Greetings, I'm happy to announce support for multiple phenotypes by FaST-LMM's single_snp function. Running with more phenotypes can generate more data, so we've also added new features related to caching and filtering out unneeded output lines. A new notebook<https://nbviewer.jupyter.org/github/fastlmm/FaST-LMM/blob/master/doc/ipynb/fastlmm2021.ipynb> demonstrates all the new features. A university user requested these feature and then used them to do a multi-day run with 16,000 phenotypes. That run found a couple areas with promising associations. To install FaST-LMM, start with Miniconda or Anaconda. (If already installed, un-install it with "pip uninstall fastlmm".) Then ... conda install "mkl==2019.4" "scipy" "numpy" pip install --no-build-isolation fastlmm * Carl
Really useful functionality. Thanks Carl! From: Carl KADIE <carlk@msn.com> Sent: Tuesday, June 8, 2021 4:10 PM To: fastlmm-user@python.org; fastlmm-dev@python.org Subject: [fastlmm-user] More multiple phenotype support in FaST-LMM Greetings, I'm happy to announce support for multiple phenotypes by FaST-LMM's single_snp function. Running with more phenotypes can generate more data, so we've also added new features related to caching and filtering out unneeded output lines. A new notebook<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fnbviewer.jupyter.org%2Fgithub%2Ffastlmm%2FFaST-LMM%2Fblob%2Fmaster%2Fdoc%2Fipynb%2Ffastlmm2021.ipynb&data=04%7C01%7C%7C902ac59f361844d5086108d92ad29cf4%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637587906326512965%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=8i4X6oD%2FBnzYn41YhPFsCXLyMu27bpp%2Fw3qx7lwVowQ%3D&reserved=0> demonstrates all the new features. A university user requested these feature and then used them to do a multi-day run with 16,000 phenotypes. That run found a couple areas with promising associations. To install FaST-LMM, start with Miniconda or Anaconda. (If already installed, un-install it with "pip uninstall fastlmm".) Then ... conda install "mkl==2019.4" "scipy" "numpy" pip install --no-build-isolation fastlmm - Carl
Hi Carl, fantastic news! I will test ASAP, Thanks a lot! Stefanie Am Mi., 9. Juni 2021 um 01:24 Uhr schrieb David Heckerman < heckerma@hotmail.com>:
Really useful functionality. Thanks Carl!
*From:* Carl KADIE <carlk@msn.com> *Sent:* Tuesday, June 8, 2021 4:10 PM *To:* fastlmm-user@python.org; fastlmm-dev@python.org *Subject:* [fastlmm-user] More multiple phenotype support in FaST-LMM
Greetings,
I’m happy to announce support for multiple phenotypes by FaST-LMM’s single_snp function. Running with more phenotypes can generate more data, so we’ve also added new features related to caching and filtering out unneeded output lines.
A new notebook <https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fnbviewer.jupyter.org%2Fgithub%2Ffastlmm%2FFaST-LMM%2Fblob%2Fmaster%2Fdoc%2Fipynb%2Ffastlmm2021.ipynb&data=04%7C01%7C%7C902ac59f361844d5086108d92ad29cf4%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637587906326512965%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=8i4X6oD%2FBnzYn41YhPFsCXLyMu27bpp%2Fw3qx7lwVowQ%3D&reserved=0> demonstrates all the new features.
A university user requested these feature and then used them to do a multi-day run with 16,000 phenotypes. That run found a couple areas with promising associations.
To install FaST-LMM, start with Miniconda or Anaconda.
(If already installed, un-install it with “pip uninstall fastlmm”.) Then …
conda install "mkl==2019.4" "scipy" "numpy" pip install --no-build-isolation fastlmm
- Carl _______________________________________________ fastlmm-user mailing list -- fastlmm-user@python.org To unsubscribe send an email to fastlmm-user-leave@python.org https://mail.python.org/mailman3/lists/fastlmm-user.python.org/ Member address: luecks@gmail.com
participants (5)
-
Amaya Hoyle -
Carl KADIE -
David Heckerman -
Harry Hames -
Stefanie Lück