Describes the workflow used for preparation of a 16S rRNA gene amplicon (V3-V4 region) Library for sequencing on a MiSeq platform (Illumina) using V3 sequencing chemistry with 300 base pairs paired-end reads.
Describes how the DNA was isolated from salmon intestinal samples before preparations of 16S rRNA gene amplicons for the Illumina MiSeq system.
Creators: Sahar Hassani, Inga Leena Angell, Jon Olav Vik, Graceline Tina Kirubakaran, Gareth Gillard, Arne Gjuvsland, Fabian Grammes, Hanne Hellerud Hansen, Thomas Harvey, Torgeir R. Hvidsten, Vitor Martins dos Santos, Dominic Nanton, Stuart Owen, Jacob Seilø Torgersen, Sandve Simen, Lars Snipen, Natalie Stanford, Kristil Sundsaasen, Kristina Vagonyte-Hallan, Dagmar Waltemath, Jesse van Dam, RAGNHILD ÅNESTAD
Submitter: Inga Leena Angell
Gre2p activity monitored by NADPH absorbance using different enzyme concentrations. Activity is measured after different storage conditions (treatments) and in presence of different amounts of tween.
A python workflow is used to analyse the data and create a plot where the outcomes of the Selwyn test are plotted. It requires the following directory structure:
./Sewlyn_test_forS19.py ./tween/M1.csv ./tween/M2.csv ./tween/M3.csv ./tween/M4.csv ./treatments/M1.csv ./treatments/M2.csv ./treatments/M3.csv ...
Gre2p activity monitored by NADPH absorbance using different enzyme concentrations. Activity is measured after different storage conditions (treatments) and in presence of different amounts of tween. Also analysis of DLS data of homogeneity of Gre2p samples measured before and after these treatments.
A python workflow is used to analyse the data and create a plot of the data. It requires the following directory structure:
./Script_for_S13andS18.py ./Script_for_S22.py ./Script_for_S15.py
and as ...
This file contains the script for the downstream scRNA-Seq analysis including quality control using the barcode ranking method together with the tool DropletUtils to exclude empty droplets and undetected genes as well as standard data processing (normalisation, variable feature identification, scaling, and dimensionality reduction) using tools of Seurat (v.3.2.2). After cluster annotation the %mtDNA was plotted for both datasets.
Python workflow for the analysis of ITC-BIND, ITC-MIM and ITC-(r)SIM experiments. Organized in a *.zip folder. Requires the following directory structure:
./ITC_analysis.py ./input/BINDING/.apj ./input/BINDING/.csv ./input/KINETICS/.apj ./input/KINETICS/.csv ./scripts/binding_neu.py ./scripts/kinetics_neu.py
And can be executed by running python ITC_analysis.py in the directory. Filenames for the input *.apj and *.csv files are defined in ITC_analysis.py. The output directory is written by ...
SOP describing how to perform an ITC binding experiment with a MicroCal PEAQ ITC by Malvern. Note: the DOIs from the Chemotion database for the synthesis of HK and NDK are missing in this version beacuse the DOIs do not exist yet (as of 27.04.21)
This file contains the detailed experimental protocol for the cultivation of "induced sinoatrial bodies (iSABs), the scRNA-Seq procedure as well as the general computational workflow for data processing. The R-script is provided separately.
This SOP describes the preparation of pteridine ligand 3D structures from SMILES or other input formats with the LigPrep routine as embedded in Schrödinger Maestro for usage in docking runs and in silico ADME-Tox property prediction.
This SOP describes the docking receptor preparation of PTR1 and DHFR receptor PDB files, performed with the Maestro Protein PrepWizard and the Glide grid generation routine. The optional identification and integration of conserved structural water molecules with the WatCH tool is also covered.
This SOP describes the docking of pteridine libraries into PTR1 or DHFR target receptors, using Glide and Prime in Schrödinger Maestro as part of the Induced Fit workflow to allow for receptor side chain reorganization upon ligand binding.
This file contains the R-script to analyse single nuclei and single cell data of Bl6 and Fzt:DU mice previously processed with cellranger. The analyses utilizes the Seurat and harmony package to integrate three datasets before subsequent downstream analysis characterizing proliferative cardiomyocytes.