Basal: Bin-level and region-level data from basal mouse brain...
In haowulab/TRESS: Toolbox for mRNA epigenetics sequencing analysis
Basal R Documentation
Bin-level and region-level data from basal mouse brain samples
Description
A data list containing both bin-level and region-level
transcriptome locations and read counts
across 7 paired input and IP replicates from basal mouse brain samples.
It also contains the size factor of each sample
for library size normalization.
Usage
data(Basal)
Format
A list containing two sublists: "Bins" and "Candidates".
In list "Bins", there are,
- Bins
A dataframe of 1000 obs and 5 variables,
containing the transcriptome location
for 1000 bins of length 50bps
- Counts
A data matrix of 1000 obs and 14 variables,
caontaining bin-level read counts
- sf
A numerical vector,
containing the size factors of 14 samples
estimated from the whole transcriptome using
bin-level read counts.
...
In list "Candidates", there are,
- Regions
A dataframe of 500 obs and 5 variables,
containing the transcriptome location
of 8011 candidates.
- Counts
A data matrix of 500 obs and 14 variables,
caontaining region-level read counts
...
Note, bins and regions may or may not overlap with each other,
as both of them are respectively randomly selected from the
whole set of bins and candidate regions.
However, both data share the same size factor for each sample.
haowulab/TRESS documentation built on Aug. 27, 2022, 7:11 p.m.
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| Basal | R Documentation |
Bin-level and region-level data from basal mouse brain samples
Description
A data list containing both bin-level and region-level transcriptome locations and read counts across 7 paired input and IP replicates from basal mouse brain samples. It also contains the size factor of each sample for library size normalization.
Usage
data(Basal)
Format
A list containing two sublists: "Bins" and "Candidates". In list "Bins", there are,
- Bins
A dataframe of 1000 obs and 5 variables, containing the transcriptome location for 1000 bins of length 50bps
- Counts
A data matrix of 1000 obs and 14 variables, caontaining bin-level read counts
- sf
A numerical vector, containing the size factors of 14 samples estimated from the whole transcriptome using bin-level read counts.
... In list "Candidates", there are,
- Regions
A dataframe of 500 obs and 5 variables, containing the transcriptome location of 8011 candidates.
- Counts
A data matrix of 500 obs and 14 variables, caontaining region-level read counts
... Note, bins and regions may or may not overlap with each other, as both of them are respectively randomly selected from the whole set of bins and candidate regions. However, both data share the same size factor for each sample.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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