Comments (4)
Sorry, I don't know how I missed your comment and just see it now.
We are also trying to add the option to control error rate, but failed with some attempts. The thing is the error rate is controlled by the length and position of each error, both are determined empirically as Markov Model and statistical mixture models. We still don't have a clear relationship between the error rate and these factors.
As to the code you are pointing to, that is about the alignment rate, namely how many reads can be aligned in one dataset. It's not the error rate of aligned reads.
Thanks for you advice.
from nanosim.
Using numpy.random.choice
http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.choice.html
switching a base out for another, inserting or deleting but at lower probability.
Also use some list for loops for poly runs of AAAA or TTTT and add or remove a letter or 2.
Probably not all that representative of "real" error that the MinION generates. Not sure how to validate, But was looking at which point some tools "break" depending on how messy the data could get.
Kind of moved on to just using the event data and dynamic time warping for some other project. But will no doubt be using something like NanoSim in the future
from nanosim.
Hello,
Ahh yes you are correct. My mistake :)
Would a close approximation error model be useful, that could be applied to the output to give more error than it currently does. I have just been introducing noise into the reads NanoSim creates and using the original read alignment, compared to the new "noisy" read alignment to calculate error.
Not all that great, but it kinda works. haha.
Regards,
from nanosim.
For curiosity, how are you introducing noise to the output reads and how do you determine if it works or not?
Thanks!
from nanosim.
Related Issues (20)
- Nanosim hangs in the middle HOT 18
- Infinite loop in function extract_reads in metagenome mode when length equals max length HOT 2
- Transcriptome mode error rate tsv explanation HOT 2
- Models for R10.3 or R10.4 flow cell
- Option to specify desired read coverage or sequencing depth HOT 2
- ValueError: Found array with 0 sample(s) (shape=(0, 1)) while a minimum of 1 is required. HOT 6
- Please specify the training reads and its reference genome! HOT 3
- Stuck at simulation stage HOT 4
- simulator.py genome FileNotFoundError: [Errno 2] No such file or directory: 'training_model_profile' HOT 1
- NanoSim for tuning Minimap2 parameters? HOT 2
- Models for newer versions of Guppy with sup basecalls HOT 3
- Options / suggestions for how to simulate nCats data? HOT 1
- Support for Dorado? HOT 2
- IndexError: list index out of range HOT 1
- Installation error HOT 4
- How to find reference genome for pre-trained models HOT 2
- Coverage breadth following metagenome characterization HOT 2
- Can't install Nanosim HOT 2
- Questions about the usage and processing of the expression profile HOT 1
- Failure in using Nanosim for transcriptome (ValueError: file does not contain alignment data)
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from nanosim.