Releases: xysheep/C2G
v1.2.2 Bug fix
Update
- Fix a bug that argument "cofactor" conflicts with some old arguments.
- Fix a broken test data file
Quick Start
Before run the executable, you need to first install MATLAB Runtime 9.2 avaliable at https://www.mathworks.com/products/compiler/matlab-runtime.html.
You can test C2G.exe with provided example. In this example, "data.csv" is a n-by-m data matrix without header where n is number of cells and m is number of markers. "label.csv" is a 10 k-means defined clustering results. In label.csv, each row is one single number corresponding to clustering assignment of one cell in data.csv.
C2G.exe data.csv label.csv
If the your data is not transformed, you also need to set the "cofactor" option to make C2G transform the data. For mass cytometry, it's recommended to be 5. For flow cytometry, it's recommended to be 100.
C2G.exe data.csv label.csv cofactor 5
Usage
C2G.exe datafile clusterfile [...options]
Required Arguments:
datafile: Path to a CSV file of data matrix. This file should have a
n-by-m matrix without header. n is the number of cells and
m is number of markers. This data should already be
compensated and transformed, otherwise, need to use "cofactor"
option to transform them.
clusterfile: Path a CSV file of cluster labels. This file
should have a n-by-1 matrix without header. n is the number
of cells. Each row correspondong to one cell in datafile. 0
means unlabeled.
Optional Arguments:
Details of optional arguments are avaliable at https://github.com/xysheep/C2G
V1.2.1 Bug fix
Update
- Fix a bug that argument "cofactor" conflicts with some old arguments.
Quick Start
Before run the executable, you need to first install MATLAB Runtime 9.2 avaliable at https://www.mathworks.com/products/compiler/matlab-runtime.html.
You can test C2G.exe with provided example. In this example, "data.csv" is a n-by-m data matrix without header where n is number of cells and m is number of markers. "label.csv" is a 10 k-means defined clustering results. In label.csv, each row is one single number corresponding to clustering assignment of one cell in data.csv.
C2G.exe data.csv label.csv
If the your data is not transformed, you also need to set the "cofactor" option to make C2G transform the data. For mass cytometry, it's recommended to be 5. For flow cytometry, it's recommended to be 100.
C2G.exe data.csv label.csv cofactor 5
Usage
C2G.exe datafile clusterfile [...options]
Required Arguments:
datafile: Path to a CSV file of data matrix. This file should have a
n-by-m matrix without header. n is the number of cells and
m is number of markers. This data should already be
compensated and transformed, otherwise, need to use "cofactor"
option to transform them.
clusterfile: Path a CSV file of cluster labels. This file
should have a n-by-1 matrix without header. n is the number
of cells. Each row correspondong to one cell in datafile. 0
means unlabeled.
Optional Arguments:
Details of optional arguments are avaliable at https://github.com/xysheep/C2G
V1.2.0 Support build-in transformation
Update
- Support transformation of the data in compiled version of C2G
Quick Start
Before run the executable, you need to first install MATLAB Runtime 9.2 avaliable at https://www.mathworks.com/products/compiler/matlab-runtime.html.
You can test C2G.exe with provided example. In this example, "data.csv" is a n-by-m data matrix without header where n is number of cells and m is number of markers. "label.csv" is a 10 k-means defined clustering results. In label.csv, each row is one single number corresponding to clustering assignment of one cell in data.csv.
C2G.exe data.csv label.csv
If the your data is not transformed, you also need to set the "cofactor" option to make C2G transform the data. For mass cytometry, it's recommended to be 5. For flow cytometry, it's recommended to be 100.
C2G.exe data.csv label.csv cofactor 5
Usage
C2G.exe datafile clusterfile [...options]
Required Arguments:
datafile: Path to a CSV file of data matrix. This file should have a
n-by-m matrix without header. n is the number of cells and
m is number of markers. This data should already be
compensated and transformed, otherwise, need to use "cofactor"
option to transform them.
clusterfile: Path a CSV file of cluster labels. This file
should have a n-by-1 matrix without header. n is the number
of cells. Each row correspondong to one cell in datafile. 0
means unlabeled.
Optional Arguments:
Details of optional arguments are avaliable at https://github.com/xysheep/C2G
V1.1.1 Support for non-MATLAB users
Update
- Support for user without access to MATLAB
- Handles outliers better
- Support all parameters of source version in the executable
Quick Start
Before run the executable, you need to first install MATLAB Runtime 9.2 avaliable at https://www.mathworks.com/products/compiler/matlab-runtime.html.
You can test C2G.exe with provided example. In this example, "data.csv" is a n-by-m data matrix without header where n is number of cells and m is number of markers. "label.csv" is a 10 k-means defined clustering results. In label.csv, each row is one single number corresponding to clustering assignment of one cell in data.csv.
C2G.exe data.csv label.csv
Usage
C2G.exe datafile clusterfile [...options]
Required Arguments:
datafile: Path to a CSV file of data matrix. This file should have a
n-by-m matrix without header. n is the number of cells and
m is number of markers. This data should already be
compensated and transformed.
clusterfile: Path a CSV file of cluster labels. This file
should have a n-by-1 matrix without header. n is the number
of cells. Each row correspondong to one cell in datafile. 0
means unlabeled.
Optional Arguments:
Details of optional arguments are avaliable at https://github.com/xysheep/C2G
More Comprehensive Documents and Available Options
More Comprehensive Documents and Available Options
C2G update demo
In this release, I updated the demo.m and allow the user to see more detail while running C2G.
C2G first release
This is the first official release of C2G on github.