舊號(hào)無(wú)故被封宁昭，小號(hào)再發(fā)一次

更多空間轉(zhuǎn)錄組文章：

1. 新版10X Visium

• 【10X空間轉(zhuǎn)錄組Visium】（一）Space Ranger 1.0.0(更新于20191205）
• 【10X空間轉(zhuǎn)錄組Visium】（二）Loupe Browser 4.0.0
• 【10X空間轉(zhuǎn)錄組Visium】（三）跑通Visium全流程記錄
• 【10X空間轉(zhuǎn)錄組Visium】（四）R下游分析的探索性代碼示例
  
• 【10X空間轉(zhuǎn)錄組Visium】（五）Visium原理踪栋、流程與產(chǎn)品
• 【10X空間轉(zhuǎn)錄組Visium】（六）新版Seurat v3.2分析Visium空間轉(zhuǎn)錄組結(jié)果的代碼實(shí)操
• 【10X空間轉(zhuǎn)錄組Visium】（七）思考新版Seurat V3.2作者在Github給予的回答

2. 舊版Sptial

• 【舊版空間轉(zhuǎn)錄組Spatial】（一）ST Spot Detector使用指南
• 【舊版空間轉(zhuǎn)錄組Spatial】（二）跑通流程試驗(yàn)記錄
• 【舊版空間轉(zhuǎn)錄組Spatial】（三）ST Spot Detector實(shí)操記錄

下載數(shù)據(jù)集

https://support.10xgenomics.com/spatial-gene-expression/datasets
我選擇的是：Mouse Brain Section (Coronal)

$ tar -xvf V1_Adult_Mouse_Brain_fastqs.tar
$ ls
V1_Adult_Mouse_Brain_S5_L001_I1_001.fastq.gz  V1_Adult_Mouse_Brain_S5_L001_R2_001.fastq.gz  V1_Adult_Mouse_Brain_S5_L002_R1_001.fastq.gz
V1_Adult_Mouse_Brain_S5_L001_I2_001.fastq.gz  V1_Adult_Mouse_Brain_S5_L002_I1_001.fastq.gz  V1_Adult_Mouse_Brain_S5_L002_R2_001.fastq.gz
V1_Adult_Mouse_Brain_S5_L001_R1_001.fastq.gz  V1_Adult_Mouse_Brain_S5_L002_I2_001.fastq.gz

• 同一個(gè)樣本的測(cè)序數(shù)據(jù)，這里總共有2條lane
• 每條lane因?yàn)槭请p索引的緣故绵跷，所以存在I1 I2 R1 R2共4個(gè)fastq文件、

• 所以總共有8條fastq
  與之對(duì)應(yīng)的情況是：

  
  
  image.png

運(yùn)行spaceranger count

此處選擇自動(dòng)對(duì)齊的方案
由于服務(wù)器沒(méi)有連接外網(wǎng)：所以手動(dòng)下載slide文件
https://support.10xgenomics.com/spatial-gene-expression/software/pipelines/latest/using/count

$ spaceranger count --id=V1_Adult_Mouse_Brain \
                      --transcriptome=/share/nas1/Data/luohb/Visium/reference/refdata-cellranger-mm10-3.0.0/  \
                      --fastqs=/share/nas1/Data/luohb/Visium/test2/V1_Adult_Mouse_Brain_fastqs \
                      --sample=V1_Adult_Mouse_Brain \
                      --image=/share/nas1/Data/luohb/Visium/test2/V1_Adult_Mouse_Brain_image.tif \
                      --slide=V19L01-041 \
                      --area=C1 \
                      --slidefile=/share/nas1/Data/luohb/Visium/test2/V19L01-041.gpr \
                      --localcores=32   \
                      --localmem=128

順利地跑完了方妖，因?yàn)榉?wù)器同時(shí)還跑著幾個(gè)比較大的任務(wù)广凸，然后居然跑了接近13個(gè)小時(shí)典鸡。被廓。。

image.png

查看結(jié)果文件

$ ls
_cmdline   _finalstate  _jobmode  _mrosource  _perf              _sitecheck              _tags       _uuid                         _vdrkill
_filelist  _invocation  _log      outs        _perf._truncated_  SPATIAL_RNA_COUNTER_CS  _timestamp  V1_Adult_Mouse_Brain.mri.tgz  _versions

$ cd outs/
$ ls
analysis       filtered_feature_bc_matrix     metrics_summary.csv  possorted_genome_bam.bam      raw_feature_bc_matrix     spatial
cloupe.cloupe  filtered_feature_bc_matrix.h5  molecule_info.h5     possorted_genome_bam.bam.bai  raw_feature_bc_matrix.h5  web_summary.html

• 查看web_summary.html

  
  
  image.png
  
  
  image.png
• 查看count管道輸出幾個(gè)包含自動(dòng)二級(jí)分析結(jié)果的CSV文件

$cd analysis/
$ls
clustering  diffexp  pca  tsne  umap

1. PCA降維結(jié)果：

$cd /pca/10_components
$ls
components.csv  dispersion.csv  features_selected.csv  projection.csv  variance.csv

投影

$head -3 projection.csv 
Barcode,PC-1,PC-2,PC-3,PC-4,PC-5,PC-6,PC-7,PC-8,PC-9,PC-10
AAACAAGTATCTCCCA-1,-10.281241313083257,-24.67223115562252,-0.19850052930601336,-2.1734929997144388,6.630976878797487,-0.12128746693282366,6.040708059434257,4.657495740394594,16.344239212184327,6.523601903899456
AAACAATCTACTAGCA-1,17.830458684877186,-27.53526668134934,15.877302377060623,9.74572143694312,-0.7208195934715782,-4.339470398396214,2.5444608437485288,-5.084679351848514,2.9247276185469495,-1.0731021612191327

components matrix

$less -S components.csv
PC,ENSMUSG00000051951,ENSMUSG00000089699,ENSMUSG00000025900,ENSMUSG00000025902,ENSMUSG00000033845,ENSMUSG00000025903,ENSMUSG00000104217,ENSMUSG00000033813,（略……）
1,9.807402710059275e-05,-0.0007359419037463138,0.0018506647696503106,0.0019216677830155664,-0.009477278899046813,-0.005003056852125207,0.0,-0.008498306263180
2,-0.0013017257339919546,0.0015759310908915448,0.0013809836795030965,0.0009513422156874659,0.007418499981929492,0.003222355732773671,0.0,0.00887178686827463,
3,-0.001920230193482586,0.003378841598139873,-0.00012165106820253075,-0.00024897415838216264,-0.0031447165300072175,-0.007787586978438225,0.0,-0.003148852394
（略……）

總方差的比例

$head -3 variance.csv
PC,Proportion.Variance.Explained
1,0.030645967432188836
2,0.015067575203691749

歸一化的離散度

$head -3 dispersion.csv
Feature,Normalized.Dispersion
ENSMUSG00000051951,0.261762717719762
ENSMUSG00000089699,-1.5988672040435437

2. t-SNE結(jié)果文件:

$cd ../../tsne/2_components/
$ls
projection.csv

$head -5 projection.csv 
Barcode,TSNE-1,TSNE-2
AAACAAGTATCTCCCA-1,-18.47081216664088,7.240054873818881
AAACAATCTACTAGCA-1,-4.219964329936257,-9.182632464702484
AAACACCAATAACTGC-1,14.744060324279337,13.360913482080413
AAACAGAGCGACTCCT-1,-11.72411901642397,-7.924228663324808

3. 聚類結(jié)果：

$cd ../../clustering/
$ls
graphclust          kmeans_2_clusters  kmeans_4_clusters  kmeans_6_clusters  kmeans_8_clusters
kmeans_10_clusters  kmeans_3_clusters  kmeans_5_clusters  kmeans_7_clusters  kmeans_9_clusters

對(duì)于每個(gè)聚類萝玷， spaceranger為每個(gè)點(diǎn)生成聚類分配cluster assignments

打開聚類3看看：

$cd kmeans_3_clusters
$ls
clusters.csv
$head -5 clusters.csv 
Barcode,Cluster
AAACAAGTATCTCCCA-1,1
AAACAATCTACTAGCA-1,3
AAACACCAATAACTGC-1,2
AAACAGAGCGACTCCT-1,1

4. 差異表達(dá)分析：

$cd ../../diffexp/
$ls
graphclust          kmeans_2_clusters  kmeans_4_clusters  kmeans_6_clusters  kmeans_8_clusters
kmeans_10_clusters  kmeans_3_clusters  kmeans_5_clusters  kmeans_7_clusters  kmeans_9_clusters

這次看個(gè)總表：

$cd /graphclust
$ls
differential_expression.csv
$head -3 differential_expression.csv 
Feature ID,Feature Name,Cluster 1 Mean Counts,Cluster 1 Log2 fold change,Cluster 1 Adjusted p value,Cluster 2 Mean Counts,Cluster 2 Log2 fold change,Cluster 2 Adjusted p value,Cluster 3 Mean Counts,Cluster 3 Log2 fold change,Cluster 3 Adjusted p value,Cluster 4 Mean Counts,Cluster 4 Log2 fold change,Cluster 4 Adjusted p value,Cluster 5 Mean Counts,Cluster 5 Log2 fold change,Cluster 5 Adjusted p value,Cluster 6 Mean Counts,Cluster 6 Log2 fold change,Cluster 6 Adjusted p value,Cluster 7 Mean Counts,Cluster 7 Log2 fold change,Cluster 7 Adjusted p value,Cluster 8 Mean Counts,Cluster 8 Log2 fold change,Cluster 8 Adjusted p value,Cluster 9 Mean Counts,Cluster 9 Log2 fold change,Cluster 9 Adjusted p value
ENSMUSG00000051951,Xkr4,0.09115907843838432,0.15688013442205495,0.9130108472807676,0.08789156406190936,0.094226986457139,1.0,0.059424476860418934,-0.5579910544947899,0.4792687534164091,0.09747791035014447,0.270272692975412,0.7950049780312995,0.08717356987748102,0.14776402072440886,1.0,0.05406634025868632,-0.6310298603360582,0.7980928917515894,0.15030400022885756,0.9570457266970553,0.22931236900985477,0.0606581027791399,-0.4319057525382224,1.0,0.10761817731957228,0.4400508833584902,1.0
ENSMUSG00000089699,Gm1992,0.0016574377897888059,1.3866145310996707,0.8220253607506287,0.0,0.423008752385563,1.0,0.0,0.22991150489664136,1.0,0.0033613072534532575,2.5793194965660433,0.5338242296758853,0.0,2.3542148981918345,1.0,0.003180372956393313,2.490599584065473,0.8676482778053517,0.0,1.5959470345290159,1.0,0.0,1.4568374963600368,1.0,0.0,2.146642828481177,1.0

5 .矩陣：Feature-Barcode Matrices
矩陣的每個(gè)元素是與特征（行）和條形碼（列）關(guān)聯(lián)的UMI的數(shù)量嫁乘。

$cd /share/nas1/Data/luohb/Visium/test2/V1_Adult_Mouse_Brain/outs
$ls
analysis       filtered_feature_bc_matrix     metrics_summary.csv  possorted_genome_bam.bam      raw_feature_bc_matrix     spatial
cloupe.cloupe  filtered_feature_bc_matrix.h5  molecule_info.h5     possorted_genome_bam.bam.bai  raw_feature_bc_matrix.h5  web_summary.html
$tree filtered_feature_bc_matrix
filtered_feature_bc_matrix
├── barcodes.tsv.gz
├── features.tsv.gz
└── matrix.mtx.gz
0 directories, 3 files

$tree raw_feature_bc_matrix
raw_feature_bc_matrix
├── barcodes.tsv.gz
├── features.tsv.gz
└── matrix.mtx.gz
0 directories, 3 files

$gzip -cd filtered_feature_bc_matrix/features.tsv.gz |head -3
ENSMUSG00000051951  Xkr4    Gene Expression
ENSMUSG00000089699  Gm1992  Gene Expression
ENSMUSG00000102343  Gm37381 Gene Expression

其中：

第一列 第二列 第三列
功能ID 基因名 標(biāo)識(shí)特征的類型

嘗試將矩陣加載到R

library(Matrix)
matrix_dir = "/share/nas1/Data/luohb/Visium/test2/V1_Adult_Mouse_Brain/outs/filtered_feature_bc_matrix/"
barcode.path <- paste0(matrix_dir, "barcodes.tsv.gz")
features.path <- paste0(matrix_dir, "features.tsv.gz")
matrix.path <- paste0(matrix_dir, "matrix.mtx.gz")
mat <- readMM(file = matrix.path)
feature.names = read.delim(features.path, 
                           header = FALSE,
                           stringsAsFactors = FALSE)
barcode.names = read.delim(barcode.path, 
                           header = FALSE,
                           stringsAsFactors = FALSE)
colnames(mat) = barcode.names$V1
rownames(mat) = feature.names$V1
dim(mat)
[1] 31053  2698

嘗試將矩陣加載到Python

import csv
import gzip
import os
import scipy.io
 
matrix_dir = "/share/nas1/Data/luohb/Visium/test2/V1_Adult_Mouse_Brain/outs/filtered_feature_bc_matrix"
mat = scipy.io.mmread(os.path.join(matrix_dir, "matrix.mtx.gz"))


features_path = os.path.join(matrix_dir, "features.tsv.gz")
feature_ids = [row[0] for row in csv.reader(gzip.open(features_path), delimiter="\t")]
gene_names = [row[1] for row in csv.reader(gzip.open(features_path), delimiter="\t")]
feature_types = [row[2] for row in csv.reader(gzip.open(features_path), delimiter="\t")]
barcodes_path = os.path.join(matrix_dir, "barcodes.tsv.gz")
barcodes = [row[0] for row in csv.reader(gzip.open(barcodes_path), delimiter="\t")]

6. 看圖片

$cd spatial/
$ls
aligned_fiducials.jpg  detected_tissue_image.jpg  scalefactors_json.json  tissue_hires_image.png  tissue_lowres_image.png  tissue_positions_list.csv

tissue_hires_image.png：較高像素的明場(chǎng)圖片

image.png

tissue_lowres_image.png：較低像素的明場(chǎng)圖片

image.png

image.png

相應(yīng)的像素坐標(biāo)轉(zhuǎn)換文件：scalefactors_json.json

$cat scalefactors_json.json
{"spot_diameter_fullres": 89.44476048022638, "tissue_hires_scalef": 0.17011142, "fiducial_diameter_fullres": 144.48769000651953, "tissue_lowres_scalef": 0.05

PS:這部有點(diǎn)像舊流程的ST_spot_detector的步驟了

其中：

• issue_hires_scalef：將原始全分辨率圖像中的像素位置轉(zhuǎn)換為tissue_hires_image.png中的像素位置的比例因子。
• tissue_lowres_scalef：將原始全分辨率圖像中的像素位置轉(zhuǎn)換為tissue_lowres_image.png中的像素位置的比例因子球碉。
• fiducial_diameter_fullres：跨越原始全分辨率圖像中基準(zhǔn)點(diǎn)直徑的像素?cái)?shù)蜓斧。
• spot_diameter_fullres：跨越原始全分辨率圖像中組織點(diǎn)直徑的像素?cái)?shù)。

detected_tissue_image.jpg:

image.png

tissue_positions_list.txt：

$head -2 tissue_positions_list.csv
ACGCCTGACACGCGCT-1,0,0,0,1252,1211
TACCGATCCAACACTT-1,0,1,1,1372,1280

其中列對(duì)應(yīng)著：

• barcode：與該點(diǎn)相關(guān)的條形碼的順序睁冬。
• in_tissue：二進(jìn)制挎春，指示該斑點(diǎn)位于組織的內(nèi)部（1）還是外部（0）。
• array_row：點(diǎn)在陣列中的行坐標(biāo)從0到77豆拨。該陣列有78行直奋。
• array_col：陣列中點(diǎn)的列坐標(biāo)。為了表示 the orange crate arrangement of the spots施禾，此列索引對(duì)偶數(shù)行使用0到126的偶數(shù)脚线，對(duì)奇數(shù)行使用1到127的奇數(shù)。注意弥搞，每行（偶數(shù)或奇數(shù)）有64個(gè)斑點(diǎn)邮绿。
• pxl_col_in_fullres：全分辨率圖像中斑點(diǎn)中心的列像素坐標(biāo)。
• pxl_row_in_fullres：全分辨率圖像中斑點(diǎn)中心的行像素坐標(biāo)攀例。

7. BAM：Barcoded BAM

$cd outs/
$samtools view possorted_genome_bam.bam |head -5
A00984:21:HMKLFDMXX:2:2117:10357:1235   16  1   3000100 255 25M199730N72M23S    *   0   0   TTTTTTTTTTTTTTTTTTTTTTTTGCAAGAAAAAAAATCAGATAACCGAGGAAAATTATTCATTATGAAGTACTACTTTCCACTTCATTTCATCCCATGTACTCTGCGTTGATACCACTG    F:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFF    NH:i:1  HI:i:1  AS:i:83 nM:i:1  RE:A:I  xf:i:0  ts:i:21 li:i:0  BC:Z:ACCAGACAAC QT:Z:FFFFFFFFFF CR:Z:GACGACGATCCGCGTT   CY:Z:FFFFFFFFFFFFFFFF   CB:Z:GACGACGATCCGCGTT-1 UR:Z:CCTGTTTGTTGT   UY:Z:FFFFFFFFFFFF   UB:Z:CCTGTTTGTTGT   RG:Z:V1_Adult_Mouse_Brain:0:1:HMKLFDMXX:2
A00984:21:HMKLFDMXX:1:1306:5041:10034   16  1   3000100 255 25M199611N95M   *   0   0   TTTTTTTTTTTTTTTTTTTTTTTTGAAATGACCACAGTGTACTTTATTTAATGATTTTTGTACTTTGTGTTGCAATAAAATAAAAAAAAAATCTACAAAATTCAAATATATAAAATTTCA    FFFF:FFFFFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF    NH:i:1  HI:i:1  AS:i:108    nM:i:0  RE:A:I  xf:i:0  li:i:0  BC:Z:ACCAGACAAC QT:Z:FFFFFFFFFF CR:Z:TGGTCTGTTGGGCGTA   CY:Z:FFFFFFFFFFFFFFFF   CB:Z:TGGTCTGTTGGGCGTA-1 UR:Z:GTTACCCTATGT   UY:Z:FFFFFFFFFFFF   UB:Z:GTTACCCTATGT   RG:Z:V1_Adult_Mouse_Brain:0:1:HMKLFDMXX:1
A00984:21:HMKLFDMXX:2:2345:21206:5087   16  1   3010019 255 98M22S  *   0   0   ATAGTGTCCCAGATTTCCTGGCTGTTTCTTGTTAGGATTTTTTTAGATTTAACATTTCTGTCATAGATTAATCTATTTTGCAGATGTAATCCCATGTACTCTGCGTTGATACCACTGCTT    F:FFFFFFFFFFF::FFF:FFFFFFFFFFFFFFFFFFFFFFFF,FFFFFFFFFFFFFFFFFFFFFFFF,FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFF:FFFFFF    NH:i:1  HI:i:1  AS:i:90 nM:i:3  RE:A:I  xf:i:0  ts:i:30 li:i:0  BC:Z:ACCAGACAAC QT:Z:FFFFFFFFFF CR:Z:ACGGTCACCGAGACCCY:Z:FFFFFFFFFFFFF,F:   CB:Z:ACGGTCACCGAGAACA-1 UR:Z:TCGATCTCGTAA   UY:Z:FFFFFFFFFFFF   UB:Z:TCGATCTCGTAA   RG:Z:V1_Adult_Mouse_Brain:0:1:HMKLFDMXX:2
A00984:21:HMKLFDMXX:1:1164:15980:17738  16  1   3013014 255 17M186702N103M  *   0   0   TTTTTTTTTTTTTTTGTTTAAAATGACCACAGTGTACTTTATTTAATGATTTTTGTACTTTGTGTTGCAATAAAATAAAAAAAAAATCTACAAAATTCAAATATATAAAATTTCAAGTTT    FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF    NH:i:1  HI:i:1  AS:i:108    nM:i:0  RE:A:I  xf:i:0  li:i:0  BC:Z:ACCAGACAAC QT:Z:FFF,FFFFFF CR:Z:TCAAGGTTACTACACC   CY:Z:FFFFFFFFFFF:FFFF   CB:Z:TCAAGGTTACTACACC-1 UR:Z:CCGGGCAGTTAT   UY:Z:FFFFFFFFFFFF   UB:Z:CCGGGCAGTTAT   RG:Z:V1_Adult_Mouse_Brain:0:1:HMKLFDMXX:1
A00984:21:HMKLFDMXX:1:1451:3477:33912   16  1   3013014 255 17M186702N103M  *   0   0   TTTTTTTTTTTTTTTGTTTAAAATGACCACAGTGTACTTTATTTAATGATTTTTGTACTTTGTGTTGCAATAAAATAAAAAAAAAATCTACAAAATTCAAATATATAAAATTTCAAGTTT    FFFFFFFFFFFFFFFF:FF:FFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFF:FFFFFFFFFFFFFFFFFFFFFFF    NH:i:1  HI:i:1  AS:i:108    nM:i:0  RE:A:I  xf:i:0  li:i:0  BC:Z:ACCAGACAAC QT:Z:FFFFFFFFFF CR:Z:TCAAGGTTACTACACC   CY:Z:FFFFFFFFFFF:F,FF   CB:Z:TCAAGGTTACTACACC-1 UR:Z:CCGGGCAGTTAT   UY:Z:FFFFFFFFFFFF   UB:Z:CCGGGCAGTTAT   RG:Z:V1_Adult_Mouse_Brain:0:1:HMKLFDMXX:1

貌似沒(méi)看到官網(wǎng)講的AGAATGGTCTGCAT-1這種spot barcodeCB標(biāo)簽包含帶短劃線分隔符的后綴船逮，后跟數(shù)字的結(jié)構(gòu)啊。粤铭。傻唾。

進(jìn)行R的下游分析

由于現(xiàn)在還沒(méi)有現(xiàn)成的用于10X Visium空間轉(zhuǎn)錄組的R包，只好參考官網(wǎng)的R代碼

官網(wǎng)地址：https://support.10xgenomics.com/spatial-gene-expression/software/pipelines/latest/rkit

通過(guò)Loupe Browser 4.0.0進(jìn)行下游分析

• 打開Xftp，打開 cloupe.cloupe
  
  image.png

• 查看tSNE

  
  
  image.png

• UMAP

  
  
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• Feacture Plot

  
  
  image.png
  
  

  Feature Plot視圖可讓您可視化每個(gè)點(diǎn)的一個(gè)或兩個(gè)基因的表達(dá)水平冠骄。此視圖使得根據(jù)一個(gè)或兩個(gè)基因的表達(dá)水平對(duì)點(diǎn)組進(jìn)行閾值化變得容易。特征（在這種情況下為基因）可以在Y軸頂部或X軸右側(cè)的文本框中輸入加袋。這些選擇器還包含一個(gè)控件凛辣，用于在線性和對(duì)數(shù)刻度之間切換軸的刻度。

  
  
  image.png