updated docs

index.md

@@ -19,11 +19,11 @@ There is strong evidence for large-scale genomic gradients helping to organize t
 
 **Project Lead(s)**
 
-Jacob W Vogel; Jakob Seidlitz
+Jacob W Vogel
 
 **Faculty Lead(s)**
 
-Theodore Satterthwaite; Aaron Alexander-Bloch
+Theodore Satterthwaite; Jakob Seidlitz
 
 
 **Analytic Replicator**
@@ -33,7 +33,7 @@ Maxwell Bertolero
 
 **Collaborators**
 
-Konrad Wagstyl, Ross Markello, Casey Paquola, Alexandr Diaz-Papkovic, Thomas Funck, Alan C Evans, Boris Bernhardt, Bratislav Misic
+Aaron Alexander-Bloch, Konrad Wagstyl, Ross Markello, Adam Pines, Valerie J Sydnor, Alexandr Diaz-Papkovich, Justine Hansen, Alan C Evans, Boris Bernhardt, Bratislav Misic
 
 
 **Project Start Date**
@@ -43,7 +43,7 @@ October 2018
 
 **Current Project Status**
 
-Drafting manuscript
+Preprint published; manuscript submitted
 
 
 **Dataset**
@@ -80,14 +80,18 @@ https://drive.google.com/drive/folders/1fOZRjUR3lyKsENMgG05WNAaJY26l6ham?usp=sha
 
 **Zotero library**
 
-Not yet established.
+None --> Paperpile used
 
 
 **Current work products**
 
 OHBM 2020 presentation --> https://www.humanbrainmapping.org/files/2020/ORAL_SESSION_Modeling_and_Analysis_Multivariate_multimodal_analysis.pdf
 
+OHBM 2022 presentation --> https://www.humanbrainmapping.org/files/2022/Oral%20Sessions/Imaging_Genetics_Mapping_the_Effects_of_Genetic_and_Transcriptional_Variation_on_the_Brain.pdf
+
+Preprint --> Coming soon...
+
 
 **Code documentation**
 
-Every single aspect of preprocessing, sample selection, analysis, plotting, etc has be thoroughly documented and annotated within 11 Jupyter notebooks, which can be found in the Git repo. These can be run in order (most importantly the first 3 notebooks), and all data and code necessary to execute them is avaialble within the repo *or* instructions are given on how to download necessary data from public repositories. Instructions for cloning python environment are provided in the documentation on the github repo. Since all of these analyses are based on public data, reproducing my environment, following the instructions and running the notebook should be sufficient for completely reproducing every aspect of the manuscript.
+Every single aspect of preprocessing, sample selection, analysis, plotting, etc has be thoroughly documented and annotated within 9 Jupyter notebooks, which can be found in the Git repo. These can be run in order (most importantly the first 3 notebooks), and all data and code necessary to execute them is avaialble within the repo *or* instructions are given on how to download necessary data from public repositories. Instructions for cloning python environment are provided in the documentation on the github repo. Since all of these analyses are based on public data, reproducing my environment, following the instructions and running the notebook should be sufficient for completely reproducing every aspect of the manuscript.