Comments (1)
The normalisation methods GEO
or GLM
are used to compute the normalisation factors for positive and housekeeping probes.
They also used to compute the "negative factor" (poor naming choice though): "geometric mean" (GEO
) or the corresponding value from GLM
of negative probes.
To summarise NACHO computes a data.frame
with three columns:
- "Positive_factor"
- "Negative_factor"
- "House_factor" (not necessarily used)
The simple formula for the normalisation is:
(Count_i - geo(Negative_i)) * PositiveF (with PositiveF: mean(geo(Positive)) / geo(Positive_i))
or
(Count - Negative) * PositiveF * HousekeepingF
In addition negative counts are replaced with 0
.
For short, background is taken into account.
Although, you can add additional threshold to be more "biologically relevant".
If you are interested in details:
from nacho.
Related Issues (20)
- Using NACHO for single catridge assays HOT 3
- Question about sample sheet contents and formatting HOT 3
- Release NACHO 1.0.1
- Move to `data.table` framework HOT 1
- Visualisation after normalise function HOT 2
- Error: invalid first argument HOT 2
- Release NACHO 1.0.2 HOT 1
- Release NACHO 1.1.0
- PlexSet Analysis HOT 1
- load_rcc doesnt recognize subfolder HOT 7
- Pos and neg controls in RCC file HOT 3
- Allow named vector for RCC file in `load_rcc`? HOT 1
- Is it possible to upload a sample sheet using the NACHO shiny app? HOT 3
- Release NACHO 2.0.0
- Change to new cran checks badge URL HOT 2
- Differing Values in QC plots HOT 4
- Question about R^2 values in positive control linearity QC HOT 3
- Release NACHO 2.0.6 HOT 1
- excluding POS_F from positive control linearity calculation HOT 1
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