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Main.AboutThisSite History
Hide minor edits - Show changes to markup
February 26, 2019, at 02:20 PM
by 132.170.195.160 -
Changed lines 64-66 from:
*norm_* : Normalized output based on user input (default: limit)
*raw_* : Non-normalized output
to:
*norm_* : Normalized output based on user input (default: limit)
*raw_* : Non-normalized output
February 26, 2019, at 02:19 PM
by 132.170.195.160 -
Changed line 70 from:
*_group* : Grouped stats/fit based on column headers.
to:
*_group* : Grouped stats/fit based on column headers.
February 26, 2019, at 02:19 PM
by 132.170.195.160 -
Changed lines 62-63 from:
Output files are generated in the ./outfiles/ directory and are labeled according to their input file (example.csv-*). This includes:
to:
Output files are generated in the ./outfiles/ directory and are labeled according to their input file (example.csv-*):
February 26, 2019, at 02:19 PM
by 132.170.195.160 -
Changed line 70 from:
*_group : Grouped stats/fit based on column headers.
to:
*_group* : Grouped stats/fit based on column headers.
February 26, 2019, at 02:18 PM
by 132.170.195.160 -
Changed lines 64-66 from:
*_norm_* : Normalized output based on user input (default: limit)
*_raw_* : Non-normalized output
to:
*norm_* : Normalized output based on user input (default: limit)
*raw_* : Non-normalized output
February 26, 2019, at 02:17 PM
by 132.170.195.160 -
Changed lines 64-70 from:
- _norm_ : Normalized output based on user input (default: limit)
- _raw_ : Non-normalized output
- _stats_ : Initial seed , max, and Kd values
- _fit_ : Global abundance fits for each curve modeled by these values
- _group : Grouped stats/fit based on column headers.
to:
*_norm_* : Normalized output based on user input (default: limit)
*_raw_* : Non-normalized output
*_stats_* : Initial seed , max, and Kd values
*_fit_* : Global abundance fits for each curve modeled by these values
*_group : Grouped stats/fit based on column headers.
Changed lines 74-78 from:
- .png/pdf : Graphical output of abundance fits from matplotlib
to:
*.png/pdf : Graphical output of abundance fits from matplotlib
February 26, 2019, at 02:16 PM
by 132.170.195.160 -
Changed lines 64-70 from:
*_norm_* : Normalized output based on user input (default: limit)
*_raw_* : Non-normalized output
*_stats_* : Initial seed , max, and Kd values
*_fit_* : Global abundance fits for each curve modeled by these values
*_group : Grouped stats/fit based on column headers.
to:
- _norm_ : Normalized output based on user input (default: limit)
- _raw_ : Non-normalized output
- _stats_ : Initial seed , max, and Kd values
- _fit_ : Global abundance fits for each curve modeled by these values
- _group : Grouped stats/fit based on column headers.
Changed lines 74-78 from:
*.png/pdf : Graphical output of abundance fits from matplotlib
to:
- .png/pdf : Graphical output of abundance fits from matplotlib
February 26, 2019, at 02:16 PM
by 132.170.195.160 -
Changed lines 62-65 from:
Output files are generated in the ./outfiles/ directory. This includes:
Output files are labeled according to their input file (example.csv-*)
to:
Output files are generated in the ./outfiles/ directory and are labeled according to their input file (example.csv-*). This includes:
February 26, 2019, at 02:14 PM
by 132.170.195.160 -
Deleted lines 63-72:
- Statistics for each curve: initial seed , max, and Kd values.
- Global abundance fits for each curve modeled by these values.
- Normalized global abundance fits to their limits (maxima set to 1), with additional normalization options.
- Grouping to obtain means, standard deviations for statistical analyses.
- Graphical output (.png and .pdf) of abundance fits using matplotlib.
Changed lines 66-76 from:
*_norm_* : Normalized output based on user input (default: limit)
*_raw_* : Non-normalized output
*_stats_* : initial seed , max, and Kd values
*_fit_* : Global abundance fits for each curve modeled by these values
*_group : Grouped stats/fit based on column headers
to:
*_norm_* : Normalized output based on user input (default: limit)
*_raw_* : Non-normalized output
*_stats_* : Initial seed , max, and Kd values
*_fit_* : Global abundance fits for each curve modeled by these values
*_group : Grouped stats/fit based on column headers.
Stats include means and standard deviations for each group.
Fits are generated from the mean of the stats.
*.png/pdf : Graphical output of abundance fits from matplotlib
February 26, 2019, at 02:09 PM
by 132.170.195.160 -
Changed lines 68-69 from:
- Normalized global abundance fits to their limits (maxima = 1), with additional normalization options. The non-normalized (raw) outputs are also generated.
to:
- Normalized global abundance fits to their limits (maxima set to 1), with additional normalization options.
Changed lines 77-78 from:
to:
*_raw_* : Non-normalized output
*_stats_* : initial seed , max, and Kd values
*_fit_* : Global abundance fits for each curve modeled by these values
*_group : Grouped stats/fit based on column headers
February 26, 2019, at 02:05 PM
by 132.170.195.160 -
Changed lines 74-78 from:
to:
Output files are labeled according to their input file (example.csv-*)
*_norm_* : Normalized output based on user input (default: limit)
February 26, 2019, at 02:02 PM
by 132.170.195.160 -
Changed lines 64-65 from:
- Global abundance fits modeled by initial seed , max, and Kd values.
to:
- Statistics for each curve: initial seed , max, and Kd values.
- Global abundance fits for each curve modeled by these values.
Changed lines 70-71 from:
- Grouping to obtain standard deviations of initial seed values for statistical comparisons.
to:
- Grouping to obtain means, standard deviations for statistical analyses.
Added lines 73-74:
February 26, 2019, at 01:55 PM
by 132.170.195.160 -
Changed lines 64-72 from:
Global abundance fits modeled by initial seed , max, and Kd values.
Normalized global abundance fits to their limits (maxima = 1), with additional normalization options. The non-normalized (raw) outputs are also generated.
Grouping to obtain standard deviations of initial seed values for statistical comparisons.
Graphical output (.png and .pdf) of abundance fits using matplotlib.
to:
- Global abundance fits modeled by initial seed , max, and Kd values.
- Normalized global abundance fits to their limits (maxima = 1), with additional normalization options. The non-normalized (raw) outputs are also generated.
- Grouping to obtain standard deviations of initial seed values for statistical comparisons.
- Graphical output (.png and .pdf) of abundance fits using matplotlib.
February 26, 2019, at 01:55 PM
by 132.170.195.160 -
Changed lines 13-15 from:
qPyCR accepts '.csv' formatted fluorescence data from qPCR reactions. The .csv sheet should contain a 'Cycle' column. Subsequent reaction columns are grouped based on their headers. Example input data is provided with the source code.
to:
qPyCR accepts '.csv' formatted fluorescence data from qPCR reactions. The .csv sheet should contain a 'Cycle' column. Subsequent reaction columns are grouped based on their headers. Column headers should be labeled as <Group>-<Sample>, without spaces or special characters. Example input data is provided with the source code.
Added lines 62-65:
Output files are generated in the ./outfiles/ directory. This includes:
February 26, 2019, at 01:49 PM
by 132.170.195.160 -
Changed lines 8-10 from:
Mac users should see this guide on Python installation, to obtain an updated release.
to:
Mac users should see this guide on Python installation, to obtain an updated release, separate from the default bundled installation.
February 26, 2019, at 01:47 PM
by 132.170.195.160 -
Changed lines 6-7 from:
qPyCR requires the installation of the Python modules: numpy, scipy, pandas, and matplotlib. We recommend using pip to obtain packages.
to:
qPyCR requires the installation of the Python modules: numpy, scipy, pandas, and matplotlib. We recommend using pip2 to obtain packages.
February 26, 2019, at 01:44 PM
by 132.170.195.160 -
Changed lines 13-15 from:
qPyCR accepts '.csv' formatted fluorescence data from qPCR reactions. The .CSV sheet should contain a 'Cycle' column. Subsequent reaction columns are grouped based on their headers. Example input data is provided with the source code.
to:
qPyCR accepts '.csv' formatted fluorescence data from qPCR reactions. The .csv sheet should contain a 'Cycle' column. Subsequent reaction columns are grouped based on their headers. Example input data is provided with the source code.
February 26, 2019, at 01:44 PM
by 132.170.195.160 -
Changed lines 13-15 from:
qPyCR accepts .CSV formatted fluorescence data from qPCR reactions. The .CSV sheet should contain a 'Cycle' column. Subsequent reaction columns are grouped based on their headers. Example input data is provided with the source code.
to:
qPyCR accepts '.csv' formatted fluorescence data from qPCR reactions. The .CSV sheet should contain a 'Cycle' column. Subsequent reaction columns are grouped based on their headers. Example input data is provided with the source code.
February 26, 2019, at 01:44 PM
by 132.170.195.160 -
Changed lines 26-29 from:
> python qPyCR.py -f example.csv
Note: Mac users will likely use the command 'python2'.
to:
> python2 qPyCR.py -f example.csv
Changed lines 30-31 from:
to:
> python2 qPyCR.py --help
February 26, 2019, at 01:43 PM
by 132.170.195.160 -
Changed lines 18-21 from:
The source installation directory contains two .PY files and two folders labeled ./infiles/ and ./outfiles/.
Place the properly formatted .CSV file in the ./infiles/ directory.
to:
The source installation directory contains two '.py' files and two folders labeled ./infiles/ and ./outfiles/.
Place the properly formatted '.csv' file in the ./infiles/ directory.
Changed line 70 from:
Graphical output (.PNG and .PDF) of abundance fits using matplotlib.
to:
Graphical output (.png and .pdf) of abundance fits using matplotlib.
February 26, 2019, at 01:24 PM
by 132.170.195.160 -
Changed lines 26-27 from:
> python qPyCR.py -f example.csv
to:
> python qPyCR.py -f example.csv
Changed lines 32-33 from:
to:
February 26, 2019, at 01:24 PM
by 132.170.195.160 -
Changed lines 26-27 from:
> python qPyCR.py -f example.csv
to:
> python qPyCR.py -f example.csv
Changed lines 32-33 from:
to:
February 26, 2019, at 01:23 PM
by 132.170.195.160 -
Changed lines 26-27 from:
> python qPyCR.py -f example.csv
to:
> python qPyCR.py -f example.csv
Changed lines 32-33 from:
to:
February 26, 2019, at 11:54 AM
by 132.170.195.160 -
Changed line 34 from:
usage: qPyCR.py [-h] [-f FILENAME] [-i INDIR] [-o OUTDIR] [-n NORMALIZE]
to:
usage: qPyCR.py [-h] [-f FILENAME] [-i INDIR] [-o OUTDIR] [-n NORMALIZE]
Changed lines 37-38 from:
to:
February 26, 2019, at 11:52 AM
by 132.170.195.160 -
Changed lines 4-5 from:
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Changed lines 11-12 from:
to:
Changed lines 16-17 from:
to:
Changed lines 62-63 from:
to:
February 26, 2019, at 11:50 AM
by 132.170.195.160 -
Changed lines 30-61 from:
to:
For more information on usage options:
> python qPyCR.py --help
usage: qPyCR.py [-h] [-f FILENAME] [-i INDIR] [-o OUTDIR] [-n NORMALIZE]
[-w WEIGHT] [-c CYCLES]
optional arguments:
-h, --help show this help message and exit
-f FILENAME, --file FILENAME
--file=<your-file.csv>
-i INDIR, --in_dir INDIR
directory for incoming files, default = ./infiles/
-o OUTDIR, --out_dir OUTDIR
directory for outgoing files, default = ./outfiles/
-n NORMALIZE, --norm NORMALIZE
limit (default), max, global
-w WEIGHT, --weight WEIGHT
if True, use weighting function in fitting
-c CYCLES, --cycles CYCLES
Number of cycles for fit
February 26, 2019, at 11:39 AM
by 132.170.195.160 -
Changed lines 8-10 from:
to:
Mac users should see this guide on Python installation, to obtain an updated release.
Changed lines 13-15 from:
.CSV formatted fluorescence data from qPCR reactions. The .CSV sheet should contain a 'Cycle' column. Subsequent reaction columns are grouped based on their headers. Example input data is provided with the source code.
to:
qPyCR accepts .CSV formatted fluorescence data from qPCR reactions. The .CSV sheet should contain a 'Cycle' column. Subsequent reaction columns are grouped based on their headers. Example input data is provided with the source code.
USAGE
The source installation directory contains two .PY files and two folders labeled ./infiles/ and ./outfiles/.
Place the properly formatted .CSV file in the ./infiles/ directory.
Open a shell and navigate to the source installation directory.
Here's the basic usage example:
> python qPyCR.py -f example.csv
Note: Mac users will likely use the command 'python2'.
Changed lines 35-36 from:
Normalized global abundance fits to their limits (maxima -> 1), with additional normalization options.
to:
Normalized global abundance fits to their limits (maxima = 1), with additional normalization options. The non-normalized (raw) outputs are also generated.
February 26, 2019, at 11:18 AM
by 132.170.195.160 -
Changed lines 11-13 from:
.CSV formatted fluorescence data from qPCR reactions. The .CSV sheet should contain a 'Cycle' column. Subsequent reaction columns Example input data is provided with the source code.
to:
.CSV formatted fluorescence data from qPCR reactions. The .CSV sheet should contain a 'Cycle' column. Subsequent reaction columns are grouped based on their headers. Example input data is provided with the source code.
Changed lines 16-19 from:
Global abundance fits modeled by initial seed values, max, and Kd.
Normalized global abundance fits to their limits (maxima -> 1).
to:
Global abundance fits modeled by initial seed , max, and Kd values.
Normalized global abundance fits to their limits (maxima -> 1), with additional normalization options.
Changed line 22 from:
Graphical output (.PNG and .PDF) of abundance fits.
to:
Graphical output (.PNG and .PDF) of abundance fits using matplotlib.
February 26, 2019, at 11:14 AM
by 132.170.195.160 -
Changed lines 1-4 from:
This is a default page.if ! auth edit
Loginifend
to:
qPyCR is written for Python 2.7 and uses a command line interface to generate numerical and graphical output.
REQUIREMENTS
qPyCR requires the installation of the Python modules: numpy, scipy, pandas, and matplotlib. We recommend using pip to obtain packages.
INPUT
.CSV formatted fluorescence data from qPCR reactions. The .CSV sheet should contain a 'Cycle' column. Subsequent reaction columns Example input data is provided with the source code.
OUTPUT
Global abundance fits modeled by initial seed values, max, and Kd.
Normalized global abundance fits to their limits (maxima -> 1).
Grouping to obtain standard deviations of initial seed values for statistical comparisons.
Graphical output (.PNG and .PDF) of abundance fits.
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