cycHumanBloodDesign

<p>This data set describes individual information, sleep
  condition and sampling time corresponding to each sample in
  'cycHumanBloodData'.</p>

There are two functions-meta2d and meta3d for
detecting rhythmic signals from time-series datasets. For analyzing
time-series datasets without individual information, 'meta2d' is
suggested, which could incorporates multiple methods from ARSER,
JTK_CYCLE and Lomb-Scargle in the detection of interested rhythms. For
analyzing time-series datasets with individual information, 'meta3d' is
suggested, which takes use of any one of these three methods to analyze
time-series data individual by individual and gives out integrated values
based on analysis result of each individual.

Gang Wu

MetaCycle

Evaluate Periodicity in Large Scale Data

Ron Anafi

John Hogenesch

Michael Hughes

Karl Kornacker

Xavier Li

Matthew Carlucci

cycHumanBloodDesign function

<p>A dataframe containing 4 columns described as below:</p><table><tr><td>
    [,1] </td>
<td> sample_library  </td>
<td> character  </td>
<td> sample ID</td>
</tr><tr><td>
    [,2] </td>
<td> subject         </td>
<td> character  </td>
<td> individual ID</td>
</tr><tr><td>
    [,3] </td>
<td> group           </td>
<td> character  </td>
<td> sleep condition</td>
</tr></table>

Format

cycHumanBloodDesign — cycHumanBloodDesign

cycHumanBloodDesign: cycHumanBloodDesign

Description

Usage

Arguments

Format

[,1]	sample_library	character	sample ID
[,2]	subject	character	individual ID
[,3]	group	character	sleep condition