RNA Sequencing - allen brain atlas resources online help

RNA Sequencing
Single Cell Transcriptomic Profiling
Single Cell Transcriptomic Profiling
Utilizing the Heatmap Viewer for LGd Cells
Searching
Gene Search
Differential Search
Cell Features
Search Results
Metadata Summary
Heatmap Viewer
Correlative Search
One of the goals of the Allen Institute’s Cell Types Program is to classify cortical neurons based on gene expression captured using single-cell
RNA sequencing. To date, RNA sequencing has been performed on cells from the lateral geniculate nucleus (LGd or LGN), primary visual cortex
(VISp or V1) and the anterior lateral motor area (ALM) of the young adult laboratory mouse. Enrichment of cells representing discrete neuronal
subpopulations was achieved using Cre-driven labeling and cell selection by Fluorescence Activated Cell Sorting (FACS). More information on the
methods used in this study can be found in the whitepapers located in Documentation.
The transcriptomics profiling data is available as downloadable files from the RNA-Seq tab on the Cell Types landing page.
Data collected from the LGd has a preliminary data visualization tool utilizing a heatmap to view possible cell classifications. Clicking on "RNASeq
heatmap for LGd" will take you to that visualization.
Utilizing the Heatmap Viewer for LGd Cells
Searching
Searching is available using three methods: (1) Gene Search, when looking for a specific gene of interest, (2) Differential Search, to find
enhanced gene expression when comparing cell type features and 3) Correlative Search, to find cell features that exhibit similar gene expression
to a "seed gene" selected from the results of a Gene or a Differential Search, or to find genes that are co-expressed in specific cells.
You can take advantage of our Gene Category or Differential curated searches by clicking on one of the links from the landing page. For the
broad class differential searches, the cell features chosen for the contrast cell features are all other broad classes. For the sub-class differential
searches, the cell features chosen for the contrast cell features are all other sub-classes within the same broad class.
Gene Search
When searching for a specific gene, type the unique identifier into the "Filter by Gene Name, Gene Symbol or Entrez Gene ID" text box and either
hit enter or click "Search". You can also narrow your search by selecting a cell features filter. Your search results will open in a heat map viewer.
Differential Search
When you do not have a gene marker to initiate your search, a differential search can be useful in that it will look for genes enhanced in the cell
type you are interested in. To perform a differential search, you must select target and contrasting cell features by selecting from the matrix that
opens when you click in either text box. The toggle switch to the right of the text boxes will exchange the Target and Contrast Cell Features.
Once you have selected your search criteria, clicking "Search" will open up your results in a heatmap viewer.
Cell Features
Clicking in the "Cell Features" text box will open a matrix with the various cell features in this resource. A two-layer classification was assigned for
each cell: the first "Class" indicates the broad class: Three classes of GABAergic neurons (Gad2), one glutamatergic class (Slc17a6), one
non-neuronal class (Olig1), and one distinct class (Lars2_Kcnmb1). The second classification, "Subclass" identifies putative subclasses within
each of these broad classes. The Classes and Subclasses were given names based on a set of marker genes that distinguish them. See the table
below to understand how the classes and subclasses relate to each other.
Cell Classes and Subclasses
Glutamatergic neurons
Class
Subclass
Slc17a6
Slc17a6_Tcrb
Slc17a6_Pcdhgb4
Slc17a6_Pigl
Slc17a6_Calb2
GABAergic neurons
Class
Subclass
Gad2_Sepp1
Gad2_Sepp1
Gad2_Chrna6
Tac1_Gabra4
Styk1_Cdh13_Car10
Chrna6_Plac9a
Styk1_Xylb
Gad2_Pthlh
Gad2_Syt4
Calb2_Plac9a
Gad2_Spata20
Plek2_Pkib
Gad2_Zar1
Cck_Serpina3g
Gad2_Rspo2
Cck_Npy_Pcdh15
Gad2_Pvalb
Plek2_Cpne4
Non neuronal cells
Class
Subclass
Olig1
Olig1_Pdgfra
Olig1_Rassf10
Olig1_Opalin
Other
Class
Subclass
Lars2_Kcnmb1
Lars2_Kcnmb1
The cell features are grouped by Class, Subclass, Region, Driver and Age. Each one of these features can be queried by clicking on the arrow to
open a drop-down menu with each of the variables listed. Check the box(es) next to the variable you would like to search to filter by that feature.
Cell Feature
Variables
Class
Gad2_Chrna6, Gad2_Sepp1, Gad2_Syt4, Lars2_Kcnmb1, Olig1, Slc17a6
Subclass
Choose a subclass from the Cell Classes and Subclasses table
Region
Mouse LGN - Core, Mouse LGN - Shell
Driver
Gad2-IRES-Cre, Slc17a6-IRES-Cre, Slc32a1-IRES-Cre, Snap25-IRES-Cre
Age
P53-P58
Search Results
Once you have conducted a gene or differential search or have selected one of the curated searches, your results will be loaded into a heatmap
viewer. Once you have clicked on a data point in the heat map, metadata will be populated in the summary above the heatmap.
Metadata Summary
The metadata summary outlines each of the 5 cell features, metadata on the gene (including symbol, name, expression values and related data)
and the find correlates function.
Heatmap Viewer
1. Gene List: List of genes defined by the search criteria by gene symbol. When the list is a result of a differential search, each gene will be
accompanied by both a "Fold Change" and "p-value". Selecting those column headers will toggle the sort of the gene list. When the list is
the result of a correlative search each gene will be accompanied by a Pearson's correlation, r.
2. Number of Genes: Number of genes that fit the search criteria.
3. Column Headers: Clicking in this box will allow you to change the initial sort parameters of the column headers
4. Classification: Indicates the class, subclass and region of the cell currently highlighted by the mouse
5. Scroll Bars: Use the scroll bars to see the entire dataset.
6. Gene Selection: Select genes by clicking on the checkbox next to the gene symbol in the gene list. View a heatmap with only selected
genes by clicking "View Selected Genes". Genes will be available for viewing until you click "Clear Selections" or clear your cache.
7. Filter Heatmap Function: To limit the amount of data displayed in the heat map use this function.
8. Color Map: Use this function to change the way the z-scored data is displayed or to view the log2 FPKM data.
9. Download: This link initiates download of the current heatmap data.
Column Sorting
The column headers on the x-axis of the heat map are a feature that can be changed
by the user. By default, the column headers are the class, subclass and region (in that
order), but any of the cell features can be used to sort the columns. Clicking the arrow
in the box in the upper left-hand corner of the heatmap will open a list of groupings
including the ones the user has created. To create a new grouping, click on "[Create
new grouping...]", and a window will open allowing you to create a new grouping.
Remember to save your selection.
To remove a grouping, hover the mouse over the grouping and a garbage can will appear. Click on the can to remove the grouping.
Filter Heatmap
To restrict the amount of data that are displayed in the heatmap, select the "Filter Heatmap" button below the heatmap. Filtering your heatmap is
a two-step process: first, select the "..." box to restrict your features, making sure to save your selections, and then toggle the filter heatmap
feature between "On" and "Off" by clicking the "Filter Heatmap" button.
Download Heatmap Data
Once you have found the data that you are interested in downloading and analyzing off-line, click on the "Download this data" link. The data will
be downloaded as three .csv files; one with metadata for the rows (genes), one for the columns (cells) and a matrix containing the FPKM values.
Color Map
To change the contrast of the heatmap display, click and drag the slider bars in the color scale
below the heatmap. Clicking on the scale will open a window allowing the user to choose from
several color scales or the log2 FPKM view.
Correlative Search
Once you have found a gene of interest either by performing a gene or differential search, you can look for cell types that show a similar pattern of
gene expression using the "Find Correlates" feature. This function will allow you to find cells with similar gene expression profiles as well as
allowing you to find co-expressed genes within a single cell.
From the heatmap,
click on a gene to
load that "seed gene"
into the search box.
You have the option
to select cell features
before clicking
"Search". All cell
types with similar
expression patterns
of your seed gene will
then be displayed in
the heat map. If you
filtered your search
using cell features, your heatmap will only display those features. Turn off the "Filter Heatmap" function to see all the cell types.