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Hi, I am new to using this pipeline and I have been following the tutorial as it is provided.
I have a confusion regarding loading the matrixes. In the following tutorial (https://github.com/BUStools/getting_started/blob/master/velocity_tutorial.ipynb) in line (26) they are importing some loom file as a reference matrix. What exactly is this file. To my understanding the whole point using this kallisto pipeline is to generate loom file from spliced and unspliced matrices to generate loom file that can be fed to velocyto.
We are using the fastqs made from the BAM file of SRR6470906 and SRR6470907
In [17]:
import pandas as pd
import scanpy as sc
import numpy as np
import scipy as scp
import sklearn
import matplotlib.pyplot as plt
import matplotlib
import sys
import loompy
import scipy.optimize
import velocyto as vcy
import scvelo as scv
import glob
import pickle
import anndata
from collections import Counter
from sklearn.decomposition import PCA
from scipy.spatial.distance import pdist, squareform
from IPython.core.display import display, HTML
display(HTML("<style>.container { width:90% !important; }</style>"))
matplotlib.rcParams.update({'font.size': 22})
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
Import reference matrices
In [26]:
them = scv.read('data/ForebrainGlut/hgForebrainGlut.loom', cleanup=True, sparse=True, cache=True, backup_url='http://pklab.med.harvard.edu/velocyto/hgForebrainGlut/hgForebrainGlut.loom')
them.var_names_make_unique()
Variable names are not unique. To make them unique, call .var_names_make_unique.
The text was updated successfully, but these errors were encountered:
Hi, I am new to using this pipeline and I have been following the tutorial as it is provided.
I have a confusion regarding loading the matrixes. In the following tutorial (https://github.com/BUStools/getting_started/blob/master/velocity_tutorial.ipynb) in line (26) they are importing some loom file as a reference matrix. What exactly is this file. To my understanding the whole point using this kallisto pipeline is to generate loom file from spliced and unspliced matrices to generate loom file that can be fed to velocyto.
We are using the fastqs made from the BAM file of SRR6470906 and SRR6470907
In [17]:
import pandas as pd
import scanpy as sc
import numpy as np
import scipy as scp
import sklearn
import matplotlib.pyplot as plt
import matplotlib
import sys
import loompy
import scipy.optimize
import velocyto as vcy
import scvelo as scv
import glob
import pickle
import anndata
from collections import Counter
from sklearn.decomposition import PCA
from scipy.spatial.distance import pdist, squareform
from IPython.core.display import display, HTML
display(HTML("<style>.container { width:90% !important; }</style>"))
matplotlib.rcParams.update({'font.size': 22})
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
Import reference matrices
In [26]:
them = scv.read('data/ForebrainGlut/hgForebrainGlut.loom', cleanup=True, sparse=True, cache=True, backup_url='http://pklab.med.harvard.edu/velocyto/hgForebrainGlut/hgForebrainGlut.loom')
them.var_names_make_unique()
Variable names are not unique. To make them unique, call
.var_names_make_unique
.The text was updated successfully, but these errors were encountered: