Tabula Muris Genome Coverage Track Settings
 
Tabula Muris single cell RNA-Seq genome coverage

Track collection: Single Cell FACS RNA-Seq of 44,779 cells from Tabula Muris

+  Description
+  All tracks in this collection (3)

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Track height: pixels (range: 11 to 128)
Data view scaling: Always include zero: 
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Windowing function: Smoothing window:  pixels
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Graph configuration help
All subtracks:
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 acinar cell Cv  pancreatic acinar cell Coverage (182 cells)    Data format 
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 adipocyte Cv  mesenchymal stem cell of adipose Coverage (2107 cells)    Data format 
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 astrocyte Cv  astrocyte Coverage (432 cells)    Data format 
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 B cell Cv  B cell Coverage (2029 cells)    Data format 
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 basal cell Cv  basal cell Coverage (1340 cells)    Data format 
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 basophil Cv  basophil Coverage (25 cells)    Data format 
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 Bergmann glial Cv  Bergmann glial cell Coverage (40 cells)    Data format 
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 bladder cell Cv  bladder cell Coverage (695 cells)    Data format 
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 blood cell Cv  blood cell Coverage (206 cells)    Data format 
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 brain pericyte Cv  brain pericyte Coverage (156 cells)    Data format 
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 Brush cell Cv  Brush cell of epithelium proper of large intestine Coverage (63 cells)    Data format 
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 cardiac muscle Cv  cardiac muscle cell Coverage (133 cells)    Data format 
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 CFU-GM Cv  granulocyte monocyte progenitor cell Coverage (134 cells)    Data format 
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 cilliated cell Cv  ciliated columnar cell of tracheobronchial tree Coverage (25 cells)    Data format 
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 class monocyte Cv  classical monocyte Coverage (90 cells)    Data format 
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 collecting duc Cv  kidney collecting duct epithelial cell Coverage (121 cells)    Data format 
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 comm lymph prg Cv  common lymphoid progenitor Coverage (156 cells)    Data format 
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 DN1 pro-T cell Cv  DN1 thymic pro-T cell Coverage (32 cells)    Data format 
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 EC-HS Cv  endothelial cell of hepatic sinusoid Coverage (182 cells)    Data format 
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 endocardial Cv  endocardial cell Coverage (165 cells)    Data format 
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 endothelial Cv  endothelial cell Coverage (3319 cells)    Data format 
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 enterocyte Cv  enterocyte of epithelium of large intestine Coverage (964 cells)    Data format 
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 enteroendocr Cv  enteroendocrine cell Coverage (59 cells)    Data format 
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 epiderm basal Cv  basal cell of epidermis Coverage (1648 cells)    Data format 
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 epidermal cell Cv  epidermal cell Coverage (276 cells)    Data format 
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 epithelial Cv  epithelial cell Coverage (201 cells)    Data format 
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 erythrocyte Cv  erythrocyte Coverage (91 cells)    Data format 
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 fibroblast Cv  fibroblast Coverage (2189 cells)    Data format 
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 goblet cell Cv  large intestine goblet cell Coverage (833 cells)    Data format 
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 granulocyte Cv  granulocyte Coverage (761 cells)    Data format 
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 hepatocyte Cv  hepatocyte Coverage (391 cells)    Data format 
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 HPC Cv  hematopoietic precursor cell Coverage (265 cells)    Data format 
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 immat T cell Cv  immature T cell Coverage (1337 cells)    Data format 
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 immature B Cv  immature B cell Coverage (344 cells)    Data format 
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 immature NK Cv  immature natural killer cell Coverage (36 cells)    Data format 
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 immature NKT Cv  immature NK T cell Coverage (37 cells)    Data format 
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 keratinocyte Cv  keratinocyte Coverage (330 cells)    Data format 
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 keratinocyteSC Cv  stem cell of epidermis Coverage (53 cells)    Data format 
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 keratinocyteSC Cv  keratinocyte stem cell Coverage (1404 cells)    Data format 
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 Kupffer cell Cv  Kupffer cell Coverage (61 cells)    Data format 
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 L.I. epithelia Cv  epithelial cell of large intestine Coverage (2019 cells)    Data format 
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 late pro-B Cv  late pro-B cell Coverage (306 cells)    Data format 
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 leukocyte Cv  leukocyte Coverage (683 cells)    Data format 
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 luminal cell Cv  luminal epithelial cell of mammary gland Coverage (578 cells)    Data format 
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 lung endothelia C  lung endothelial cell Coverage (693 cells)    Data format 
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 lung epithelia Cv  epithelial cell of lung Coverage (113 cells)    Data format 
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 lymphocyte Cv  lymphocyte Coverage (81 cells)    Data format 
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 macrophage Cv  macrophage Coverage (395 cells)    Data format 
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 mature NK Cv  mature natural killer cell Coverage (49 cells)    Data format 
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 MEP cell Cv  megakaryocyte-erythroid progenitor cell Coverage (55 cells)    Data format 
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 mesenchymalSC Cv  mesenchymal stem cell Coverage (499 cells)    Data format 
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 mesenchyme Cv  mesenchymal cell Coverage (830 cells)    Data format 
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 microglia Cv  microglial cell Coverage (4394 cells)    Data format 
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 monocyte Cv  monocyte Coverage (331 cells)    Data format 
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 myeloid cell Cv  myeloid cell Coverage (1208 cells)    Data format 
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 myofibroblast Cv  myofibroblast cell Coverage (178 cells)    Data format 
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 naive B cell Cv  naive B cell Coverage (692 cells)    Data format 
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 neuron Cv  neuron Coverage (281 cells)    Data format 
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 NK cell Cv  natural killer cell Coverage (171 cells)    Data format 
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 oligodendroc. Cv  oligodendrocyte Coverage (1574 cells)    Data format 
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 OPC Cv  oligodendrocyte precursor cell Coverage (203 cells)    Data format 
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 pancr B cell Cv  type B pancreatic cell Coverage (449 cells)    Data format 
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 pancr D cell Cv  pancreatic D cell Coverage (140 cells)    Data format 
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 pancr PPcell Cv  pancreatic PP cell Coverage (73 cells)    Data format 
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 pancreatic A Cv  pancreatic A cell Coverage (390 cells)    Data format 
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 pancreatic duc Cv  pancreatic ductal cell Coverage (161 cells)    Data format 
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 pre-B cell Cv  precursor B cell Coverage (517 cells)    Data format 
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 pre-granulocyt Cv  granulocytopoietic cell Coverage (221 cells)    Data format 
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 pre-NK cell Cv  pre-natural killer cell Coverage (22 cells)    Data format 
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 Pro APC Cv  professional antigen presenting cell Coverage (59 cells)    Data format 
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 proximal tube Cv  epithelial cell of proximal tubule Coverage (219 cells)    Data format 
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 satellite Cv  skeletal muscle satellite cell Coverage (540 cells)    Data format 
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 satellite SC Cv  skeletal muscle satellite stem cell Coverage (439 cells)    Data format 
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 Slamf1+ cell Cv  Slamf1-positive multipotent progenitor cell Coverage (134 cells)    Data format 
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 Slamf1- cell Cv  Slamf1-negative multipotent progenitor cell Coverage (713 cells)    Data format 
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 smooth muscle Cv  smooth muscle cell Coverage (42 cells)    Data format 
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 stellate cell Cv  pancreatic stellate cell Coverage (49 cells)    Data format 
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 stromal cell Cv  stromal cell Coverage (863 cells)    Data format 
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 T cell Cv  T cell Coverage (793 cells)    Data format 
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 T-reg Cv  regulatory T cell Coverage (27 cells)    Data format 
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 urothelial Cv  bladder urothelial cell Coverage (683 cells)    Data format 
    
Assembly: Mouse Dec. 2011 (GRCm38/mm10)

Description

Tabula Muris is a compendium of single cell transcriptome data from the model organism Mus musculus, containing nearly 100,000 cells from 20 organs and tissues. The data allow for direct and controlled comparison of gene expression in cell types shared between tissues, such as immune cells from distinct anatomical locations.

This track shows the results from FACS sorted cells sequenced with the SmartSeq2 protocol, as it has much higher transcript coverage. The sequencing data comprises more than 2TB and was summarized into a track at UCSC.

Display Conventions and Configuration

As indicated by the "..." after its name, this is a 'super track', a container for subtracks. There are three different subtracks:

Cell type expression:
A rectangle on the genome, at the location of a gene, filled with a bar graph that indicates the gene's expression by single cell cluster. The term "cluster" refers to a cluster of single cells, which usually represents a cell or tissue type. The height of the bar graph on the genome is the median expression level and a click-through on the bar chart displays a boxplot of expression level quartiles with outliers, per cluster. On the boxplot, the number of cells from each experiment is shown.
Coverage:
Bar graphs indicate the number of reads at this base pair. You may want to switch on auto-scaling of the y-axis. For configuration options, see the graph tracks configuration help page. These tracks are shown in "dense" by default, set any of the tracks to "full" to see the detailed coverage plot.
Splice Junctions:
Thick rectangles show exons around a splice site, connected by a line that indicates the intron. These gaps are shown and are annotated with the number of reads, in the 'score' field. You can use the 'score' filter on the track configuration page to show only introns with a certain number of supporting reads. The maximum number of reads that are shown is 1,000, even if more reads support an intron. These tracks are shown in dense by default, set this track to "pack" to see. Then click the splice junctions to see their score.

Methods

BAM files were provided by the data submitters, one (single end) or two files (paired end) per cell. The BAM alignments were used as submitted. They were merged with "samtools merge" into a single BAM file per cluster. The readgroup (RG) BAM tag indicates the original cell.

From the resulting merged BAM file, coverage was obtained using "wiggletools coverage" a tool written by Daniel Zerbino and the result was converted with the UCSC tool "wigToBigWig".

Also on the merged BAM file, the software IntronProspector was run with default settings. It retains reads with a gap longer than 70 bp and shorter than 500 kbp and merges them into annotated splice junctions.

Data Access

The merged BAM files, coverage bigWig files and splice junctions in bigBed format can be downloaded from the /gbdb fileserver.

Since the splice junction .bigBed files have their scores capped at 1000, the original IntronProspector .bed files are available in the same track hub directory. You can also find there *.calls.tsv files with more details about each junction, e.g. the number of uniquely mapping reads.

Credits

WiggleTools was written by Daniel Zerbino, IntronProspector was written by Mark Diekhans, track hubs were written to a large extent by Brian Raney and colleages at the UCSC Genome Browser. Track creation was done by Max Haeussler and tested by Jairo Navarro.

References

Zerbino DR, Johnson N, Juettemann T, Wilder SP, Flicek P. WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis. Bioinformatics. 2014 Apr 1;30(7):1008-9. PMID: 24363377; PMC: PMC3967112

Mark Diekhans, IntronProspector GitHub Repository. Github 2018

The Tabula Muris Consortium, Stephen R. Quake, Tony Wyss-Coray, Spyros Darmanis: Single-cell transcriptomic characterization of 20 organs and tissues from individual mice creates a Tabula Muris. bioRxiv preprint March 2018, accepted paper in Nature 2018 (562) p.367-372