trajectory_test1

In this Repository we are using One Recent Trajectory analysis software StaVia (Via 2.0) or pyVia Installation and Usage :

Installation :

In order to run Pyvia software (which is very difficult) both in Linux and Mac , we have to follow below steps carefully .

• I have tried and Installed both in Mac (Personal laptop ) and in Linux (Either in workstation or in Gitpod or in any cloud environment).

• Here I am giving Gitpod platoform example :

** Step - 1 : Create Github account and and repository with any name (Here it is 1rajecroy_test1 ) ** Step - 2 : Connect this repository w+inside Gitpod (which opens vscode interface) ** Step - 3 : We create miniconda_install.sh and pyvia_env.yml (to create conda environment and pyvia installation) . Copy the content and paste in your required files ** Step - 4 : Open Terminal in vscode (from Gitpod) and Run bash miniconda_install.sh . This will install miniconda inside virtual machine. ** Step - 5 : Open new bash Terminal (very important) , so conda will be accesible . ** Step - 6 : Run conda create -s pyvia_env.yml to install all pyvia and dependency packages . ** Step - 7 : create trajectory_analysis_test.ipynb and click select kernel and Python environments and then select installed conda environment (here in my case ViaEnv2 ) which is present in my pyvia_env.yml name .

Working Example :

Run the basic analysis steps with basic example

** Step - 1 : Load the libaries

1. Basic workflow This vignette shows the basic workflow of Via and how to access the different visualizations after running the computations. The dataset is a toy multifurcation. We start by importing modules.

from pyVIA.core import * import pyVIA.datasets_via as datasets_via import pandas as pd import scanpy as sc

import warnings warnings.filterwarnings('ignore') First load all the data.

adata_counts = datasets_via.toy_multifurcating() print(adata_counts) true_label = adata_counts.obs['group_id'].tolist() ncomps = 30 sc.tl.pca(adata_counts, svd_solver='arpack', n_comps=ncomps)