Cyclum | Identify circular trajectories in scRNA-seq data | Data Manipulation library
kandi X-RAY | Cyclum Summary
kandi X-RAY | Cyclum Summary
Cyclum is a package to tackle cell cycle. It provides methods to recover cell cycle information and remove cell cycle factor from the scRNA-seq data. The methodology is to rely on the circular manifold, instead of the marker genes. We provide an Auto-Encoder based realization at this time, and we are adding Gaussian Process Latent Variable Model soon.
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- Train the model
- Close the session
- Fit the model
- Write a DataFrame to a binary file
- Writes a matrix to a binary file
- Convert an integer to bytes
- Refine labels
- Wrapper around circular_divide
- Linear inner product
- Compute the linear curve
- Read data from binary format
- Read a matrix from a binary file
- Builds the model
- Make the decoder
- Make a circular layer
- Make a circular decoder
- Calculate the circular coupling of a circular system
- Perform preprocessing
- Calculate the correct sample
- Generate a rotation matrix
- Create a function that converts a pandas dataframe
Cyclum Key Features
Cyclum Examples and Code Snippets
Community Discussions
Trending Discussions on Data Manipulation
QUESTION
I am working with the R programming language.
I have the following dataset:
...ANSWER
Answered 2022-Apr-10 at 05:36Up front, "1,3,4" != 1
. It seems you should look to split the strings using strsplit(., ",")
.
QUESTION
I've the following table
Owner Pet Housing_Type A Cats;Dog;Rabbit 3 B Dog;Rabbit 2 C Cats 2 D Cats;Rabbit 3 E Cats;Fish 1The code is as follows:
...ANSWER
Answered 2022-Mar-15 at 08:48One approach is to define a helper function that matches for a specific animal, then bind the columns to the original frame.
Note that some wrangling is done to get rid of whitespace to identify the unique animals to query.
QUESTION
I have this data frame:
...ANSWER
Answered 2022-Mar-10 at 04:12We can use stri_replace_all_regex
to replace your color_1
into integers together with the arithmetic operator.
Here I've stored your values into a vector color_1_convert
. We can use this as the input in stri_replace_all_regex
for better management of the values.
QUESTION
I have a database with columns M1
, M2
and M3
. These M values correspond to the values obtained by each method. My idea is now to make a rank column for each of them. For M1
and M2
, the rank will be from the highest value to the lowest value and M3
in reverse. I made the output table for you to see.
ANSWER
Answered 2022-Mar-07 at 14:15Using rank
and relocate
:
QUESTION
I working on a Python project that has a DataFrame like this:
...ANSWER
Answered 2022-Feb-24 at 20:48You could use the idxmax
method on axis:
QUESTION
I would like to know of a fast/efficient way in any program (awk/perl/python) to split a csv file (say 10k columns) into multiple small files each containing 2 columns. I would be doing this on a unix machine.
...ANSWER
Answered 2021-Dec-12 at 05:22With your show samples, attempts; please try following awk
code. Since you are opening files all together it may fail with infamous "too many files opened error" So to avoid that have all values into an array and in END
block of this awk
code print them one by one and I am closing them ASAP all contents are getting printed to output file.
QUESTION
Good afternoon, friends!
I'm currently performing some calculations in R (df is displayed below). My goal is to display in a new column the first non-null value from selected cells for each row.
My df is:
...ANSWER
Answered 2022-Feb-03 at 11:16One option with dplyr
could be:
QUESTION
I am again struggling with transforming a wide df into a long one using pivot_longer
The data frame is a result of power analysis for different effect sizes and sample sizes, this is how the original df looks like:
ANSWER
Answered 2022-Feb-03 at 10:59library(tidyverse)
example %>%
pivot_longer(cols = starts_with("es"), names_to = "type", names_prefix = "es_", values_to = "es") %>%
pivot_longer(cols = starts_with("pwr"), names_to = "pwr", names_prefix = "pwr_") %>%
filter(substr(type, 1, 3) == substr(pwr, 1, 3)) %>%
mutate(pwr = parse_number(pwr)) %>%
arrange(pwr, es, type)
QUESTION
Suppose I have the following 10 variables (num_var_1, num_var_2, num_var_3, num_var_4, num_var_5, factor_var_1, factor_var_2, factor_var_3, factor_var_4, factor_var_5):
...ANSWER
Answered 2021-Dec-26 at 10:11You may define a function FUN(n)
that creates a data set as shown in OP.
QUESTION
I am trying to tidy up some data that is all contained in 1 column called "game_info" as a string. This data contains college basketball upcoming game data, with the Date, Time, Team IDs, Team Names, etc. Ideally each one of those would be their own column. I have tried separating with a space delimiter, but that has not worked well since there are teams such as "Duke" with 1 part to their name, and teams with 2 to 3 parts to their name (Michigan State, South Dakota State, etc). There also teams with "-" dashes in their name.
Here is my data:
...ANSWER
Answered 2021-Dec-16 at 15:25Here's one with regex. See regex101 link for the regex explanations
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