Package PathwaySeq. February 3, 2015

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1 Package PathwaySeq February 3, 2015 Type Package Title RNA-Seq pathway analysis Version 1.0 Date Imports PearsonDS, AnnotationDbi, quad, mcc, org.hs.eg.db, GO.db,KEGG.db Author Maintainer PathwaySeq gives accurate statistical pathway analysis of RNA-Seq data. The R package has automatic annotation for human, mouse and rat. Unique features of the package include data transformations to enhance power and computation of exact permutation moments of quadratic forms, for powerful testing while preserving type I error. License GPL (>= 2) LazyLoad yes R topics documented: PathwaySeq-package bp.anno.mm bp.anno.rat cc.anno.mm cc.anno.rat center centernorm data.anno data.test gender get.maxindex getanno getanno.mm getanno.rat getmomentk getp.mixture hammer

2 2 PathwaySeq-package kegg.mm kegg.rat loss match.table.mm match.table.rat mf.anno.mm mf.anno.rat momentqprimek PathwayAnalysis test.id treatdata Index 20 PathwaySeq-package Pathway analysis for RNA-Seq data A variety of pathway/gene-set approaches have been proposed to provide evidence of higher-level biological phenomena in the association of expression with experimental condition or clinical outcome. Among these approaches, it has been repeatedly shown that permutation or bootstrapping of samples is far preferable to approaches that implicitly assume independence of genes. However, few approaches have been optimized for the specific characteristics of RNA-Seq transcription data, in which mapped tags produce discrete counts, and for which library sizes or other normalization factors may vary across samples. Our package gives flexiable transformation of the dataset. The approach uses aggregated summaries of gene-specific score statistics, with competitive comparison of genes in the pathway to those in the complement. PathwaySeq controls type I error control without actual permutation and it is powerful in comparison to competing approaches, and provides a convenient integrated approach to RNA-Seq pathway analysis. Package: PathwaySeq Type: Package Version: 1.0 Date: License: GPL (>= 2) Maintainer: <yihui_zhou@ncsu.edu>

3 bp.anno.mm 3 bp.anno.mm GO BP annotation file for Mouse The GO BP annotation file for mouse contains gene annotation built from GO full database association table download released Genes annotated to a specific GO term include all genes annotated to the term itself and all of its children terms on the GO hierarchy. data(bp.anno.mm) This file is needed to generate the pathway indicator matrix bp.anno.rat GO BP annotation file for Rat GO BP annotation file for Rat contains gene annotation built from GO full database association table download released Genes annotated to a specific GO term include all genes annotated to the term itself and all of its children terms on the GO hierarchy. data(bp.anno.rat) This file is needed to generate the pathway indicator matrix

4 4 cc.anno.rat cc.anno.mm GO CC annotation file for Mouse GO CC annotation file for mouse contains gene annotation built from GO full database association table download released Genes annotated to a specific GO term include all genes annotated to the term itself and all of its children terms on the GO hierarchy. data(cc.anno.mm) This file is needed to generate the pathway indicator matrix cc.anno.rat GO CC annotation file for rat GO CC annotation file for rat contains gene annotation built from GO full database association table download released Genes annotated to a specific GO term include all genes annotated to the term itself and all of its children terms on the GO hierarchy. data(cc.anno.rat) This file is needed to generate the pathway indicator matrix

5 center 5 center The center information of the 448 samples in the Vignette This is the covariate variable center of the toy example in the Vignette. centernorm Centering and normalization of the data matrix Implements a preprocessing step of the data analysis. Given a data matrix, initial standardization is necessary so that inner products are score statistics. centernorm(oldmatrix,y, z=null) oldmatrix y z the input data matrix clinical/experimental vector covariate vector This function row-centers and scales a data matrix, within each stratum if covariate z is provided. Value newmatrix newy Alist S2 the data matrix after centering and scaling centered clinical/experimental data if we denote the input data matrix as X, Alist is X X Score statistics

6 6 gender See Also PathwayAnalysis data.anno The annotation file example The annotation file for the toy example in the Vignette. data.test The toy example raw count data in the Vignettee This toy data contains 1000 genes and 448 samples. gender The gender information of the 448 samples in the Vignette This is the experimental variable gender of the toy example in the Vignette.

7 get.maxindex 7 get.maxindex Choose the best η1 and η2 This function helps you to choose the best transformation parameters to reach the best power, when you run the Moment Corrected Correlation (mcc) Package for RNA-Seq data analysis get.maxindex(y, yvec, covariate) Y yvec covariate Input the count data matrix Clinical/experimental variables Covariate vector, i.e. z This function provides you the transformation parameters η 1 and η 2 before you run pathway analysis. Alternatively, you can select the default values η 1 = 1 and η 2 = 1. Value numgene index.max eta.1 eta.2 newmatrix the matrix of number of significant genes we can detect using different combination of η 1 and η 2 the index of the rows and columsn when you reach the maximum number of genes the suggested η 1 value. the suggested η 2 value. the transformed data matrix \ YH Zhou and FA Wright, 2014, Hypothesis testing at the extremes: fast and robust association for high-throughput data, submitted

8 8 getanno getanno This function is designed for human data. It gets the pathway indicator matrix and annotation files. This function will provide KEGG, GOBP, GOMF, GOCC pathway indicator matrix for human, as well as the corresponding annotation files. getanno(gene.name) gene.name A vector of Ensembl IDs This function is the main functioin to get all the pathway annotation files for human data Value kegg bp mf cc kegganno bpanno mfanno ccanno indication matrix Gene vs KEGG pathway indication matrix Gene vs GOBP pathway indication matrix Gene vs GOMF pathway indication matrix Gene vs GOCC pathway KEGG name GOBP name GOMF name GOCC name See Also PathwayAnalysis

9 getanno.mm 9 getanno.mm Get gene vs pathway indicator matrix and annotation files for mouse data This function will provide KEGG, GOBP, GOMF, GOCC pathway indication matrix for mouse as well as the corresponding annotation file. getanno.mm(bp.anno.mm, mf.anno.mm, cc.anno.mm, match.table.mm, id, kegg.mm, type, number = 5) bp.anno.mm mf.anno.mm cc.anno.mm GOBP pathway annotation file for mouse GOMF pathway annotation file for mouse GOMF pathway annotation file for mouse match.table.mm Ensemble ID vs Gene symbol table id kegg.mm list of Ensemble ID KEGG annotation file for mouse number The minimum number of genes in a pathway, the default is 5 type Value The ID can be Ensembl Transcript ID transcript or Ensembl Gene ID ensemblgene or Gene Symbol genesymbol This function is the main functioin to get all the pathway annotation files for mouse data bp bpanno mf mfanno cc ccanno kegg kegganno indication matrix Gene vs GOBP pathway GOBP name indication matrix Gene vs GOMF pathway GOMF name indication matrix Gene vs GOCC pathway GOCC name indication matrix Gene vs KEGG pathway KEGG name

10 10 getanno.rat See Also PathwayAnalysis getanno.rat Get gene vs pathway indication matrix and annotation files for rat data This function will provide KEGG, GOBP, GOMF, GOCC pathway indication matrix for rat as well as the corresponding annotation file. getanno.rat(bp.anno.rat, mf.anno.rat, cc.anno.rat, match.table.rat, id, kegg.rat, type, number = 5) bp.anno.rat mf.anno.rat GOBP pathway annotation file for rat GOMF pathway annotation file for rat cc.anno.rat GOCC pathway annotation file for rat match.table.rat Ensemble ID vs Gene symbol table id kegg.rat list of Ensemble ID KEGG annotation file for rat number The minimum number of genes in a pathway, the default is 5 type Value The ID can be Ensembl Transcript ID transcript or Ensembl Gene ID ensemblgene or Gene Symbol genesymbol This function is the main functioin to get all the pathway annotation files for rat data bp bpanno mf mfanno cc ccanno kegg kegganno indication matrix Gene vs GOBP pathway GOBP name indication matrix Gene vs GOMF pathway GOMF name indication matrix Gene vs GOCC pathway GOCC name indication matrix Gene vs KEGG pathway KEGG name

11 getmomentk 11 See Also PathwayAnalysis getmomentk Get the first four moments This function outputs the exact first four permutation moments of the quadratic form statistics getmomentk(yvec, A, mycoef) yvec A mycoef experimental/clinical variable symmetric contrast matrix in quadratic form statistics these are useful coefficients which help to calculate the four exact moments this function provides you the exact four moments of the quadratic form statistics Value m1 m2 m3 m4 mean variance skewness kurtosis the first moment of the quadratic form statistics the second moment of the quadratic form statistics the third moment of the quadratic form statistics the fourth moment of the quadratic form statistics mean of test statistics variance of teststatistics skewness of test statistics kurtosis of test statistics

12 12 hammer getp.mixture further correction for the p value Provides a mixture density fit to the permutation distribtion of Q, in rare instances in which the Pearson family density fit is poor. getp.mixture(d, mymoments) D mymoments statistics first four moments from getmomentk Uses the four moments to provide an alternative (not Pearson family) density fit, when no fourmoment Pearson approximation is possible. This option is invoked only rarely, and typically for small datasets. hammer Rat data This dataset came from Hammer et al. We filtered the data to keep the number of reads in each gene larger than 15 for all the 8 samples P Hammer et al. 2010, mrna-seq with agnostic splice site discovery for nervous system transcriptomics tested in chronic pain, Genome Research, 20:

13 kegg.mm 13 kegg.mm kegg annotation file for Mouse kegg annotation file for mouse contains KEGG pathway annotations parsed from NCBI Biosystems download released on data(kegg.mm) This file is needed to generate the pathway indicator matrix kegg.rat kegg annotation file for rat kegg annotation file for rat contains KEGG pathway annotations parsed from NCBI Biosystems download released on data(kegg.rat) This file is needed to generate the pathway indicator matrix

14 14 match.table.mm loss loss function This is a loss function, used in numeric fitting for getp.mixture loss(param, target) param target parameters of the fitting distribution parameter estimation of the fitting distribution Value Returns an error loss measuring how different the proposed parameters are from the target myloss The error returned by comparing the proposed parameter to the target value See Also getp.mixture match.table.mm the mouse database which match Ensemble ID and Gene symbol Cross-references between Ensembl gene and transcript IDs release 75 to associated gene symbols were downloaded from Ensembl BioMart web portal. this table is used to look up gene symbols corresponding to Ensembl IDs and vice versa.

15 match.table.rat 15 match.table.rat the rat database which match Ensemble ID and Gene symbol Cross-references between Ensembl gene and transcript IDs release 75 to associated gene symbols were downloaded from Ensembl BioMart web portal. this table is used to lookup gene symbols corresponding to Ensembl IDs and vice versa. mf.anno.mm GO MF annotation file for Mouse The GO MF annotation file for mouse contains gene annotation built from GO full database association table download released Genes annotated to a specific GO term include all genes annotated to the term itself and all of its children terms on the GO hierarchy. data(mf.anno.mm) We need this file to generate the indicatior matrix of pathway

16 16 momentqprimek mf.anno.rat GO MF annotation file for rat GO MF annotation file for Rat contains gene annotation built from GO full database association table download released Genes annotated to a specific GO term include all genes annotated to the term itself and all of its children terms on the GO hierarchy. data(mf.anno.rat) We need this file to generate the indicator matrix of pathway momentqprimek the moments This function is designed for the case when covariate z is provided, and is assumed to have several factor levels. momentqprimek(oldmatrix, index.pathway, prestep, mycoef, z) oldmatrix index.pathway prestep mycoef z the original data matrix the indicator vector for the current pathway, i.e. is 1 for each gene belonging to the pathway, and 0 otherwise the output from function centernorm coefficents which are necessary to calculate the exact four permutation moments of a quadratic form the covariate vector

17 momentqprimek 17 this function generates the first four moments of the test statistics when the covariate vector z has several factors Value mean variance skewness kurtosis center Alist mean.sc variance.sc skewness.sc kurtosis.sc center.sc Alistsc newy the mean value of the statistics for the competitive hypothesis considering different strata the variance of the statistics for the competitive hypothesis considering different strata the new skewness for the competitive hypothesis the new kurtosis for the competitive hypothesis the center for the new quadratic form which considers the strata effect of z for the competitive hypothesis the new symmetric contrast matrix A in the quadratic form considering the factors in z the mean value of the statistics for the self-contained hypothesis considering different strata the variance of the statistics for the self-contained hypothesis considering different strata the new skewness for the self-contained hypothesis the new kurtosis for the self-contained hypothesis the center for the new quadratic form which considers the strata effect of z for the self-contained hypothesis the new symmetric contrast matrix A in the quadratic form considering the factors in z for the self-contained hypothesis the new centered clinical variable See Also PathwayAnalysis

18 18 PathwayAnalysis PathwayAnalysis The main pathway analysis function This function returns the list of significant pathways and p-values, for pathways with q-values below a threshold PathwayAnalysis(annotation,input.data,Cmatrix,pheno,mycoef,cutpoint=0.05,z=NULL) annotation all the annotation files and indication matrices from getanno input.data the original data matrix Cmatrix the gene vs pathway indication matrix pheno the clinical/experimental vector mycoef mycoef are the quadratic form coefficients from the R package quad cutpoint The threshold for FDR correction. The default is 0.05 z the covariate vector This is the main function of PathwaySeq. It performs quadratic-form pathway analysis for RNA- Seq data, with proper control of type I error, and with high power. The output contains basic annotation for the pathways and the number of assigned genes in each pathway. The proportional contribution of the most important gene in each pathway is also provided. Value competitive SelfContained Outputs the significant pathways and related information for the competitive hypothesis testing. (1) pathway ID and name; (2) the number of genes in each pathway; (3) proportional contribution of the gene with greatest contribution. Outputs the significant pathways and related information for the self-contained hypothesis testing.

19 test.id 19 test.id Ensembl Gene ID for the toy human data A vector of Gene ID treatdata Updates result for a single pathway calculate the score statistics for a single pathway treatdata(oldmatrix, index.pathway, Alist, z) oldmatrix index.pathway Alist z the input data matrix the index for each pathway X X is the output from function centernorm covariate vector This function returns the appropriate contrast matrix for the pathway Value cat_new Alistpath Alistpathsc the particular pathway we are interested in the test statistics of that pathway the test statistics of the complementary sets of that pathway

20 Index Topic PathwayAnalysis PathwayAnalysis, 18 Topic PathwaySeq PathwaySeq-package, 2 Topic centernorm centernorm, 5 Topic datasets center, 5 data.anno, 6 data.test, 6 gender, 6 hammer, 12 match.table.mm, 14 match.table.rat, 15 test.id, 19 Topic get.maxindex get.maxindex, 7 Topic getanno.mm getanno.mm, 9 Topic getanno.rat getanno.rat, 10 Topic getanno getanno, 8 Topic getmomentk getmomentk, 11 Topic getp.mixture getp.mixture, 12 Topic loss loss, 14 Topic momentqprimek momentqprimek, 16 Topic treatdata treatdata, 19 gender, 6 get.maxindex, 7 getanno, 8 getanno.mm, 9 getanno.rat, 10 getmomentk, 11 getp.mixture, 12, 14 hammer, 12 kegg.mm, 13 kegg.rat, 13 loss, 14 match.table.mm, 14 match.table.rat, 15 mf.anno.mm, 15 mf.anno.rat, 16 momentqprimek, 16 PathwayAnalysis, 6, 8, 10, 11, 17, 18 PathwaySeq (PathwaySeq-package), 2 PathwaySeq-package, 2 test.id, 19 treatdata, 19 bp.anno.mm, 3 bp.anno.rat, 3 cc.anno.mm, 4 cc.anno.rat, 4 center, 5 centernorm, 5 data.anno, 6 data.test, 6 20