regrMultBy1or2point

<code>regrMultBy1or2point</code> regresses each col of matrix according to 'refLst'(describing rownames of inDat). 
If 'refLst' conatins 2 groups, the 1st group will be set to the 1st value of 'regrTo' (and the 2nd group of 'refLst' to the 2nd 'regtTo')

The efficient treatment and convenient analysis of experimental high-throughput (omics) data gets facilitated through this collection of diverse functions.
Several functions address advanced object-conversions, like manipulating lists of lists or lists of arrays, reorganizing lists to arrays or into separate vectors, merging of multiple entries, etc.
Another set of functions provides speed-optimized calculation of standard deviation (sd), coefficient of variance (CV) or standard error of the mean (SEM)
for data in matrixes or means per line with respect to additional grouping (eg n groups of replicates).
A group of functions facilitate dealing with non-redundant information, by indexing unique, adding counters to redundant or eliminating lines with respect redundancy in a given reference-column, etc.
Help is provided to identify very closely matching numeric values to generate (partial) distance matrixes for very big data in a memory efficient manner or to reduce the complexity of large data-sets by combining very close values.
Other functions help aligning a matrix or data.frame to a reference using partial matching or to mine an experimental setup to extract patterns of replicate samples.
Many times large experimental datasets need some additional filtering, adequate functions are provided.
Convenient data normalization is supported in various different modes, parameter estimation via permutations or boot-strap as well as flexible testing of multiple pair-wise combinations using the framework of 'limma' is provided, too.
Batch reading (or writing) of sets of files and combining data to arrays is supported, too.

Wolfgang Raffelsberger

wrMisc

Analyze Experimental High-Throughput (Omics) Data

regrMultBy1or2point function

<dl><dt>inDat</dt>
<dd>matrix or data.frame</dd>
<dt>refLst</dt>
<dd>list of names existing in inDat (one group of names for each value in 'regrTo'), to be transformed in values precised in 'regTo'; if no matches to names of 'inDat' found, the 2 lowest and/or highest highest values will be chosen</dd>
<dt>regrTo</dt>
<dd>(numeric,length=2) range (at scale 0-1) of target-values for mean of elements cited in 'refLst'</dd>
<dt>silent</dt>
<dd>(logical) suppress messages</dd>
<dt>callFrom</dt>
<dd>(character) allow easier tracking of message(s) produced</dd></dl>

Arguments

Rescaling of multiple data-sets according to reference data using regression — regrMultBy1or2point

<dl>

<dt>inDat</dt>
<dd>matrix or data.frame</dd>


<dt>refLst</dt>
<dd>list of names existing in inDat (one group of names for each value in 'regrTo'), to be transformed in values precised in 'regTo'; if no matches to names of 'inDat' found, the 2 lowest and/or highest highest values will be chosen</dd>


<dt>regrTo</dt>
<dd>(numeric,length=2) range (at scale 0-1) of target-values for mean of elements cited in 'refLst'</dd>


<dt>silent</dt>
<dd>(logical) suppress messages</dd>


<dt>callFrom</dt>
<dd>(character) allow easier tracking of message(s) produced</dd>

</dl>

regrMultBy1or2point: Rescaling of multiple data-sets according to reference data using regression

Description

Usage

Value

Arguments

See Also

Examples