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tagtag committed Jan 22, 2023
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120 changes: 61 additions & 59 deletions inst/doc/QuickStart.html
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<!DOCTYPE html>



<html>

<head>
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line-height: normal;
}

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</script>
<script type="text/javascript">
document.addEventListener("DOMContentLoaded", function() {
var links = document.links;
var links = document.links;
for (var i = 0, linksLength = links.length; i < linksLength; i++)
if (links[i].hostname != window.location.hostname)
links[i].target = '_blank';
Expand Down Expand Up @@ -787,12 +789,12 @@ <h2><span class="header-section-number">2.1</span> Gene expression.</h2>
#&gt; ── Column specification ─────────────────────────────────────────────────────────────────────
#&gt; Delimiter: &quot;,&quot;
#&gt; chr (2): TXNAME, GENEID
#&gt;
#&gt;
#&gt; ℹ Use `spec()` to retrieve the full column specification for this data.
#&gt; ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
txi &lt;- tximport(files, type=&quot;salmon&quot;, tx2gene=tx2gene)
#&gt; reading in files with read_tsv
#&gt; 1 2 3 4 5 6
#&gt; 1 2 3 4 5 6
#&gt; summarizing abundance
#&gt; summarizing counts
#&gt; summarizing length</code></pre>
Expand All @@ -809,14 +811,14 @@ <h2><span class="header-section-number">2.1</span> Gene expression.</h2>
dim(attr(Z,&quot;value&quot;))
#&gt; [1] 10000 3 2
HOSVD &lt;- computeHosvd(Z)
#&gt;
|
#&gt;
|
| | 0%
|
|
|============================ | 33%
|
|
|======================================================= | 67%
|
|
|===================================================================================| 100%</code></pre>
<p>Here 3 and 2 stand for the number of samples in each class and the number of classes, respectively. HOSVD includes output from HOSVD.
Next, we need to decide which singular value vectors are used for the download analysis interacxtively. Since vignettes has no ability to store the output from
Expand Down Expand Up @@ -905,19 +907,19 @@ <h2><span class="header-section-number">2.2</span> Multiomics data analysis</h2>
mRNA=rownames(CLL_data$mRNA),Mutations=rownames(CLL_data$Mutations)),
value=convertSquare(CLL_data),sampleData=list(CLL_covariates[,1]))
HOSVD &lt;- computeHosvdSqure(Z)
#&gt;
|
#&gt;
|
| | 0%
|
|
|============================ | 33%
|
|
|======================================================= | 67%
|
|
|===================================================================================| 100%</code></pre>
<p>CLL_covariate is labeling information, among which we employed the distinction between male (m) and female (f).</p>
<pre class="r"><code>table(CLL_covariates[,1])
#&gt;
#&gt; f m
#&gt;
#&gt; f m
#&gt; 79 121
cond &lt;- list(attr(Z,&quot;sampleData&quot;)[[1]],attr(Z,&quot;sampleData&quot;)[[1]],seq_len(4))</code></pre>
<p>Since a tensor is a bundle of liner kernel, the first two singular value vectors are decicated to samples and the third (last) one is dedecated to four omics classes (Drugs, Metylation, mRNA and mutations).
Expand Down Expand Up @@ -954,9 +956,9 @@ <h2><span class="header-section-number">2.2</span> Multiomics data analysis</h2>
<p>In order to see selected fearures for all four omics data, tableFeatureSquare function must be repeated four times as</p>
<pre class="r"><code>for (id in seq_len(4)){print(head(tableFeaturesSquare(Z,index,id)))}
#&gt; [1] Feature p value adjusted p value
#&gt; &lt;0 行&gt; (または長さ 0 の row.names)
#&gt; &lt;0 行&gt; (または長さ 0 の row.names)
#&gt; [1] Feature p value adjusted p value
#&gt; &lt;0 行&gt; (または長さ 0 の row.names)
#&gt; &lt;0 行&gt; (または長さ 0 の row.names)
#&gt; Feature p value adjusted p value
#&gt; 4 ENSG00000152953 9.669707e-13 4.834854e-09
#&gt; 3 ENSG00000163873 1.369068e-10 3.422671e-07
Expand All @@ -980,43 +982,43 @@ <h1><span class="header-section-number">3</span> Conclusion</h1>
#&gt; R version 4.2.2 Patched (2022-11-10 r83330)
#&gt; Platform: x86_64-pc-linux-gnu (64-bit)
#&gt; Running under: Ubuntu 18.04.6 LTS
#&gt;
#&gt;
#&gt; Matrix products: default
#&gt; BLAS: /usr/lib/x86_64-linux-gnu/atlas/libblas.so.3.10.3
#&gt; LAPACK: /usr/lib/x86_64-linux-gnu/atlas/liblapack.so.3.10.3
#&gt;
#&gt;
#&gt; locale:
#&gt; [1] LC_CTYPE=ja_JP.UTF-8 LC_NUMERIC=C LC_TIME=ja_JP.UTF-8
#&gt; [4] LC_COLLATE=ja_JP.UTF-8 LC_MONETARY=ja_JP.UTF-8 LC_MESSAGES=ja_JP.UTF-8
#&gt; [7] LC_PAPER=ja_JP.UTF-8 LC_NAME=C LC_ADDRESS=C
#&gt; [10] LC_TELEPHONE=C LC_MEASUREMENT=ja_JP.UTF-8 LC_IDENTIFICATION=C
#&gt;
#&gt; [1] LC_CTYPE=ja_JP.UTF-8 LC_NUMERIC=C LC_TIME=ja_JP.UTF-8
#&gt; [4] LC_COLLATE=ja_JP.UTF-8 LC_MONETARY=ja_JP.UTF-8 LC_MESSAGES=ja_JP.UTF-8
#&gt; [7] LC_PAPER=ja_JP.UTF-8 LC_NAME=C LC_ADDRESS=C
#&gt; [10] LC_TELEPHONE=C LC_MEASUREMENT=ja_JP.UTF-8 LC_IDENTIFICATION=C
#&gt;
#&gt; attached base packages:
#&gt; [1] stats4 stats graphics grDevices utils datasets methods base
#&gt;
#&gt; [1] stats4 stats graphics grDevices utils datasets methods base
#&gt;
#&gt; other attached packages:
#&gt; [1] MOFAdata_1.12.0 tximportData_1.24.0 tximport_1.24.0 readr_2.1.2
#&gt; [5] rTensor_1.4.8 GenomicRanges_1.48.0 GenomeInfoDb_1.32.2 IRanges_2.30.0
#&gt; [9] S4Vectors_0.34.0 BiocGenerics_0.42.0 BiocStyle_2.24.0 TDbasedUFE_0.1.0
#&gt;
#&gt; [1] MOFAdata_1.12.0 tximportData_1.24.0 tximport_1.24.0 readr_2.1.2
#&gt; [5] rTensor_1.4.8 GenomicRanges_1.48.0 GenomeInfoDb_1.32.2 IRanges_2.30.0
#&gt; [9] S4Vectors_0.34.0 BiocGenerics_0.42.0 BiocStyle_2.24.0 TDbasedUFE_0.1.0
#&gt;
#&gt; loaded via a namespace (and not attached):
#&gt; [1] tidyselect_1.1.2 xfun_0.31 bslib_0.3.1
#&gt; [4] purrr_0.3.4 vctrs_0.4.1 htmltools_0.5.2
#&gt; [7] usethis_2.1.6 yaml_2.3.5 utf8_1.2.2
#&gt; [10] rlang_1.0.2 pillar_1.7.0 jquerylib_0.1.4
#&gt; [1] tidyselect_1.1.2 xfun_0.31 bslib_0.3.1
#&gt; [4] purrr_0.3.4 vctrs_0.4.1 htmltools_0.5.2
#&gt; [7] usethis_2.1.6 yaml_2.3.5 utf8_1.2.2
#&gt; [10] rlang_1.0.2 pillar_1.7.0 jquerylib_0.1.4
#&gt; [13] glue_1.6.2 bit64_4.0.5 GenomeInfoDbData_1.2.8
#&gt; [16] lifecycle_1.0.1 stringr_1.4.0 zlibbioc_1.42.0
#&gt; [19] evaluate_0.15 knitr_1.39 tzdb_0.3.0
#&gt; [22] fastmap_1.1.0 parallel_4.2.2 sys_3.4
#&gt; [25] fansi_1.0.3 openssl_2.0.2 BiocManager_1.30.18
#&gt; [28] vroom_1.5.7 jsonlite_1.8.0 XVector_0.36.0
#&gt; [31] bit_4.0.4 fs_1.5.2 credentials_1.3.2
#&gt; [34] hms_1.1.1 askpass_1.1 digest_0.6.29
#&gt; [37] stringi_1.7.6 bookdown_0.32 cli_3.3.0
#&gt; [40] tools_4.2.2 bitops_1.0-7 magrittr_2.0.3
#&gt; [43] sass_0.4.1 RCurl_1.98-1.6 tibble_3.1.7
#&gt; [46] crayon_1.5.1 pkgconfig_2.0.3 ellipsis_0.3.2
#&gt; [49] rstudioapi_0.13 rmarkdown_2.19 R6_2.5.1
#&gt; [16] lifecycle_1.0.1 stringr_1.4.0 zlibbioc_1.42.0
#&gt; [19] evaluate_0.15 knitr_1.39 tzdb_0.3.0
#&gt; [22] fastmap_1.1.0 parallel_4.2.2 sys_3.4
#&gt; [25] fansi_1.0.3 openssl_2.0.2 BiocManager_1.30.18
#&gt; [28] vroom_1.5.7 jsonlite_1.8.0 XVector_0.36.0
#&gt; [31] bit_4.0.4 fs_1.5.2 credentials_1.3.2
#&gt; [34] hms_1.1.1 askpass_1.1 digest_0.6.29
#&gt; [37] stringi_1.7.6 bookdown_0.32 cli_3.3.0
#&gt; [40] tools_4.2.2 bitops_1.0-7 magrittr_2.0.3
#&gt; [43] sass_0.4.1 RCurl_1.98-1.6 tibble_3.1.7
#&gt; [46] crayon_1.5.1 pkgconfig_2.0.3 ellipsis_0.3.2
#&gt; [49] rstudioapi_0.13 rmarkdown_2.19 R6_2.5.1
#&gt; [52] compiler_4.2.2</code></pre>
<div id="refs" class="references csl-bib-body hanging-indent">
<div id="ref-Taguchi2022b" class="csl-entry">
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<script type="text/javascript">
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87 changes: 44 additions & 43 deletions inst/doc/TDbasedUFE.html
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<!DOCTYPE html>


<html>

<head>
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line-height: normal;
}

code > span.kw { color: #E07020; }
code > span.dt { color: #404040; }
code > span.dv { color: #D02070; }
code > span.bn { color: #d14; }
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code > span.ch { color: #40A040; }
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</script>
<script type="text/javascript">
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var links = document.links;
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links[i].target = '_blank';
Expand Down Expand Up @@ -879,43 +880,43 @@ <h1><span class="header-section-number">4</span> Conclusions</h1>
#&gt; R version 4.2.2 Patched (2022-11-10 r83330)
#&gt; Platform: x86_64-pc-linux-gnu (64-bit)
#&gt; Running under: Ubuntu 18.04.6 LTS
#&gt;
#&gt;
#&gt; Matrix products: default
#&gt; BLAS: /usr/lib/x86_64-linux-gnu/atlas/libblas.so.3.10.3
#&gt; LAPACK: /usr/lib/x86_64-linux-gnu/atlas/liblapack.so.3.10.3
#&gt;
#&gt;
#&gt; locale:
#&gt; [1] LC_CTYPE=ja_JP.UTF-8 LC_NUMERIC=C LC_TIME=ja_JP.UTF-8
#&gt; [4] LC_COLLATE=ja_JP.UTF-8 LC_MONETARY=ja_JP.UTF-8 LC_MESSAGES=ja_JP.UTF-8
#&gt; [7] LC_PAPER=ja_JP.UTF-8 LC_NAME=C LC_ADDRESS=C
#&gt; [10] LC_TELEPHONE=C LC_MEASUREMENT=ja_JP.UTF-8 LC_IDENTIFICATION=C
#&gt;
#&gt; [1] LC_CTYPE=ja_JP.UTF-8 LC_NUMERIC=C LC_TIME=ja_JP.UTF-8
#&gt; [4] LC_COLLATE=ja_JP.UTF-8 LC_MONETARY=ja_JP.UTF-8 LC_MESSAGES=ja_JP.UTF-8
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#&gt; [10] LC_TELEPHONE=C LC_MEASUREMENT=ja_JP.UTF-8 LC_IDENTIFICATION=C
#&gt;
#&gt; attached base packages:
#&gt; [1] stats4 stats graphics grDevices utils datasets methods base
#&gt;
#&gt; [1] stats4 stats graphics grDevices utils datasets methods base
#&gt;
#&gt; other attached packages:
#&gt; [1] MOFAdata_1.12.0 tximportData_1.24.0 tximport_1.24.0 readr_2.1.2
#&gt; [5] rTensor_1.4.8 GenomicRanges_1.48.0 GenomeInfoDb_1.32.2 IRanges_2.30.0
#&gt; [9] S4Vectors_0.34.0 BiocGenerics_0.42.0 BiocStyle_2.24.0 TDbasedUFE_0.1.0
#&gt;
#&gt; [1] MOFAdata_1.12.0 tximportData_1.24.0 tximport_1.24.0 readr_2.1.2
#&gt; [5] rTensor_1.4.8 GenomicRanges_1.48.0 GenomeInfoDb_1.32.2 IRanges_2.30.0
#&gt; [9] S4Vectors_0.34.0 BiocGenerics_0.42.0 BiocStyle_2.24.0 TDbasedUFE_0.1.0
#&gt;
#&gt; loaded via a namespace (and not attached):
#&gt; [1] tidyselect_1.1.2 xfun_0.31 bslib_0.3.1
#&gt; [4] purrr_0.3.4 vctrs_0.4.1 htmltools_0.5.2
#&gt; [7] usethis_2.1.6 yaml_2.3.5 utf8_1.2.2
#&gt; [10] rlang_1.0.2 pillar_1.7.0 jquerylib_0.1.4
#&gt; [1] tidyselect_1.1.2 xfun_0.31 bslib_0.3.1
#&gt; [4] purrr_0.3.4 vctrs_0.4.1 htmltools_0.5.2
#&gt; [7] usethis_2.1.6 yaml_2.3.5 utf8_1.2.2
#&gt; [10] rlang_1.0.2 pillar_1.7.0 jquerylib_0.1.4
#&gt; [13] glue_1.6.2 bit64_4.0.5 GenomeInfoDbData_1.2.8
#&gt; [16] lifecycle_1.0.1 stringr_1.4.0 zlibbioc_1.42.0
#&gt; [19] evaluate_0.15 knitr_1.39 tzdb_0.3.0
#&gt; [22] fastmap_1.1.0 parallel_4.2.2 sys_3.4
#&gt; [25] fansi_1.0.3 openssl_2.0.2 BiocManager_1.30.18
#&gt; [28] vroom_1.5.7 jsonlite_1.8.0 XVector_0.36.0
#&gt; [31] bit_4.0.4 fs_1.5.2 credentials_1.3.2
#&gt; [34] hms_1.1.1 askpass_1.1 digest_0.6.29
#&gt; [37] stringi_1.7.6 bookdown_0.32 cli_3.3.0
#&gt; [40] tools_4.2.2 bitops_1.0-7 magrittr_2.0.3
#&gt; [43] sass_0.4.1 RCurl_1.98-1.6 tibble_3.1.7
#&gt; [46] crayon_1.5.1 pkgconfig_2.0.3 ellipsis_0.3.2
#&gt; [49] rstudioapi_0.13 rmarkdown_2.19 R6_2.5.1
#&gt; [16] lifecycle_1.0.1 stringr_1.4.0 zlibbioc_1.42.0
#&gt; [19] evaluate_0.15 knitr_1.39 tzdb_0.3.0
#&gt; [22] fastmap_1.1.0 parallel_4.2.2 sys_3.4
#&gt; [25] fansi_1.0.3 openssl_2.0.2 BiocManager_1.30.18
#&gt; [28] vroom_1.5.7 jsonlite_1.8.0 XVector_0.36.0
#&gt; [31] bit_4.0.4 fs_1.5.2 credentials_1.3.2
#&gt; [34] hms_1.1.1 askpass_1.1 digest_0.6.29
#&gt; [37] stringi_1.7.6 bookdown_0.32 cli_3.3.0
#&gt; [40] tools_4.2.2 bitops_1.0-7 magrittr_2.0.3
#&gt; [43] sass_0.4.1 RCurl_1.98-1.6 tibble_3.1.7
#&gt; [46] crayon_1.5.1 pkgconfig_2.0.3 ellipsis_0.3.2
#&gt; [49] rstudioapi_0.13 rmarkdown_2.19 R6_2.5.1
#&gt; [52] compiler_4.2.2</code></pre>
<div id="refs" class="references csl-bib-body hanging-indent">
<div id="ref-Roy2022" class="csl-entry">
Expand Down Expand Up @@ -1005,7 +1006,7 @@ <h1><span class="header-section-number">4</span> Conclusions</h1>

<script type="text/javascript">
$(document).ready(function () {

// Map "enter" keypress to the same action as a cursor click
function navigateLink(e) {
if (e.key === "Enter") {
Expand Down

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