics_.pdf|Kang et al (2010)]]

March 26 - [[Media:Question_Sheet_-_2017_-_Wu_et_al_(2011)_American_Journal_of_Human_Genetics.pdf|Wu et al (2011)]]

April 2 - [[Media:Question_Sheet_-_2017_-_Liu_et_al_(2013)_Nature_Genetics.pdf|Liu et al (2014)]]

=== Adventures in Statistical Genetics ===

April 9 - [[Media:2017.04_-_Adventures_in_Human_Genetics.pdf|Goncalo's Adventure in Human Genetics]]

== Student Presentations ==
[[Greg File:Zajac_Journey_Lecture.pdf]]

== Standards of Academic Conduct ==

The following is an extract from the School of Public Health's Student Code of Conduct [http://www.sph.umich.edu/academics/policies/conduct.html]:

''Student academic misconduct includes behavior involving plagiarism, cheating, fabrication, falsification of records or official documents, intentional misuse of equipment or materials, and aiding and abetting the perpetration of such acts. The preparation of reports, papers, and examinations, assigned on an individual basis, must represent each student’s own effort. Reference sources should be indicated clearly. The use of assistance from other students or aids of any kind during a written examination, except when the use of books or notes has been approved by an instructor, is a violation of the standard of academic conduct.''

In the context of this course, any work you hand-in should be your own and any material that is a transcript (or interpreted transcript) of work by others must be clearly labeled as such. If you turn in work that is directly copied from another student or from a published or unpublished source without attribution, you risk failing the course.

== Planned Reading ==

* Abecasis GR, Cherny SS, Cookson WO, Cardon LR (2002) Merlin--rapid analysis of dense genetic maps using sparse gene flow trees. ''Nat Genetics'' '''30''':97-101

* Boehnke M and Cox N (1997) Accurate Inference of Relationships in Sib-Pair Linkage Studies. ''Am J Hum Genet'' '''61''':423-429

* Coventry A, Bull-Otterson LM, Liu X, Clark AG, Maxwell TJ, Crosby J, Hixson JE, Rea TJ, Muzny DM, Lewis LR, Wheeler DA, Sabo A, Lusk C, Weiss KG, Akbar H, Cree A, Hawes AC, Newsham I, Varghese RT, Villasana D, Gross S, Joshi V, Santibanez J, Morgan M, Chang K, Iv WH, Templeton AR, Boerwinkle E, Gibbs R, Sing CF (2010) Deep resequencing reveals excess rare recent variants consistent with explosive population growth. ''Nat Commun.'' '''1''':131. PMID: 21119644

* Delaneau O, Zagury JF, Marchini J (2013) Improved whole-chromosome phasing for disease and population genetic studies. ''Nat Methods.'' '''10''':5-6. PMID: 23269371

* Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR (2012) Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. ''Nat Genet.'' '''44''':955-9. PMID: 22820512 [[Biostatistics 830 - Code Snippets|[Code Snippets]]]

* Iqbal Z, Caccamo M, Turner I, Flicek P, McVean G (2012) De novo assembly and genotyping of variants using colored de Bruijn graphs. ''Nat Genet.'' '''44''':226-32. PMID: 22231483

* Field Y, Boyle EA, Telis N, Gao Z, Gaulton KJ, Golan D, Yengo L, Rocheleau G, Froguel P, McCarthy MI, Pritchard JK (2016) Detection of human adaptation during the past 2000 years. ''Science'' '''354''':760-764

* Jun G, Flickinger M, Hetrick KN, Romm JM, Doheny KF, Abecasis GR, Boehnke M, Kang HM (2012) Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data. ''Am J Hum Genet.'' '''91''':839-48. PMID: 23103226

* Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, Sabatti C, Eskin E (2010) Variance component model to account for sample structure in genome-wide association studies. ''Nat. Genet.'' '''42''':348-354

* Kircher M, Witten DM, Jain P, O'Roak BJ, Cooper GM, Shendure J (2014) A general framework for estimating the relative pathogenicity of human genetic variants. ''Nat. Genet.'' '''46''' 310–315

* Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES (1996) Parametric and non-parametric linkage analysis: a unified multipoint approach. ''Am J Hum Genet'' '''58''':1347-63

* Li H, Ruan J, Durbin R (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. ''Genome Res.'' '''18''':1851-8. PMID: 18714091

* Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. ''Bioinformatics.'' '''25''':1754-60. PMID: 19451168

* Li H, Durbin R (2011) Inference of human population history from individual whole-genome sequences. ''Nature.'' '''475''':493-6. PMID: 21753753

* Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR (2010) MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. ''Genet Epidemiol.'' '''34''':816-34. PMID: 21058334 [[Biostatistics 830 - Code Snippets|[Code Snippets]]]

* Lin DY, Zeng D (2010) Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data. ''Genet Epidemiol.'' '''34''':60-6. PMID: 19847795

* Liu DJ, Peloso GM, Zhan X, Holmen OL, Zawistowski M, Feng S, Nikpay M, Auer PL, Goel A, Zhang H, Peters U, Farrall M, Orho-Melander M, Kooperberg C, McPherson R, Watkins H, Willer CJ, Hveem K, Melander O, Kathiresan S, Abecasis GR (2014) Meta-analysis of gene-level tests for rare variant association. ''Nat Genet.'' '''46''':200-4

* Sobel E, Lange K (1996) Descent Graphs in Pedigree Analysis: Applications to Haplotyping, Location Scores, and Marker-Sharing Statistics. ''Am. J. Hum. Genet.'' '''58''':1323-1336

* Wang C, Zhan X, Bragg-Gresham J, Kang HM, Stambolian D, Chew EY, Branham KE, Heckenlively J; FUSION Study, Fulton R, Wilson RK, Mardis ER, Lin X, Swaroop A, Zöllner S, Abecasis GR (2014) Ancestry estimation and control of population stratification for sequence-based association studies. ''Nat Genet. 2014'' '''46''':409-15

* Wen X, Stephens M (2010) Using linear predictors to impute allele frequencies from summary or pooled genotype data. ''Ann Appl Stat.'' '''4''':1158-1182. PMID: 21479081

* Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X (2011) Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet. 89:82-93

* Zerbino DR, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. ''Genome Res.'' '''18''':821-9. PMID: 18349386

== Course History ==

This course is offered occasionally. Typically, Mike Boehnke has taught it. Each instructor gives the course a different flavor, so you may find it worthwhile -- even if you have taken the course with Mike previously.

Biostatistics 866: Main Page

2017-04-18T05:46:11Z

Gzajac: /* Student Presentations */

== Objective ==

Gene mapping studies study the relationship between genetic variation and susceptibility to human disease. These studies are changing rapidly with the availability of techniques for very large scale genetic analysis, whether based on sequencing or on genotyping. Biostatistics 866 is a Ph.D. level course that helps students understand some of the key building blocks of modern genetic analysis tools. It is meant to provide students with a toolkit to facilitate development and implementation of new statistical methods.

For additional information, see also [[Biostatistics 866: Core Competencies|Core Competencies in Biostatistics Program covered by this course]].

== Target Audience ==

It is highly recommended that students registering for Biostatistics 830 should have previously completed [[Biostatistics 666]] and [[Biostatistics 615/815]], which are courses introducing methods for genetic analysis and programming principles, respectively.

== Scheduling ==

For Winter 2017, classes are scheduled for Tuesdays and Thursdays, 8:30 - 10 am in SPH II, room 1152.

== Grading ==

The final grade will take into account your performance in problem sets and worksheets as well as your participation in class.

== Class Worksheets ==

=== Hidden Markov Models ===

Week of January 8 - [[Media:Question_Sheet_-_Li_et_al_(2010)_Gen_Epid.pdf|Li et al (2010)]]

Week of January 15 - [[Media:Question_Sheet_-_Howie_et_al_(2012)_Nat_Genet.pdf|Howie et al (2012)]] (and, [[Media:866_-_Slides_for_Hyun.pdf|Discussion slides for January 19]])

Week of January 22 - [[Media:Question_Sheet_-_Delaneau_et_al_(2013)_Nature_Methods.pdf|Delaneau et al (2013)]]

Week of January 29 - [[Media:Question_Sheet_-_Boehnke_and_Cox_(1997)_AJHG.pdf|Boehnke and Cox (1997)]]

=== Short Read Sequencing ===

February 12 - [[Media:Question_Sheet_-_Li_et_al_(2008)_Genome_Research.pdf|Li et al (2008)]]

February 19 - [[Media:Question_Sheet_-_Li_and_Durbin_(2009)_Bioinformatics.pdf|Li and Durbin (2009)]]

March 5 - [[Media:Question_Sheet_-_Zerbino_and_Birney_(2008)_Bioinformatics.pdf|Zerbino and Birney (2008)]]

March 12 - [[Media:Question_Sheet_-_Iqbal_et_al_(2012)_Nature_Genetics.pdf|Iqbal et al (2012)]]

=== Association Analysis ===

March 19 - [[Media:Question_Sheet_-_2017_-_Kang_et_al_(2010)_Nature_Genetics_.pdf|Kang et al (2010)]]

March 26 - [[Media:Question_Sheet_-_2017_-_Wu_et_al_(2011)_American_Journal_of_Human_Genetics.pdf|Wu et al (2011)]]

April 2 - [[Media:Question_Sheet_-_2017_-_Liu_et_al_(2013)_Nature_Genetics.pdf|Liu et al (2014)]]

=== Adventures in Statistical Genetics ===

April 9 - [[Media:2017.04_-_Adventures_in_Human_Genetics.pdf|Goncalo's Adventure in Human Genetics]]

== Student Presentations ==
[Greg [File:Zajac_Journey_Lecture.pdf]]

== Standards of Academic Conduct ==

The following is an extract from the School of Public Health's Student Code of Conduct [http://www.sph.umich.edu/academics/policies/conduct.html]:

''Student academic misconduct includes behavior involving plagiarism, cheating, fabrication, falsification of records or official documents, intentional misuse of equipment or materials, and aiding and abetting the perpetration of such acts. The preparation of reports, papers, and examinations, assigned on an individual basis, must represent each student’s own effort. Reference sources should be indicated clearly. The use of assistance from other students or aids of any kind during a written examination, except when the use of books or notes has been approved by an instructor, is a violation of the standard of academic conduct.''

In the context of this course, any work you hand-in should be your own and any material that is a transcript (or interpreted transcript) of work by others must be clearly labeled as such. If you turn in work that is directly copied from another student or from a published or unpublished source without attribution, you risk failing the course.

== Planned Reading ==

* Abecasis GR, Cherny SS, Cookson WO, Cardon LR (2002) Merlin--rapid analysis of dense genetic maps using sparse gene flow trees. ''Nat Genetics'' '''30''':97-101

* Boehnke M and Cox N (1997) Accurate Inference of Relationships in Sib-Pair Linkage Studies. ''Am J Hum Genet'' '''61''':423-429

* Coventry A, Bull-Otterson LM, Liu X, Clark AG, Maxwell TJ, Crosby J, Hixson JE, Rea TJ, Muzny DM, Lewis LR, Wheeler DA, Sabo A, Lusk C, Weiss KG, Akbar H, Cree A, Hawes AC, Newsham I, Varghese RT, Villasana D, Gross S, Joshi V, Santibanez J, Morgan M, Chang K, Iv WH, Templeton AR, Boerwinkle E, Gibbs R, Sing CF (2010) Deep resequencing reveals excess rare recent variants consistent with explosive population growth. ''Nat Commun.'' '''1''':131. PMID: 21119644

* Delaneau O, Zagury JF, Marchini J (2013) Improved whole-chromosome phasing for disease and population genetic studies. ''Nat Methods.'' '''10''':5-6. PMID: 23269371

* Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR (2012) Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. ''Nat Genet.'' '''44''':955-9. PMID: 22820512 [[Biostatistics 830 - Code Snippets|[Code Snippets]]]

* Iqbal Z, Caccamo M, Turner I, Flicek P, McVean G (2012) De novo assembly and genotyping of variants using colored de Bruijn graphs. ''Nat Genet.'' '''44''':226-32. PMID: 22231483

* Field Y, Boyle EA, Telis N, Gao Z, Gaulton KJ, Golan D, Yengo L, Rocheleau G, Froguel P, McCarthy MI, Pritchard JK (2016) Detection of human adaptation during the past 2000 years. ''Science'' '''354''':760-764

* Jun G, Flickinger M, Hetrick KN, Romm JM, Doheny KF, Abecasis GR, Boehnke M, Kang HM (2012) Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data. ''Am J Hum Genet.'' '''91''':839-48. PMID: 23103226

* Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, Sabatti C, Eskin E (2010) Variance component model to account for sample structure in genome-wide association studies. ''Nat. Genet.'' '''42''':348-354

* Kircher M, Witten DM, Jain P, O'Roak BJ, Cooper GM, Shendure J (2014) A general framework for estimating the relative pathogenicity of human genetic variants. ''Nat. Genet.'' '''46''' 310–315

* Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES (1996) Parametric and non-parametric linkage analysis: a unified multipoint approach. ''Am J Hum Genet'' '''58''':1347-63

* Li H, Ruan J, Durbin R (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. ''Genome Res.'' '''18''':1851-8. PMID: 18714091

* Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. ''Bioinformatics.'' '''25''':1754-60. PMID: 19451168

* Li H, Durbin R (2011) Inference of human population history from individual whole-genome sequences. ''Nature.'' '''475''':493-6. PMID: 21753753

* Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR (2010) MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. ''Genet Epidemiol.'' '''34''':816-34. PMID: 21058334 [[Biostatistics 830 - Code Snippets|[Code Snippets]]]

* Lin DY, Zeng D (2010) Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data. ''Genet Epidemiol.'' '''34''':60-6. PMID: 19847795

* Liu DJ, Peloso GM, Zhan X, Holmen OL, Zawistowski M, Feng S, Nikpay M, Auer PL, Goel A, Zhang H, Peters U, Farrall M, Orho-Melander M, Kooperberg C, McPherson R, Watkins H, Willer CJ, Hveem K, Melander O, Kathiresan S, Abecasis GR (2014) Meta-analysis of gene-level tests for rare variant association. ''Nat Genet.'' '''46''':200-4

* Sobel E, Lange K (1996) Descent Graphs in Pedigree Analysis: Applications to Haplotyping, Location Scores, and Marker-Sharing Statistics. ''Am. J. Hum. Genet.'' '''58''':1323-1336

* Wang C, Zhan X, Bragg-Gresham J, Kang HM, Stambolian D, Chew EY, Branham KE, Heckenlively J; FUSION Study, Fulton R, Wilson RK, Mardis ER, Lin X, Swaroop A, Zöllner S, Abecasis GR (2014) Ancestry estimation and control of population stratification for sequence-based association studies. ''Nat Genet. 2014'' '''46''':409-15

* Wen X, Stephens M (2010) Using linear predictors to impute allele frequencies from summary or pooled genotype data. ''Ann Appl Stat.'' '''4''':1158-1182. PMID: 21479081

* Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X (2011) Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet. 89:82-93

* Zerbino DR, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. ''Genome Res.'' '''18''':821-9. PMID: 18349386

== Course History ==

This course is offered occasionally. Typically, Mike Boehnke has taught it. Each instructor gives the course a different flavor, so you may find it worthwhile -- even if you have taken the course with Mike previously.

Biostatistics 866: Main Page

2017-04-10T13:50:18Z

Gzajac:

== Objective ==

Gene mapping studies study the relationship between genetic variation and susceptibility to human disease. These studies are changing rapidly with the availability of techniques for very large scale genetic analysis, whether based on sequencing or on genotyping. Biostatistics 866 is a Ph.D. level course that helps students understand some of the key building blocks of modern genetic analysis tools. It is meant to provide students with a toolkit to facilitate development and implementation of new statistical methods.

For additional information, see also [[Biostatistics 866: Core Competencies|Core Competencies in Biostatistics Program covered by this course]].

== Target Audience ==

It is highly recommended that students registering for Biostatistics 830 should have previously completed [[Biostatistics 666]] and [[Biostatistics 615/815]], which are courses introducing methods for genetic analysis and programming principles, respectively.

== Scheduling ==

For Winter 2017, classes are scheduled for Tuesdays and Thursdays, 8:30 - 10 am in SPH II, room 1152.

== Grading ==

The final grade will take into account your performance in problem sets and worksheets as well as your participation in class.

== Class Worksheets ==

=== Hidden Markov Models ===

Week of January 8 - [[Media:Question_Sheet_-_Li_et_al_(2010)_Gen_Epid.pdf|Li et al (2010)]]

Week of January 15 - [[Media:Question_Sheet_-_Howie_et_al_(2012)_Nat_Genet.pdf|Howie et al (2012)]] (and, [[Media:866_-_Slides_for_Hyun.pdf|Discussion slides for January 19]])

Week of January 22 - [[Media:Question_Sheet_-_Delaneau_et_al_(2013)_Nature_Methods.pdf|Delaneau et al (2013)]]

Week of January 29 - [[Media:Question_Sheet_-_Boehnke_and_Cox_(1997)_AJHG.pdf|Boehnke and Cox (1997)]]

=== Short Read Sequencing ===

February 12 - [[Media:Question_Sheet_-_Li_et_al_(2008)_Genome_Research.pdf|Li et al (2008)]]

February 19 - [[Media:Question_Sheet_-_Li_and_Durbin_(2009)_Bioinformatics.pdf|Li and Durbin (2009)]]

March 5 - [[Media:Question_Sheet_-_Zerbino_and_Birney_(2008)_Bioinformatics.pdf|Zerbino and Birney (2008)]]

March 12 - [[Media:Question_Sheet_-_Iqbal_et_al_(2012)_Nature_Genetics.pdf|Iqbal et al (2012)]]

=== Association Analysis ===

March 19 - [[Media:Question_Sheet_-_2017_-_Kang_et_al_(2010)_Nature_Genetics_.pdf|Kang et al (2010)]]

March 26 - [[Media:Question_Sheet_-_2017_-_Wu_et_al_(2011)_American_Journal_of_Human_Genetics.pdf|Wu et al (2011)]]

April 2 - [[Media:Question_Sheet_-_2017_-_Liu_et_al_(2013)_Nature_Genetics.pdf|Liu et al (2014)]]

== Student Presentations ==

== Standards of Academic Conduct ==

The following is an extract from the School of Public Health's Student Code of Conduct [http://www.sph.umich.edu/academics/policies/conduct.html]:

''Student academic misconduct includes behavior involving plagiarism, cheating, fabrication, falsification of records or official documents, intentional misuse of equipment or materials, and aiding and abetting the perpetration of such acts. The preparation of reports, papers, and examinations, assigned on an individual basis, must represent each student’s own effort. Reference sources should be indicated clearly. The use of assistance from other students or aids of any kind during a written examination, except when the use of books or notes has been approved by an instructor, is a violation of the standard of academic conduct.''

In the context of this course, any work you hand-in should be your own and any material that is a transcript (or interpreted transcript) of work by others must be clearly labeled as such. If you turn in work that is directly copied from another student or from a published or unpublished source without attribution, you risk failing the course.

== Planned Reading ==

* Abecasis GR, Cherny SS, Cookson WO, Cardon LR (2002) Merlin--rapid analysis of dense genetic maps using sparse gene flow trees. ''Nat Genetics'' '''30''':97-101

* Boehnke M and Cox N (1997) Accurate Inference of Relationships in Sib-Pair Linkage Studies. ''Am J Hum Genet'' '''61''':423-429

* Coventry A, Bull-Otterson LM, Liu X, Clark AG, Maxwell TJ, Crosby J, Hixson JE, Rea TJ, Muzny DM, Lewis LR, Wheeler DA, Sabo A, Lusk C, Weiss KG, Akbar H, Cree A, Hawes AC, Newsham I, Varghese RT, Villasana D, Gross S, Joshi V, Santibanez J, Morgan M, Chang K, Iv WH, Templeton AR, Boerwinkle E, Gibbs R, Sing CF (2010) Deep resequencing reveals excess rare recent variants consistent with explosive population growth. ''Nat Commun.'' '''1''':131. PMID: 21119644

* Delaneau O, Zagury JF, Marchini J (2013) Improved whole-chromosome phasing for disease and population genetic studies. ''Nat Methods.'' '''10''':5-6. PMID: 23269371

* Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR (2012) Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. ''Nat Genet.'' '''44''':955-9. PMID: 22820512 [[Biostatistics 830 - Code Snippets|[Code Snippets]]]

* Iqbal Z, Caccamo M, Turner I, Flicek P, McVean G (2012) De novo assembly and genotyping of variants using colored de Bruijn graphs. ''Nat Genet.'' '''44''':226-32. PMID: 22231483

* Field Y, Boyle EA, Telis N, Gao Z, Gaulton KJ, Golan D, Yengo L, Rocheleau G, Froguel P, McCarthy MI, Pritchard JK (2016) Detection of human adaptation during the past 2000 years. ''Science'' '''354''':760-764

* Jun G, Flickinger M, Hetrick KN, Romm JM, Doheny KF, Abecasis GR, Boehnke M, Kang HM (2012) Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data. ''Am J Hum Genet.'' '''91''':839-48. PMID: 23103226

* Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, Sabatti C, Eskin E (2010) Variance component model to account for sample structure in genome-wide association studies. ''Nat. Genet.'' '''42''':348-354

* Kircher M, Witten DM, Jain P, O'Roak BJ, Cooper GM, Shendure J (2014) A general framework for estimating the relative pathogenicity of human genetic variants. ''Nat. Genet.'' '''46''' 310–315

* Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES (1996) Parametric and non-parametric linkage analysis: a unified multipoint approach. ''Am J Hum Genet'' '''58''':1347-63

* Li H, Ruan J, Durbin R (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. ''Genome Res.'' '''18''':1851-8. PMID: 18714091

* Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. ''Bioinformatics.'' '''25''':1754-60. PMID: 19451168

* Li H, Durbin R (2011) Inference of human population history from individual whole-genome sequences. ''Nature.'' '''475''':493-6. PMID: 21753753

* Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR (2010) MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. ''Genet Epidemiol.'' '''34''':816-34. PMID: 21058334 [[Biostatistics 830 - Code Snippets|[Code Snippets]]]

* Lin DY, Zeng D (2010) Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data. ''Genet Epidemiol.'' '''34''':60-6. PMID: 19847795

* Liu DJ, Peloso GM, Zhan X, Holmen OL, Zawistowski M, Feng S, Nikpay M, Auer PL, Goel A, Zhang H, Peters U, Farrall M, Orho-Melander M, Kooperberg C, McPherson R, Watkins H, Willer CJ, Hveem K, Melander O, Kathiresan S, Abecasis GR (2014) Meta-analysis of gene-level tests for rare variant association. ''Nat Genet.'' '''46''':200-4

* Sobel E, Lange K (1996) Descent Graphs in Pedigree Analysis: Applications to Haplotyping, Location Scores, and Marker-Sharing Statistics. ''Am. J. Hum. Genet.'' '''58''':1323-1336

* Wang C, Zhan X, Bragg-Gresham J, Kang HM, Stambolian D, Chew EY, Branham KE, Heckenlively J; FUSION Study, Fulton R, Wilson RK, Mardis ER, Lin X, Swaroop A, Zöllner S, Abecasis GR (2014) Ancestry estimation and control of population stratification for sequence-based association studies. ''Nat Genet. 2014'' '''46''':409-15

* Wen X, Stephens M (2010) Using linear predictors to impute allele frequencies from summary or pooled genotype data. ''Ann Appl Stat.'' '''4''':1158-1182. PMID: 21479081

* Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X (2011) Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet. 89:82-93

* Zerbino DR, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. ''Genome Res.'' '''18''':821-9. PMID: 18349386

== Course History ==

This course is offered occasionally. Typically, Mike Boehnke has taught it. Each instructor gives the course a different flavor, so you may find it worthwhile -- even if you have taken the course with Mike previously.