From 49e1701d2949f4bd74a591f2c6236d6dac26032c Mon Sep 17 00:00:00 2001 From: Cesaire Joris Kuete Fouodo Date: Thu, 18 Jul 2024 20:24:36 +0200 Subject: [PATCH] Run test code --- .github/workflows/R-CMD-check.yaml | 5 - README.Rmd | 2 +- README.md | 144 ++++++++++++++--------------- 3 files changed, 73 insertions(+), 78 deletions(-) diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml index ccf7eae..bdb0db8 100644 --- a/.github/workflows/R-CMD-check.yaml +++ b/.github/workflows/R-CMD-check.yaml @@ -58,8 +58,3 @@ jobs: env: GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} - - - name: Upload coverage to Codecov - uses: codecov/codecov-action@v4.0.1 - with: - verbose: true diff --git a/README.Rmd b/README.Rmd index ad24dd3..4ce2c7f 100644 --- a/README.Rmd +++ b/README.Rmd @@ -13,7 +13,7 @@ knitr::opts_chunk$set(echo = TRUE) [![R-CMD-check](https://github.com/imbs-hl/fuseMLR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/imbs-hl/fuseMLR/actions/workflows/R-CMD-check.yaml) -[![Coverage Status](https://coveralls.io/repos/github/imbs-hl/fuseMLR/badge.svg?branch=main)](https://coveralls.io/github/imbs-hl/fuseMLR?branch=main) +[![codecov](https://codecov.io/gh/imbs-hl/fuseMLR/branch/main/graph/badge.svg)](https://codecov.io/gh/imbs-hl/fuseMLR) [![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental) [![CRAN downloads](http://www.r-pkg.org/badges/version/fuseMLR)](http://cranlogs.r-pkg.org/badges/grand-total/fuseMLR) [![Stack Overflow](https://img.shields.io/badge/stackoverflow-questions-orange.svg)](https://stackoverflow.com/questions/tagged/fuseMLR) diff --git a/README.md b/README.md index 113ddca..a9fa439 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,7 @@ [![R-CMD-check](https://github.com/imbs-hl/fuseMLR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/imbs-hl/fuseMLR/actions/workflows/R-CMD-check.yaml) -[![Coverage -Status](https://coveralls.io/repos/github/imbs-hl/fuseMLR/badge.svg?branch=main)](https://coveralls.io/github/imbs-hl/fuseMLR?branch=main) +[![codecov](https://codecov.io/gh/imbs-hl/fuseMLR/branch/main/graph/badge.svg)](https://codecov.io/gh/imbs-hl/fuseMLR) [![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental) [![CRAN @@ -225,51 +224,52 @@ print(var_sel_res) ## Layer variable ## 1 geneexpr ACACA - ## 2 geneexpr BAP1 - ## 3 geneexpr CHEK2 - ## 4 geneexpr EIF4E - ## 5 geneexpr MAP2K1 - ## 6 geneexpr MAPK14 - ## 7 geneexpr PCNA - ## 8 geneexpr YWHAE - ## 9 proteinexpr Bap1.c.4 - ## 10 proteinexpr Bid - ## 11 proteinexpr Cyclin_E2 - ## 12 proteinexpr P.Cadherin - ## 13 proteinexpr Chk1 - ## 14 proteinexpr Chk1_pS345 - ## 15 proteinexpr EGFR - ## 16 proteinexpr EGFR_pY1173 - ## 17 proteinexpr HER3_pY1289 - ## 18 proteinexpr MIG.6 - ## 19 proteinexpr ETS.1 - ## 20 proteinexpr MEK1_pS217_S221 - ## 21 proteinexpr p38_MAPK - ## 22 proteinexpr c.Met_pY1235 - ## 23 proteinexpr N.Ras - ## 24 proteinexpr PEA15_pS116 - ## 25 proteinexpr PKC.delta_pS664 - ## 26 proteinexpr Rad50 - ## 27 proteinexpr C.Raf_pS338 - ## 28 proteinexpr p70S6K - ## 29 proteinexpr p70S6K_pT389 - ## 30 proteinexpr Smad4 - ## 31 proteinexpr STAT3_pY705 - ## 32 proteinexpr 14.3.3_epsilon - ## 33 methylation cg20139214 - ## 34 methylation cg18457775 - ## 35 methylation cg24747396 - ## 36 methylation cg09637363 - ## 37 methylation cg01306510 - ## 38 methylation cg02412050 - ## 39 methylation cg25984124 - ## 40 methylation cg07566050 - ## 41 methylation cg02630105 - ## 42 methylation cg20849549 - ## 43 methylation cg00547829 - ## 44 methylation cg25539131 - ## 45 methylation cg07064406 - ## 46 methylation cg11816577 + ## 2 geneexpr ASNS + ## 3 geneexpr BAP1 + ## 4 geneexpr CHEK2 + ## 5 geneexpr EIF4E + ## 6 geneexpr MAP2K1 + ## 7 geneexpr MAPK14 + ## 8 geneexpr PCNA + ## 9 geneexpr SMAD4 + ## 10 geneexpr SQSTM1 + ## 11 geneexpr YWHAE + ## 12 proteinexpr Bap1.c.4 + ## 13 proteinexpr Bid + ## 14 proteinexpr Cyclin_E2 + ## 15 proteinexpr P.Cadherin + ## 16 proteinexpr Chk1 + ## 17 proteinexpr Chk1_pS345 + ## 18 proteinexpr EGFR + ## 19 proteinexpr EGFR_pY1173 + ## 20 proteinexpr HER3_pY1289 + ## 21 proteinexpr MIG.6 + ## 22 proteinexpr ETS.1 + ## 23 proteinexpr MEK1_pS217_S221 + ## 24 proteinexpr p38_MAPK + ## 25 proteinexpr c.Met_pY1235 + ## 26 proteinexpr N.Ras + ## 27 proteinexpr PCNA + ## 28 proteinexpr PEA15_pS116 + ## 29 proteinexpr PKC.delta_pS664 + ## 30 proteinexpr Rad50 + ## 31 proteinexpr C.Raf_pS338 + ## 32 proteinexpr p70S6K + ## 33 proteinexpr p70S6K_pT389 + ## 34 proteinexpr Smad4 + ## 35 proteinexpr STAT3_pY705 + ## 36 proteinexpr 14.3.3_epsilon + ## 37 methylation cg20139214 + ## 38 methylation cg18457775 + ## 39 methylation cg24747396 + ## 40 methylation cg01306510 + ## 41 methylation cg02412050 + ## 42 methylation cg07566050 + ## 43 methylation cg02630105 + ## 44 methylation cg20849549 + ## 45 methylation cg25539131 + ## 46 methylation cg07064406 + ## 47 methylation cg11816577 For each layer, the variable selection results show the chosen variables. In this example, we perform variable selection on the entire @@ -374,9 +374,9 @@ print(model_ge) ## Layer : geneexpr ## ind. id. : IDS ## target : disease - ## n : 24 + ## n : 22 ## Missing : 0 - ## p : 9 + ## p : 12 #### C) Predicting @@ -425,29 +425,29 @@ print(new_predictions) ## ## $predicted_values ## IDS geneexpr proteinexpr methylation meta_layer - ## 1 subject4 0.5692770 0.7216738 0.5381234 0.6120387 - ## 2 subject7 0.5245984 0.1517905 0.4670440 0.3700894 - ## 3 subject8 0.7372762 0.9001016 0.6653460 0.7685477 - ## 4 subject10 0.8185226 0.8399246 0.6433667 0.7608181 - ## 5 subject13 0.4501103 0.3053063 0.2560587 0.3260454 - ## 6 subject15 0.6945798 0.9100496 0.4598270 0.6838968 - ## 7 subject16 0.7228405 0.2317556 0.4113329 0.4313865 - ## 8 subject18 0.6225540 0.2598992 0.1398702 0.3130737 - ## 9 subject23 0.7695409 0.1713853 0.6136909 0.4979463 - ## 10 subject24 0.4136722 0.7267909 0.4837393 0.5515487 - ## 11 subject27 0.4922226 0.2237667 0.5171135 0.4057083 - ## 12 subject31 0.4245571 0.8263060 0.4952425 0.5942924 - ## 13 subject32 0.4240972 0.8565766 0.7284512 0.6919688 - ## 14 subject35 0.2577560 0.7256048 0.6949587 0.5878086 - ## 15 subject36 0.4312321 0.1882139 0.5812706 0.4004817 - ## 16 subject50 0.7175571 0.5257234 0.8015587 0.6804371 - ## 17 subject54 0.5352171 0.7050111 0.8339952 0.7072681 - ## 18 subject55 0.5982429 0.2227556 0.3961583 0.3888607 - ## 19 subject59 0.4251044 0.1941571 0.6051290 0.4098478 - ## 20 subject62 0.3933698 0.2651238 0.2761345 0.3038700 - ## 21 subject63 0.5148698 0.8214048 0.8638964 0.7544627 - ## 22 subject66 0.5892992 0.6357849 0.8877810 0.7172364 - ## 23 subject70 0.2878270 0.3115385 0.4574508 0.3595667 + ## 1 subject4 0.3726087 0.59537778 0.47381190 0.4889144 + ## 2 subject7 0.5655742 0.16043056 0.63213968 0.4443262 + ## 3 subject8 0.8380849 0.81605913 0.62031071 0.7517472 + ## 4 subject10 0.7485567 0.67704206 0.75187460 0.7241172 + ## 5 subject13 0.5003869 0.17996905 0.13598651 0.2542748 + ## 6 subject15 0.6705560 0.81115317 0.31752143 0.5937900 + ## 7 subject16 0.7694242 0.22026984 0.16176508 0.3536987 + ## 8 subject18 0.5648512 0.24205952 0.04436071 0.2616643 + ## 9 subject23 0.6220655 0.26641865 0.53513095 0.4632689 + ## 10 subject24 0.3979790 0.64181151 0.51609048 0.5279254 + ## 11 subject27 0.4740099 0.15473413 0.57565794 0.3961783 + ## 12 subject31 0.3332222 0.80231468 0.66360833 0.6203752 + ## 13 subject32 0.6312270 0.83857421 0.75272500 0.7493149 + ## 14 subject35 0.4284504 0.81069484 0.46795913 0.5796981 + ## 15 subject36 0.6677992 0.09947698 0.56287937 0.4262902 + ## 16 subject50 0.7492417 0.50755357 0.71450397 0.6500953 + ## 17 subject54 0.7328262 0.63104563 0.67778095 0.6765153 + ## 18 subject55 0.6632115 0.13317024 0.49766508 0.4135867 + ## 19 subject59 0.4514956 0.19528016 0.47464603 0.3679932 + ## 20 subject62 0.3743234 0.24441389 0.33078214 0.3120733 + ## 21 subject63 0.5050103 0.81469048 0.88478611 0.7528117 + ## 22 subject66 0.7438659 0.65945357 0.95636349 0.7901499 + ## 23 subject70 0.3073437 0.21391667 0.19276032 0.2325814 © 2024 Institute of Medical Biometry and Statistics (IMBS). 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