{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Vignette for Cao et al., 2017

", "

", "This notebook will show you how to work with the C. elegans L2-stage sci-RNA-seq data from Cao et al., 2017.

", "

It aims to cover the following use cases:

", "

", "1. Accessing the raw data

", "1. Exploring the expression pattern of a gene of interest

", "1. Finding differentially expressed genes between subsets of cells

", "1. Re-clustering subsets of the data using t-SNE

", "

", "You will need the `dplyr` and `ggplot` R packages, as well as the `monocle` package at version 2.3.5. Monocle is a comprehensive package for single cell analysis developed by the Trapnell lab. Monocle version 2.3.5 is the version that was used for the paper. The source code for Monocle 2.3.5 is available at:

", "

", "https://github.com/cole-trapnell-lab/single-cell-worm/Waterston_Data/monocle_2.3.5.tar.gz

", "

", "To install it, open a command line (outside this Jupyter notebook) and run:

", "

", "```

", "curl -O http://waterston.gs.washington.edu/sci_RNA_seq_gene_count_data/monocle_2.3.5.tar.gz

", "R CMD INSTALL monocle_2.3.5.tar.gz

", "```

", "

", "More recent versions of Monocle will produce different results for use case 4 (re-clustering with t-SNE) due to changes in how we preprocess the data before running t-SNE. We will update this vignette when we release the next version of Monocle, 2.6.0, to support the new version." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Warning message:

", "\"replacing previous import by 'splines::splineDesign' when loading 'VGAM'\"Warning message:

", "\"replacing previous import by 'grid::arrow' when loading 'monocle'\"Warning message:

", "\"replacing previous import by 'grid::unit' when loading 'monocle'\"Warning message:

", "\"replacing previous import by 'igraph::clusters' when loading 'monocle'\"Warning message:

", "\"replacing previous import by 'ggplot2::Position' when loading 'monocle'\"" ] } ], "source": [ "suppressPackageStartupMessages({

", " library(dplyr)

", " library(ggplot2)

", " library(monocle)

", "})" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "R version 3.2.1 (2015-06-18)

", "Platform: x86_64-unknown-linux-gnu (64-bit)

", "Running under: CentOS release 6.8 (Final)

", "

", "locale:

", " [1] LC_CTYPE=en_US LC_NUMERIC=C LC_TIME=en_US

", " [4] LC_COLLATE=en_US LC_MONETARY=en_US LC_MESSAGES=en_US

", " [7] LC_PAPER=en_US LC_NAME=C LC_ADDRESS=C

", "[10] LC_TELEPHONE=C LC_MEASUREMENT=en_US LC_IDENTIFICATION=C

", "

", "attached base packages:

", " [1] splines stats4 parallel stats graphics grDevices utils

", " [8] datasets methods base

", "

", "other attached packages:

", "[1] monocle_2.3.5 DDRTree_0.1.5 irlba_2.2.1

", "[4] VGAM_1.0-3 Biobase_2.30.0 BiocGenerics_0.16.1

", "[7] Matrix_1.2-7.1 ggplot2_2.2.1 dplyr_0.7.1

", "

", "loaded via a namespace (and not attached):

", " [1] Rcpp_0.12.11 RColorBrewer_1.1-2 plyr_1.8.4

", " [4] bindr_0.1 tools_3.2.1 densityClust_0.2.1

", " [7] digest_0.6.12 uuid_0.1-2 jsonlite_1.5

", "[10] evaluate_0.10.1 tibble_1.3.3 gtable_0.2.0

", "[13] lattice_0.20-35 pkgconfig_2.0.1 rlang_0.1.1

", "[16] igraph_1.0.1 IRdisplay_0.4.4 HSMMSingleCell_0.104.0

", "[19] IRkernel_0.7 bindrcpp_0.2 fastICA_1.2-1

", "[22] cluster_2.0.6 repr_0.12.0 stringr_1.2.0

", "[25] combinat_0.0-8 grid_3.2.1 glue_1.1.1

", "[28] R6_2.2.2 qlcMatrix_0.9.5 pheatmap_1.0.8

", "[31] limma_3.26.9 pbdZMQ_0.2-6 reshape2_1.4.2

", "[34] magrittr_1.5 matrixStats_0.52.2 scales_0.4.1

", "[37] assertthat_0.2.0 colorspace_1.3-2 stringi_1.1.5

", "[40] lazyeval_0.2.0 munsell_0.4.3 slam_0.1-35

", "[43] crayon_1.3.2 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sessionInfo()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This RData file contains both the data and some utility functions to help navigate it." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ "download.file(

", " \"http://waterston.gs.washington.edu/sci_RNA_seq_gene_count_data/Cao_et_al_2017_vignette.RData\",

", " destfile = \"Cao_et_al_2017_vignette.RData\")" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [], "source": [ "load(\"Cao_et_al_2017_vignette.RData\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- cds is a Monocle CellDataSet object containing the single cell RNA-seq data from the main L2-stage C. elegans experiment described in Cao et al., along with annotations.

", "- cds.neurons is a re-clustered subset of the neuronal cells from cds.

", "- cds.experiment.2 has data from the second C. elegans experiment described in Cao et al.. This includes intestine cells that were missed in the first experiment, but the data overall is lower quality than the first experiment. In the manuscript, we only included the intestine cells from this experiment and excluded the rest." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Use case 1: accessing the raw data

", "

", "The raw gene-by-cell UMI (unique molecular identifier) count matrix for a CellDataSet can be accessed using the `exprs` function. It is stored as a sparse matrix object (\"`.`\" = 0)

", "

", "Note that if you need \"even rawer\" data (FASTQ files), they are available at the Gene Expression Omnibus (www.ncbi.nlm.nih.gov/geo) under accession code GSE98561.

", "

", "If you aren't familiar with working with single cell RNA-seq data, we highly recommend that you take a look at the examples and utility functions presented in the other sections of this document instead of trying to dive in to the raw data directly." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "3 x 3 sparse Matrix of class \"dgCMatrix\"

", " cele-001-001.CATGACTCAA cele-001-001.AAGACGGCCA

", "WBGene00000001 . .

", "WBGene00000002 . .

", "WBGene00000003 . .

", " cele-001-001.GCCAACGCCA

", "WBGene00000001 .

", "WBGene00000002 .

", "WBGene00000003 ." ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exprs(cds)[1:3, 1:3]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The `fData` function is used to access gene annotations." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "



", " gene_id symbol num_cells_expressed

", "

", "\t WBGene00000001 WBGene00000001 aap-1 1016

", "\t WBGene00000002 WBGene00000002 aat-1 354

", "\t WBGene00000003 WBGene00000003 aat-2 897

", "

", "



", " cell n.umi plate Size_Factor num_genes_expressed tsne_1 tsne_2 Cluster peaks halo delta rho cell.type tissue

", "

", "\t cele-001-001.CATGACTCAA cele-001-001.CATGACTCAA 144 001 0.2368328 89 5.4866377 14.67085 20 FALSE TRUE 0.02491657 893.9855 Unclassified neurons Neurons

", "\t cele-001-001.AAGACGGCCA cele-001-001.AAGACGGCCA 790 001 1.2992911 419 -3.8619751 -27.63448 6 FALSE TRUE 0.40961274 812.2076 Germline Gonad

", "\t cele-001-001.GCCAACGCCA cele-001-001.GCCAACGCCA 832 001 1.3683674 338 -0.5594413 41.98569 13 FALSE TRUE 0.04445184 240.2908 Intestinal/rectal muscle Intestinal/rectal muscle

", "

", "



", " cell n.umi plate Size_Factor num_genes_expressed tsne_1 tsne_2 Cluster peaks halo delta rho tissue cell.type neuron.type

", "

", "\t cele-001-001.CATGACTCAA cele-001-001.CATGACTCAA 144 001 0.2368328 89 0.9574604 0.8288424 11 FALSE TRUE 0.37046400 108.71265 Neurons Unclassified neurons Cholinergic (11)

", "\t cele-001-001.AACTACGGCT cele-001-001.AACTACGGCT 201 001 0.3305791 129 -3.0567593 -41.4083795 8 FALSE FALSE 0.25861943 70.88069 Neurons Ciliated sensory neurons ASI/ASJ

", "\t cele-001-001.GAGGCTTATT cele-001-001.GAGGCTTATT 117 001 0.1924267 76 -18.5689290 -33.9833909 39 FALSE TRUE 0.02962754 37.29414 Neurons Ciliated sensory neurons AFD

", "

", "



", " facet tpm prop.cells.expr n.umi total.n.umi.for.facet

", "

", "\t Body wall muscle 7972.27222 0.96451347 157028 19390434

", "\t Gonad 390.16652 0.03757116 3597 11166871

", "\t Intestine 97.88569 0.09775967 102 1230975

", "\t Neurons 89.83882 0.01406926 187 2203067

", "\t Glia 72.96189 0.02148228 39 787560

", "\t Pharynx 49.97025 0.01237113 48 1122443

", "\t Hypodermis 47.05950 0.01821904 158 5821384

", "

", "



", " facet tpm prop.cells.expr n.umi total.n.umi.for.facet

", "

", "\t Distal tip cells 16165.1598 0.97520661 3405 202581

", "\t Body wall muscle 7972.2722 0.96451347 157028 19390434

", "\t Intestinal/rectal muscle 5211.8861 0.84740260 2622 439170

", "\t Sex myoblasts 218.2425 0.14776632 75 377288

", "\t Pharyngeal neurons 165.1210 0.01592357 14 85381

", "\t Other interneurons 137.8986 0.02483070 17 172852

", "\t Socket cells 123.7517 0.02793296 26 184774

", "\t Coelomocytes 115.4683 0.02503682 71 544263

", "\t Non-seam hypodermis 102.4186 0.02006689 56 1059546

", "\t Somatic gonad precursors 102.1766 0.06376812 75 823856

", "

", "



", " facet tpm prop.cells.expr n.umi total.n.umi.for.facet

", "

", "\t Cluster 21 9807.74014 0.91588785 446 49587

", "\t Cluster 16 8266.64832 0.66025641 363 47719

", "\t ASK 6720.61429 0.81944444 155 24157

", "\t ASI/ASJ 6482.22237 0.74358974 239 40396

", "\t ASG 2121.04289 0.39534884 48 26295

", "\t ASEL 1670.50501 0.37837838 17 11042

", "\t ASER 795.91129 0.28571429 16 15324

", "\t AWB/AWC 85.09161 0.02380952 4 23186

", "\t Cholinergic (15) 60.56935 0.01538462 1 14463

", "\t Pharyngeal (33) 58.35581 0.02857143 2 25101

", "

", "

function (gene, expr.info)

", "{

", " if (class(expr.info) == \"character\") {

", " expr.info = gsub(\"[.]\", \" \", tolower(expr.info))

", " if (expr.info == \"tissue\")

", " expr.info = tissue.expr.info

", " else if (expr.info == \"cell type\")

", " expr.info = cell.type.expr.info

", " else if (expr.info == \"neuron type\")

", " expr.info = neuron.type.expr.info

", " }

", " gene.id = get.gene.id(gene, fData.df = expr.info$gene.annotations)

", " data.frame(facet = names(expr.info$tpm[gene.id, ]), tpm = expr.info$tpm[gene.id,

", " ], prop.cells.expr = expr.info$prop.cells.expr[gene.id,

", " ], n.umi = expr.info$n.umi[gene.id, ], total.n.umi.for.facet = expr.info$total.n.umi.for.facet) %>%

", " arrange(-tpm)

", "}

function (cds, x)

", "{

", " with(pData(cds), !is.na(tissue) & tissue == x)

", "}



", "\t FALSE

", "\t TRUE

", "\t FALSE

", "\t FALSE

", "\t FALSE

", "\t TRUE

", "



", "\t 'Body wall muscle'

", "\t 'Pharynx'

", "\t 'Hypodermis'

", "\t 'Neurons'

", "\t 'Glia'

", "\t 'Gonad'

", "\t 'Intestine'

", "



", "\t 'Am/PH sheath cells'

", "\t 'Body wall muscle'

", "\t 'Canal associated neurons'

", "\t 'Cholinergic neurons'

", "\t 'Ciliated sensory neurons'

", "\t 'Coelomocytes'

", "\t 'Distal tip cells'

", "\t 'Dopaminergic neurons'

", "\t 'Excretory cells'

", "\t 'flp-1(+) interneurons'

", "\t 'GABAergic neurons'

", "\t 'Germline'

", "\t 'Intestinal/rectal muscle'

", "\t 'Intestine'

", "\t 'Non-seam hypodermis'

", "\t 'Other interneurons'

", "\t 'Oxygen sensory neurons'

", "\t 'Pharyngeal epithelia'

", "\t 'Pharyngeal gland'

", "\t 'Pharyngeal muscle'

", "\t 'Pharyngeal neurons'

", "\t 'Rectum'

", "\t 'Seam cells'

", "\t 'Sex myoblasts'

", "\t 'Socket cells'

", "\t 'Somatic gonad precursors'

", "\t 'Touch receptor neurons'

", "\t 'Vulval precursors'

", "



", "\t 'AFD'

", "\t 'ASEL'

", "\t 'ASER'

", "\t 'ASG'

", "\t 'ASI/ASJ'

", "\t 'ASK'

", "\t 'AWA'

", "\t 'AWB/AWC'

", "\t 'BAG'

", "\t 'CAN'

", "\t 'Cholinergic (11)'

", "\t 'Cholinergic (15)'

", "\t 'Cholinergic (23)'

", "\t 'Cholinergic (24)'

", "\t 'Cholinergic (26)'

", "\t 'Cholinergic (29)'

", "\t 'Cholinergic (3)'

", "\t 'Cholinergic (35)'

", "\t 'Cholinergic (36)'

", "\t 'Cluster 10'

", "\t 'Cluster 13'

", "\t 'Cluster 16'

", "\t 'Cluster 17'

", "\t 'Cluster 21'

", "\t 'Cluster 25'

", "\t 'Cluster 27'

", "\t 'Cluster 40'

", "\t 'Cluster 5'

", "\t 'Dopaminergic'

", "\t 'DVA'

", "\t 'flp-1(+)'

", "\t 'GABAergic'

", "\t 'Pharyngeal (33)'

", "\t 'Pharyngeal (37)'

", "\t 'PVC/PVD'

", "\t 'RIA'

", "\t 'RIC'

", "\t 'SDQ/ALN/PLN'

", "\t 'Touch receptor'

", "\t 'URX/AQR/PQR'

", "



", " gene set.1.n.umi set.2.n.umi set.1.tpm set.2.tpm higher.expr log2.ratio precision recall f.score

", "

", "\t tank-1 20 570 1794.188 36169.778 Set 2 4.332578 0.8536585 1.0000000 0.9210526

", "\t gcy-22 0 129 0.000 8862.360 Set 2 13.113475 1.0000000 0.8000000 0.8888889

", "\t gei-3 10 166 1095.928 12076.301 Set 2 3.460638 0.9090909 0.8571429 0.8823529

", "\t gcy-3 0 147 0.000 9593.506 Set 2 13.227842 1.0000000 0.7428571 0.8524590

", "\t gcy-6 66 0 6909.705 0.000 Set 1 12.754408 1.0000000 0.7297297 0.8437500

", "\t T27C4.1 30 164 3210.293 11338.218 Set 2 1.819968 0.6808511 0.9142857 0.7804878

", "

", "



", " gene set.1.n.umi set.2.n.umi set.1.tpm set.2.tpm higher.expr log2.ratio precision recall f.score

", "

", "\t gcy-6 66 0 6909.705 0.000 Set 1 12.754408 1.0000000 0.7297297 0.8437500

", "\t gcy-17 69 0 6553.874 0.000 Set 1 12.678132 1.0000000 0.6216216 0.7666667

", "\t crh-1 58 12 5675.336 800.504 Set 1 2.823924 0.8333333 0.6756757 0.7462687

", "\t gcy-20 53 0 5339.037 0.000 Set 1 12.382364 1.0000000 0.5945946 0.7457627

", "\t gcy-7 39 0 3709.660 0.000 Set 1 11.857071 1.0000000 0.5675676 0.7241379

", "\t unc-44 88 45 7647.438 2915.088 Set 1 1.390942 0.6000000 0.8108108 0.6896552

", "

", "

gene set.1.n.umi set.2.n.umi set.1.tpm set.2.tpm higher.expr log2.ratio precision recall f.score p.val q.val



", "\t gcy-3 0 147 0.000 9593.506 Set 2 13.227842 1.0000000 0.7428571 0.8524590 1.238145e-11 9.360380e-09

", "\t gcy-22 0 129 0.000 8862.360 Set 2 13.113475 1.0000000 0.8000000 0.8888889 2.699776e-11 1.020515e-08

", "\t tank-1 20 570 1794.188 36169.778 Set 2 4.332578 0.8536585 1.0000000 0.9210526 4.789133e-11 1.206861e-08

", "\t gcy-6 66 0 6909.705 0.000 Set 1 12.754408 1.0000000 0.7297297 0.8437500 1.053208e-08 1.487185e-06

", "\t gcy-17 69 0 6553.874 0.000 Set 1 12.678132 1.0000000 0.6216216 0.7666667 1.180306e-08 1.487185e-06

", "\t K09F6.9 0 75 0.000 5925.954 Set 2 12.532832 1.0000000 0.5428571 0.7037037 1.161684e-08 1.487185e-06

", "



", " gene set.1.n.umi set.2.n.umi set.1.tpm set.2.tpm higher.expr log2.ratio precision recall f.score

", "

", "\t mec-17 2720 118 24033.028 39.202902 Set 1 9.223503 0.9009288 0.8712575 0.8858447

", "\t mec-18 796 49 7040.671 17.963804 Set 1 8.536321 0.9094828 0.6317365 0.7455830

", "\t mtd-1 443 15 4025.528 5.513083 Set 1 9.271622 0.9476440 0.5419162 0.6895238

", "\t mec-7 4418 743 35936.308 239.162028 Set 1 7.225290 0.5563771 0.9011976 0.6880000

", "\t mec-1 1717 695 16304.188 328.822706 Set 1 5.627408 0.4609610 0.9191617 0.6140000

", "\t mec-9 726 337 7088.606 182.571539 Set 1 5.271088 0.5126263 0.6077844 0.5561644

", "

", "



", " gene set.1.n.umi set.2.n.umi set.1.tpm set.2.tpm higher.expr log2.ratio precision recall f.score

", "

", "\t tni-3 6981 93 3804.24742 18.57887 Anterior BWM 7.602169 0.9819890 1.0000000 0.9909127

", "\t cwn-1 59 3113 13.99762 1311.17230 Posterior BWM 6.449980 0.9821732 0.8968992 0.9376013

", "\t T21B6.3 13869 271 5966.03306 60.20010 Anterior BWM 6.607094 0.9553265 0.8867624 0.9197684

", "\t him-4 1366 12029 595.78605 3527.26462 Posterior BWM 2.563264 0.8371408 0.8806202 0.8583302

", "\t lec-5 862 9838 230.36587 2677.35386 Posterior BWM 3.532560 0.8626374 0.8519380 0.8572543

", "\t F41C3.5 2478 21353 592.75881 5575.97179 Posterior BWM 3.231274 0.7865412 0.8426357 0.8136228

", "

", "



", " gene set.1.n.umi set.2.n.umi set.1.tpm set.2.tpm higher.expr log2.ratio precision recall f.score

", "

", "\t tni-3 6981 93 3804.24742 18.5788744 Anterior BWM 7.602169 0.9819890 1.0000000 0.9909127

", "\t T21B6.3 13869 271 5966.03306 60.2000953 Anterior BWM 6.607094 0.9553265 0.8867624 0.9197684

", "\t glc-4 684 37 310.53057 11.4323046 Anterior BWM 4.642570 0.9506849 0.2767145 0.4286597

", "\t tre-3 555 5 214.79033 0.6369876 Anterior BWM 7.035742 0.9852399 0.2129187 0.3501639

", "\t F48E3.8 402 1 144.96720 0.1162907 Anterior BWM 7.020870 0.9947917 0.1523126 0.2641770

", "\t dpyd-1 289 6 91.93291 0.9050051 Anterior BWM 5.592715 0.9740933 0.1499203 0.2598480

", "\t ceh-34 307 2 131.08432 0.2528051 Anterior BWM 6.709189 0.9885057 0.1371611 0.2408964

", "\t seb-2 201 5 85.08025 0.6848107 Anterior BWM 5.658166 0.9750000 0.1244019 0.2206506

", "\t sfrp-1 335 2 145.18286 0.2754131 Anterior BWM 6.830763 0.9863946 0.1156300 0.2069950

", "\t F35C11.5 168 1 67.97453 0.5230727 Anterior BWM 5.479937 0.9923664 0.1036683 0.1877256

", "

", "



", " facet tpm prop.cells.expr n.umi total.n.umi.for.facet

", "

", "\t Cluster 21 9807.74014 0.91588785 446 49587

", "\t Cluster 16 8266.64832 0.66025641 363 47719

", "\t ASK 6720.61429 0.81944444 155 24157

", "\t ASI/ASJ 6482.22237 0.74358974 239 40396

", "\t ASG 2121.04289 0.39534884 48 26295

", "\t ASEL 1670.50501 0.37837838 17 11042

", "\t ASER 795.91129 0.28571429 16 15324

", "\t AWB/AWC 85.09161 0.02380952 4 23186

", "

", "



", " gene set.1.n.umi set.2.n.umi set.1.tpm set.2.tpm higher.expr log2.ratio precision recall f.score

", "

", "\t C39D10.2 226 1 5237.910 1.667334 Cluster 21 10.939377 0.9880952 0.7757009 0.8691099

", "\t T09B9.3 197 0 3836.121 0.000000 Cluster 21 11.905433 1.0000000 0.6074766 0.7558140

", "\t F15A4.5 157 15 3677.812 67.963116 Cluster 21 5.736879 0.8923077 0.5420561 0.6744186

", "\t flp-25 100 7 1775.299 44.020086 Cluster 21 5.301349 0.9137931 0.4953271 0.6424242

", "\t C18H7.6 118 0 2385.147 0.000000 Cluster 21 11.219863 1.0000000 0.4579439 0.6282051

", "\t cdh-3 79 11 1811.618 69.489017 Cluster 21 4.683736 0.8809524 0.3457944 0.4966443

", "\t K04D7.6 65 0 1110.520 0.000000 Cluster 21 10.117019 1.0000000 0.2710280 0.4264706

", "\t C29F4.3 53 0 1067.368 0.000000 Cluster 21 10.059842 1.0000000 0.2523364 0.4029851

", "\t K02E2.1 39 0 1084.714 0.000000 Cluster 21 10.083099 1.0000000 0.2523364 0.4029851

", "\t dhs-9 67 15 987.323 53.024505 Cluster 21 4.191836 0.8484848 0.2616822 0.4000000

", "

", "



", " gene set.1.n.umi set.2.n.umi set.1.tpm set.2.tpm higher.expr log2.ratio precision recall f.score

", "

", "\t F27C1.11 223 367 5302.959 1576.21303 Cluster 16 1.7494202 0.3537118 0.5192308 0.4207792

", "\t W05F2.7 137 309 3007.794 1054.38784 Cluster 16 1.5109326 0.3564356 0.4615385 0.4022346

", "\t M04B2.6 117 4 2144.256 14.78412 Cluster 16 7.0858594 0.9285714 0.2500000 0.3939394

", "\t ocr-2 100 81 2408.536 294.50719 Cluster 16 3.0268916 0.5465116 0.3012821 0.3884298

", "\t osm-10 66 32 1209.716 124.87432 Cluster 16 3.2646129 0.7222222 0.2500000 0.3714286

", "\t R102.2 363 926 8266.648 3753.48748 Cluster 16 1.1386865 0.2524510 0.6602564 0.3652482

", "\t T01D3.1 87 122 1849.955 382.64946 Cluster 16 2.2696298 0.4112903 0.3269231 0.3642857

", "\t ida-1 337 1211 7843.130 5636.27821 Cluster 16 0.4764307 0.2234848 0.7564103 0.3450292

", "\t lap-2 132 55 2344.214 231.93208 Cluster 16 3.3311228 0.5263158 0.2564103 0.3448276

", "\t rps-11 83 230 2013.967 1036.83972 Cluster 16 0.9564565 0.2863636 0.4038462 0.3351064

", "

", "



", " Cluster n.total n.cholinergic prop.cholinergic neuron.type

", "

", "\t 29 305 155 0.5081967 Cholinergic (29)

", "\t 23 45 19 0.4222222 Cholinergic (23)

", "\t 3 385 131 0.3402597 Cholinergic (3)

", "\t 26 261 81 0.3103448 Cholinergic (26)

", "\t 35 58 16 0.2758621 Cholinergic (35)

", "\t 36 128 35 0.2734375 Cholinergic (36)

", "\t 15 65 16 0.2461538 Cholinergic (15)

", "\t 12 68 14 0.2058824 DVA

", "\t 24 188 38 0.2021277 Cholinergic (24)

", "\t 8 117 23 0.1965812 ASI/ASJ

", "\t 11 1998 387 0.1936937 Cholinergic (11)

", "\t 6 160 21 0.1312500 SDQ/ALN/PLN

", "\t 25 363 43 0.1184573 Cluster 25

", "\t 41 211 24 0.1137441 Doublets

", "\t 16 156 17 0.1089744 Cluster 16

", "

", "

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22



", " cluster gene cluster.n.umi other.n.umi cluster.tpm other.tpm log2.ratio precision recall f.score

", "

", "\t 7 B0432.14 194 11 10886.411 5.8332893 10.637661 0.9047619 0.9500000 0.9268293

", "\t 13 nlp-42 298 16 23458.070 18.4945954 10.232794 0.8666667 0.9285714 0.8965517

", "\t 12 flp-12 1556 120 16722.790 134.5197992 6.947168 0.8478261 0.8041237 0.8253968

", "\t 13 T04C12.3 168 30 11975.053 31.5493333 8.523188 0.7037037 0.6785714 0.6909091

", "\t 21 lgc-39 305 77 4677.683 97.0702337 5.575835 0.7019231 0.6186441 0.6576577

", "\t 1 sem-2 128 63 6240.354 52.4115889 6.868331 0.6615385 0.6056338 0.6323529

", "\t 2 vglu-2 30 1 2356.216 0.6977763 10.438609 0.9523810 0.4444444 0.6060606

", "\t 5 Y48C3A.5 339 145 7097.543 147.9313494 5.574600 0.5747664 0.6340206 0.6029412

", "\t 11 glb-17 81 19 4790.632 16.9955396 8.056433 0.7352941 0.5000000 0.5952381

", "\t 9 nlp-5 34 24 3552.050 21.1320088 7.326374 0.5500000 0.6470588 0.5945946

", "

", "



", " facet tpm prop.cells.expr n.umi total.n.umi.for.facet

", "

", "\t 21 4677.68319 0.618644068 305 63153

", "\t 18 244.90291 0.060606061 4 14652

", "\t 19 232.84907 0.052884615 14 50800

", "\t 8 217.45530 0.038461538 18 80071

", "\t 4 155.65487 0.027100271 24 174660

", "\t 22 129.10174 0.024615385 10 117663

", "\t 1 79.17593 0.028169014 2 19954

", "\t 6 60.42661 0.014925373 1 17215

", "\t 9 56.34438 0.029411765 1 12093

", "\t 10 30.47108 0.008196721 1 26202

", "

", "



", " facet tpm prop.cells.expr n.umi total.n.umi.for.facet

", "

", "\t 2 2356.21566 0.44444444 30 11540

", "\t 14 37.52486 0.01587302 1 23493

", "\t 1 0.00000 0.00000000 0 19954

", "\t 3 0.00000 0.00000000 0 19911

", "\t 4 0.00000 0.00000000 0 174660

", "\t 5 0.00000 0.00000000 0 51233

", "\t 6 0.00000 0.00000000 0 17215

", "\t 7 0.00000 0.00000000 0 17691

", "\t 8 0.00000 0.00000000 0 80071

", "\t 9 0.00000 0.00000000 0 12093

", "

", "



", " facet tpm prop.cells.expr n.umi total.n.umi.for.facet

", "

", "\t 9 3200.3642 0.3823529 44 12093

", "\t 2 2944.3520 0.2888889 27 11540

", "\t 13 2128.1049 0.2500000 29 13140

", "\t 5 2087.7739 0.2731959 119 51233

", "\t 15 1992.1189 0.2941176 62 31426

", "\t 6 1721.6386 0.2686567 34 17215

", "\t 8 1527.0847 0.1826923 126 80071

", "\t 4 1344.6852 0.1585366 235 174660

", "\t 12 1114.1395 0.1718213 123 97104

", "\t 16 886.1635 0.1923077 16 19103

", "

", "