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Results: 1 to 20 of 42

1.

Polyester: simulating RNA-seq datasets with differential transcript expression.

Frazee AC, Jaffe AE, Langmead B, Leek JT.

Bioinformatics. 2015 Apr 28. pii: btv272. [Epub ahead of print]

PMID:
25926345
2.

Statistics: P values are just the tip of the iceberg.

Leek JT, Peng RD.

Nature. 2015 Apr 30;520(7549):612. doi: 10.1038/520612a. No abstract available.

PMID:
25925460
3.

Test set bias affects reproducibility of gene signatures.

Patil P, Bachant-Winner PO, Haibe-Kains B, Leek JT.

Bioinformatics. 2015 Jul 15;31(14):2318-23. doi: 10.1093/bioinformatics/btv157. Epub 2015 Mar 18.

PMID:
25788628
4.

Ballgown bridges the gap between transcriptome assembly and expression analysis.

Frazee AC, Pertea G, Jaffe AE, Langmead B, Salzberg SL, Leek JT.

Nat Biotechnol. 2015 Mar;33(3):243-6. doi: 10.1038/nbt.3172. No abstract available.

PMID:
25748911
5.

Statistics. What is the question?

Leek JT, Peng RD.

Science. 2015 Mar 20;347(6228):1314-5. doi: 10.1126/science.aaa6146. Epub 2015 Feb 26. No abstract available.

PMID:
25721505
6.

Opinion: Reproducible research can still be wrong: adopting a prevention approach.

Leek JT, Peng RD.

Proc Natl Acad Sci U S A. 2015 Feb 10;112(6):1645-6. doi: 10.1073/pnas.1421412111. No abstract available.

7.

Developmental regulation of human cortex transcription and its clinical relevance at single base resolution.

Jaffe AE, Shin J, Collado-Torres L, Leek JT, Tao R, Li C, Gao Y, Jia Y, Maher BJ, Hyde TM, Kleinman JE, Weinberger DR.

Nat Neurosci. 2015 Jan;18(1):154-61. doi: 10.1038/nn.3898. Epub 2014 Dec 15.

8.

Removing batch effects for prediction problems with frozen surrogate variable analysis.

Parker HS, Corrada Bravo H, Leek JT.

PeerJ. 2014 Sep 23;2:e561. doi: 10.7717/peerj.561. eCollection 2014.

9.

svaseq: removing batch effects and other unwanted noise from sequencing data.

Leek JT.

Nucleic Acids Res. 2014 Dec 1;42(21). doi: 10.1093/nar/gku864. Epub 2014 Oct 7.

10.

Preserving biological heterogeneity with a permuted surrogate variable analysis for genomics batch correction.

Parker HS, Leek JT, Favorov AV, Considine M, Xia X, Chavan S, Chung CH, Fertig EJ.

Bioinformatics. 2014 Oct;30(19):2757-63. doi: 10.1093/bioinformatics/btu375. Epub 2014 Jun 6.

PMID:
24907368
11.

Inflammatory molecular signature associated with infectious agents in psychosis.

Hayes LN, Severance EG, Leek JT, Gressitt KL, Rohleder C, Coughlin JM, Leweke FM, Yolken RH, Sawa A.

Schizophr Bull. 2014 Sep;40(5):963-72. doi: 10.1093/schbul/sbu052. Epub 2014 Apr 17.

PMID:
24743863
12.

Differential expression analysis of RNA-seq data at single-base resolution.

Frazee AC, Sabunciyan S, Hansen KD, Irizarry RA, Leek JT.

Biostatistics. 2014 Jul;15(3):413-26. doi: 10.1093/biostatistics/kxt053. Epub 2014 Jan 6. Erratum in: Biostatistics. 2014 Jul;15(3):584-5.

13.

Gene set bagging for estimating the probability a statistically significant result will replicate.

Jaffe AE, Storey JD, Ji H, Leek JT.

BMC Bioinformatics. 2013 Dec 12;14:360. doi: 10.1186/1471-2105-14-360.

14.

An estimate of the science-wise false discovery rate and application to the top medical literature.

Jager LR, Leek JT.

Biostatistics. 2014 Jan;15(1):1-12. doi: 10.1093/biostatistics/kxt007. Epub 2013 Sep 25.

15.

A decision-theory approach to interpretable set analysis for high-dimensional data.

Boca SM, Bravo HC, Caffo B, Leek JT, Parmigiani G.

Biometrics. 2013 Sep;69(3):614-23. doi: 10.1111/biom.12060. Epub 2013 Aug 2.

16.

A simple and reproducible breast cancer prognostic test.

Marchionni L, Afsari B, Geman D, Leek JT.

BMC Genomics. 2013 May 17;14:336. doi: 10.1186/1471-2164-14-336.

17.

Sequestration: inadvertently killing biomedical research to score political points.

Leek JT, Salzberg SL.

Genome Biol. 2013 Mar 27;14(3):109. doi: 10.1186/gb-2013-14-3-109. No abstract available.

18.

SVAw - a web-based application tool for automated surrogate variable analysis of gene expression studies.

Pirooznia M, Seifuddin F, Goes FS, Leek JT, Zandi PP.

Source Code Biol Med. 2013 Mar 11;8(1):8. doi: 10.1186/1751-0473-8-8.

19.

Gene expression anti-profiles as a basis for accurate universal cancer signatures.

Bravo HC, Pihur V, McCall M, Irizarry RA, Leek JT.

BMC Bioinformatics. 2012 Oct 22;13:272. doi: 10.1186/1471-2105-13-272.

20.

A statistical approach to selecting and confirming validation targets in -omics experiments.

Leek JT, Taub MA, Rasgon JL.

BMC Bioinformatics. 2012 Jun 27;13:150.

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