search

broadinstitute / infercnv

Inferring CNV from Single-Cell RNA-Seq
Other
565 stars 166 forks source link

how to do the inferCNV in integrated data and Distribution of Expression are all blue? #287

Closed Yinglei1 closed 2 years ago

Yinglei1 commented 3 years ago

Hi, there,

I am a new for integration and inferCNV. I have four samples(two from normal people and two from patients with chr20 deletion) . I integrated these four samples together using finding FindIntegrationAnchors, now I want to check if there is any inferCNVs between normal people and patients in one cluster(one cell type). Note: this cell type occurred in both normal and patients regardless of the chromosome disability. image

This are the codes that I used for integration: anchors <- FindIntegrationAnchors(object.list = object) integration <- IntegrateData(anchorset = anchors)

thisare the codes that I used for inferCNV:

  1. extracting the matrix with gene expression: exprMatrix <- as.matrix(GetAssayData(object1[["RNA"]], slot='counts')) there are the gene expression data and cells annotation.

Picture1 image

  1. running inferCNV infercnv_obj = CreateInfercnvObject(delim = '\t', raw_counts_matrix = 'exprMatrix.txt', annotations_file = 'cellAnnota.txt', gene_order_file = gene_pos.txt', ref_group_names = c("Control1","Control2"))

infercnv_obj1 = infercnv::run(infercnv_obj, cutoff=0.1, out_dir=" inferCNV/Astroglia/inferCNV1-3", cluster_by_groups=TRUE, denoise=TRUE, HMM=TRUE)

here are the outputs: STEP 1: incoming data

INFO [2021-01-11 10:09:21] 

STEP 02: Removing lowly expressed genes

INFO [2021-01-11 10:09:21] ::above_min_mean_expr_cutoff:Start INFO [2021-01-11 10:09:21] Removing 10609 genes from matrix as below mean expr threshold: 0.1 INFO [2021-01-11 10:09:21] validating infercnv_obj INFO [2021-01-11 10:09:21] There are 5394 genes and 1502 cells remaining in the expr matrix. INFO [2021-01-11 10:09:22] no genes removed due to min cells/gene filter INFO [2021-01-11 10:09:24] 

STEP 03: normalization by sequencing depth

INFO [2021-01-11 10:09:24] normalizing counts matrix by depth INFO [2021-01-11 10:09:24] Computed total sum normalization factor as median libsize: 3048.500000 INFO [2021-01-11 10:09:24] Adding h-spike INFO [2021-01-11 10:09:24] -hspike modeling of Control1 INFO [2021-01-11 10:10:16] -hspike modeling of Control2 INFO [2021-01-11 10:11:03] validating infercnv_obj INFO [2021-01-11 10:11:03] normalizing counts matrix by depth INFO [2021-01-11 10:11:03] Using specified normalization factor: 3048.500000 INFO [2021-01-11 10:11:06] 

STEP 04: log transformation of data

INFO [2021-01-11 10:11:06] transforming log2xplus1() INFO [2021-01-11 10:11:06] -mirroring for hspike INFO [2021-01-11 10:11:06] transforming log2xplus1() INFO [2021-01-11 10:11:10] 

STEP 08: removing average of reference data (before smoothing)

INFO [2021-01-11 10:11:10] ::subtract_ref_expr_from_obs:Start inv_log=FALSE, use_bounds=TRUE INFO [2021-01-11 10:11:10] subtracting mean(normal) per gene per cell across all data INFO [2021-01-11 10:11:11] -subtracting expr per gene, use_bounds=TRUE INFO [2021-01-11 10:11:12] -mirroring for hspike INFO [2021-01-11 10:11:12] ::subtract_ref_expr_from_obs:Start inv_log=FALSE, use_bounds=TRUE INFO [2021-01-11 10:11:12] subtracting mean(normal) per gene per cell across all data INFO [2021-01-11 10:11:13] -subtracting expr per gene, use_bounds=TRUE INFO [2021-01-11 10:11:19] 

STEP 09: apply max centered expression threshold: 3

INFO [2021-01-11 10:11:19] ::process_data:setting max centered expr, threshold set to: +/-: 3 INFO [2021-01-11 10:11:19] -mirroring for hspike INFO [2021-01-11 10:11:19] ::process_data:setting max centered expr, threshold set to: +/-: 3 INFO [2021-01-11 10:11:24] 

STEP 10: Smoothing data per cell by chromosome

INFO [2021-01-11 10:11:24] smooth_by_chromosome: chr: chr1 INFO [2021-01-11 10:11:25] smooth_by_chromosome: chr: chr2 INFO [2021-01-11 10:11:27] smooth_by_chromosome: chr: chr3 INFO [2021-01-11 10:11:28] smooth_by_chromosome: chr: chr4 INFO [2021-01-11 10:11:29] smooth_by_chromosome: chr: chr5 INFO [2021-01-11 10:11:30] smooth_by_chromosome: chr: chr6 INFO [2021-01-11 10:11:32] smooth_by_chromosome: chr: chr7 INFO [2021-01-11 10:11:33] smooth_by_chromosome: chr: chr8 INFO [2021-01-11 10:11:34] smooth_by_chromosome: chr: chr9 INFO [2021-01-11 10:11:35] smooth_by_chromosome: chr: chr10 INFO [2021-01-11 10:11:36] smooth_by_chromosome: chr: chr11 INFO [2021-01-11 10:11:38] smooth_by_chromosome: chr: chr12 INFO [2021-01-11 10:11:39] smooth_by_chromosome: chr: chr13 INFO [2021-01-11 10:11:40] smooth_by_chromosome: chr: chr14 INFO [2021-01-11 10:11:42] smooth_by_chromosome: chr: chr15 INFO [2021-01-11 10:11:43] smooth_by_chromosome: chr: chr16 INFO [2021-01-11 10:11:44] smooth_by_chromosome: chr: chr17 INFO [2021-01-11 10:11:46] smooth_by_chromosome: chr: chr18 INFO [2021-01-11 10:11:47] smooth_by_chromosome: chr: chr19 INFO [2021-01-11 10:11:48] smooth_by_chromosome: chr: chr20 INFO [2021-01-11 10:11:49] smooth_by_chromosome: chr: chr21 INFO [2021-01-11 10:11:50] smooth_by_chromosome: chr: chr22 INFO [2021-01-11 10:11:51] -mirroring for hspike INFO [2021-01-11 10:11:51] smooth_by_chromosome: chr: chrA INFO [2021-01-11 10:11:51] smooth_by_chromosome: chr: chr_0 INFO [2021-01-11 10:11:52] smooth_by_chromosome: chr: chr_B INFO [2021-01-11 10:11:53] smooth_by_chromosome: chr: chr_0pt5 INFO [2021-01-11 10:11:53] smooth_by_chromosome: chr: chr_C INFO [2021-01-11 10:11:53] smooth_by_chromosome: chr: chr_1pt5 INFO [2021-01-11 10:11:54] smooth_by_chromosome: chr: chr_D INFO [2021-01-11 10:11:54] smooth_by_chromosome: chr: chr_2pt0 INFO [2021-01-11 10:11:55] smooth_by_chromosome: chr: chr_E INFO [2021-01-11 10:11:55] smooth_by_chromosome: chr: chr_3pt0 INFO [2021-01-11 10:11:55] smooth_by_chromosome: chr: chr_F INFO [2021-01-11 10:12:01] 

STEP 11: re-centering data across chromosome after smoothing

INFO [2021-01-11 10:12:01] ::center_smooth across chromosomes per cell INFO [2021-01-11 10:12:02] -mirroring for hspike INFO [2021-01-11 10:12:02] ::center_smooth across chromosomes per cell INFO [2021-01-11 10:12:08] 

STEP 12: removing average of reference data (after smoothing)

INFO [2021-01-11 10:12:08] ::subtract_ref_expr_from_obs:Start inv_log=FALSE, use_bounds=TRUE INFO [2021-01-11 10:12:08] subtracting mean(normal) per gene per cell across all data INFO [2021-01-11 10:12:10] -subtracting expr per gene, use_bounds=TRUE INFO [2021-01-11 10:12:11] -mirroring for hspike INFO [2021-01-11 10:12:11] ::subtract_ref_expr_from_obs:Start inv_log=FALSE, use_bounds=TRUE INFO [2021-01-11 10:12:11] subtracting mean(normal) per gene per cell across all data INFO [2021-01-11 10:12:12] -subtracting expr per gene, use_bounds=TRUE INFO [2021-01-11 10:12:18] 

STEP 14: invert log2(FC) to FC

INFO [2021-01-11 10:12:18] invert_log2(), computing 2^x INFO [2021-01-11 10:12:19] -mirroring for hspike INFO [2021-01-11 10:12:19] invert_log2(), computing 2^x INFO [2021-01-11 10:12:26] 

STEP 15: Clustering samples (not defining tumor subclusters)

INFO [2021-01-11 10:12:26] define_signif_tumor_subclusters(p_val=0.1 INFO [2021-01-11 10:12:26] define_signif_tumor_subclusters(), tumor: Patient1 INFO [2021-01-11 10:12:32] cut tree into: 1 groups INFO [2021-01-11 10:12:32] -processing Patient1,Patient1_s1 INFO [2021-01-11 10:12:32] define_signif_tumor_subclusters(), tumor: Patient2 INFO [2021-01-11 10:12:45] cut tree into: 1 groups INFO [2021-01-11 10:12:45] -processing Patient2,Patient2_s1 INFO [2021-01-11 10:12:45] define_signif_tumor_subclusters(), tumor: Control1 INFO [2021-01-11 10:12:48] cut tree into: 1 groups INFO [2021-01-11 10:12:48] -processing Control1,Control1_s1 INFO [2021-01-11 10:12:48] define_signif_tumor_subclusters(), tumor: Control2 INFO [2021-01-11 10:12:48] cut tree into: 1 groups INFO [2021-01-11 10:12:48] -processing Control2,Control2_s1 INFO [2021-01-11 10:12:48] -mirroring for hspike INFO [2021-01-11 10:12:48] define_signif_tumor_subclusters(p_val=0.1 INFO [2021-01-11 10:12:48] define_signif_tumor_subclusters(), tumor: spike_tumor_cell_Control1 INFO [2021-01-11 10:12:49] cut tree into: 1 groups INFO [2021-01-11 10:12:49] -processing spike_tumor_cell_Control1,spike_tumor_cell_Control1_s1 INFO [2021-01-11 10:12:49] define_signif_tumor_subclusters(), tumor: spike_tumor_cell_Control2 INFO [2021-01-11 10:12:49] cut tree into: 1 groups INFO [2021-01-11 10:12:49] -processing spike_tumor_cell_Control2,spike_tumor_cell_Control2_s1 INFO [2021-01-11 10:12:49] define_signif_tumor_subclusters(), tumor: simnorm_cell_Control1 INFO [2021-01-11 10:12:49] cut tree into: 1 groups INFO [2021-01-11 10:12:49] -processing simnorm_cell_Control1,simnorm_cell_Control1_s1 INFO [2021-01-11 10:12:49] define_signif_tumor_subclusters(), tumor: simnorm_cell_Control2 INFO [2021-01-11 10:12:49] cut tree into: 1 groups INFO [2021-01-11 10:12:49] -processing simnorm_cell_Control2,simnorm_cell_Control2_s1 INFO [2021-01-11 10:13:04] ::plot_cnv:Start INFO [2021-01-11 10:13:04] ::plot_cnv:Current data dimensions (r,c)=5394,1502 Total=8109332.60491251 Min=0.749570260465397 Max=1.46781862387323. INFO [2021-01-11 10:13:04] ::plot_cnv:Depending on the size of the matrix this may take a moment. INFO [2021-01-11 10:13:27] plot_cnv(): auto thresholding at: (0.890175 , 1.111687) INFO [2021-01-11 10:13:27] plot_cnv_observation:Start INFO [2021-01-11 10:13:27] Observation data size: Cells= 1079 Genes= 5394 INFO [2021-01-11 10:13:27] plot_cnv_observation:Writing observation groupings/color. INFO [2021-01-11 10:13:27] plot_cnv_observation:Done writing observation groupings/color. INFO [2021-01-11 10:13:27] plot_cnv_observation:Writing observation heatmap thresholds. INFO [2021-01-11 10:13:27] plot_cnv_observation:Done writing observation heatmap thresholds. INFO [2021-01-11 10:13:28] Colors for breaks: #00008B,#24249B,#4848AB,#6D6DBC,#9191CC,#B6B6DD,#DADAEE,#FFFFFF,#EEDADA,#DDB6B6,#CC9191,#BC6D6D,#AB4848,#9B2424,#8B0000 INFO [2021-01-11 10:13:28] Quantiles of plotted data range: 0.890174979398446,0.975560729029878,1,1.02363926892263,1.11168747489251 INFO [2021-01-11 10:13:29] plot_cnv_observations:Writing observation data to inferCNV/Astroglia/inferCNV1-3/infercnv.preliminary.observations.txt INFO [2021-01-11 10:13:45] plot_cnv_references:Start INFO [2021-01-11 10:13:45] Reference data size: Cells= 423 Genes= 5394 INFO [2021-01-11 10:13:49] plot_cnv_references:Number reference groups= 2 INFO [2021-01-11 10:13:49] plot_cnv_references:Plotting heatmap. INFO [2021-01-11 10:13:49] Colors for breaks: #00008B,#24249B,#4848AB,#6D6DBC,#9191CC,#B6B6DD,#DADAEE,#FFFFFF,#EEDADA,#DDB6B6,#CC9191,#BC6D6D,#AB4848,#9B2424,#8B0000 INFO [2021-01-11 10:13:49] Quantiles of plotted data range: 0.890174979398446,0.976493266316419,1,1.02260645130909,1.11168747489251 INFO [2021-01-11 10:13:50] plot_cnv_references:Writing reference data to inferCNV/Astroglia/inferCNV1-3/infercnv.preliminary.references.txt INFO [2021-01-11 10:13:56] 

STEP 17: HMM-based CNV prediction

INFO [2021-01-11 10:13:56] predict_CNV_via_HMM_on_whole_tumor_samples INFO [2021-01-11 10:13:59] -done predicting CNV based on initial tumor subclusters INFO [2021-01-11 10:14:02] get_predicted_CNV_regions(subcluster) INFO [2021-01-11 10:14:02] -processing cell_group_name: Patient1.Patient1_s1, size: 435 INFO [2021-01-11 10:14:08] -processing cell_group_name: Patient2.Patient2_s1, size: 644 INFO [2021-01-11 10:14:15] -processing cell_group_name: Control1.Control1_s1, size: 341 INFO [2021-01-11 10:14:21] -processing cell_group_name: Control2.Control2_s1, size: 82 INFO [2021-01-11 10:14:25] -writing cell clusters file: inferCNV/Astroglia/inferCNV1-3/17_HMM_predHMMi6.hmm_mode-samples.cell_groupings INFO [2021-01-11 10:14:25] -writing cnv regions file: inferCNV/Astroglia/inferCNV1-3/17_HMM_predHMMi6.hmm_mode-samples.pred_cnv_regions.dat INFO [2021-01-11 10:14:25] -writing per-gene cnv report: inferCNV/Astroglia/inferCNV1-3/17_HMM_predHMMi6.hmm_mode-samples.pred_cnv_genes.dat INFO [2021-01-11 10:14:25] -writing gene ordering info: inferCNV/Astroglia/inferCNV1-3/17_HMM_predHMMi6.hmm_mode-samples.genes_used.dat INFO [2021-01-11 10:14:26] ::plot_cnv:Start INFO [2021-01-11 10:14:26] ::plot_cnv:Current data dimensions (r,c)=5394,1502 Total=24305364 Min=3 Max=3. INFO [2021-01-11 10:14:26] ::plot_cnv:Depending on the size of the matrix this may take a moment. INFO [2021-01-11 10:14:37] plot_cnv_observation:Start INFO [2021-01-11 10:14:37] Observation data size: Cells= 1079 Genes= 5394 INFO [2021-01-11 10:14:37] plot_cnv_observation:Writing observation groupings/color. INFO [2021-01-11 10:14:37] plot_cnv_observation:Done writing observation groupings/color. INFO [2021-01-11 10:14:37] plot_cnv_observation:Writing observation heatmap thresholds. INFO [2021-01-11 10:14:37] plot_cnv_observation:Done writing observation heatmap thresholds. INFO [2021-01-11 10:14:38] Colors for breaks: #00008B,#24249B,#4848AB,#6D6DBC,#9191CC,#B6B6DD,#DADAEE,#FFFFFF,#EEDADA,#DDB6B6,#CC9191,#BC6D6D,#AB4848,#9B2424,#8B0000 INFO [2021-01-11 10:14:38] Quantiles of plotted data range: 3,3,3,3,3 INFO [2021-01-11 10:14:38] plot_cnv_observations:Writing observation data to inferCNV/Astroglia/inferCNV1-3/infercnv.17_HMM_predHMMi6.hmm_mode-samples.observations.txt INFO [2021-01-11 10:14:46] plot_cnv_references:Start INFO [2021-01-11 10:14:46] Reference data size: Cells= 423 Genes= 5394 INFO [2021-01-11 10:14:49] plot_cnv_references:Number reference groups= 2 INFO [2021-01-11 10:14:49] plot_cnv_references:Plotting heatmap. INFO [2021-01-11 10:14:49] Colors for breaks: #00008B,#24249B,#4848AB,#6D6DBC,#9191CC,#B6B6DD,#DADAEE,#FFFFFF,#EEDADA,#DDB6B6,#CC9191,#BC6D6D,#AB4848,#9B2424,#8B0000 INFO [2021-01-11 10:14:49] Quantiles of plotted data range: 3,3,3,3,3 INFO [2021-01-11 10:14:49] plot_cnv_references:Writing reference data to inferCNV/Astroglia/inferCNV1-3/infercnv.17_HMM_predHMMi6.hmm_mode-samples.references.txt INFO [2021-01-11 10:14:53] 

STEP 19: Converting HMM-based CNV states to repr expr vals

INFO [2021-01-11 10:14:56] ::plot_cnv:Start INFO [2021-01-11 10:14:56] ::plot_cnv:Current data dimensions (r,c)=5394,1502 Total=8101788 Min=1 Max=1. INFO [2021-01-11 10:14:57] ::plot_cnv:Depending on the size of the matrix this may take a moment. INFO [2021-01-11 10:15:08] plot_cnv_observation:Start INFO [2021-01-11 10:15:08] Observation data size: Cells= 1079 Genes= 5394 INFO [2021-01-11 10:15:08] plot_cnv_observation:Writing observation groupings/color. INFO [2021-01-11 10:15:08] plot_cnv_observation:Done writing observation groupings/color. INFO [2021-01-11 10:15:08] plot_cnv_observation:Writing observation heatmap thresholds. INFO [2021-01-11 10:15:08] plot_cnv_observation:Done writing observation heatmap thresholds. INFO [2021-01-11 10:15:09] Colors for breaks: #00008B,#24249B,#4848AB,#6D6DBC,#9191CC,#B6B6DD,#DADAEE,#FFFFFF,#EEDADA,#DDB6B6,#CC9191,#BC6D6D,#AB4848,#9B2424,#8B0000 INFO [2021-01-11 10:15:09] Quantiles of plotted data range: 1,1,1,1,1 INFO [2021-01-11 10:15:09] plot_cnv_observations:Writing observation data to inferCNV/Astroglia/inferCNV1-3/infercnv.19_HMM_predHMMi6.hmm_mode-samples.Pnorm_0.5.repr_intensities.observations.txt INFO [2021-01-11 10:15:17] plot_cnv_references:Start INFO [2021-01-11 10:15:17] Reference data size: Cells= 423 Genes= 5394 INFO [2021-01-11 10:15:20] plot_cnv_references:Number reference groups= 2 INFO [2021-01-11 10:15:20] plot_cnv_references:Plotting heatmap. INFO [2021-01-11 10:15:20] Colors for breaks: #00008B,#24249B,#4848AB,#6D6DBC,#9191CC,#B6B6DD,#DADAEE,#FFFFFF,#EEDADA,#DDB6B6,#CC9191,#BC6D6D,#AB4848,#9B2424,#8B0000 INFO [2021-01-11 10:15:20] Quantiles of plotted data range: 1,1,1,1,1 INFO [2021-01-11 10:15:20] plot_cnv_references:Writing reference data to inferCNV/Astroglia/inferCNV1-3/infercnv.19_HMM_predHMMi6.hmm_mode-samples.Pnorm_0.5.repr_intensities.references.txt INFO [2021-01-11 10:15:24] 

STEP 21: Denoising

INFO [2021-01-11 10:15:24] ::process_data:Remove noise, noise threshold defined via ref mean sd_amplifier: 1.5 INFO [2021-01-11 10:15:24] denoising using mean(normal) +- sd_amplifier * sd(normal) per gene per cell across all data INFO [2021-01-11 10:15:24] :: clear_noise_via_ref_quantiles : removing noise between bounds: 0.942944684299806 - 1.05879392213761 INFO [2021-01-11 10:15:27] ::plot_cnv:Start INFO [2021-01-11 10:15:27] ::plot_cnv:Current data dimensions (r,c)=5394,1502 Total=8123186.37967838 Min=0.749570260465397 Max=1.46781862387323. INFO [2021-01-11 10:15:27] ::plot_cnv:Depending on the size of the matrix this may take a moment. INFO [2021-01-11 10:15:46] plot_cnv(): auto thresholding at: (0.893595 , 1.111687) INFO [2021-01-11 10:15:46] plot_cnv_observation:Start INFO [2021-01-11 10:15:46] Observation data size: Cells= 1079 Genes= 5394 INFO [2021-01-11 10:15:46] plot_cnv_observation:Writing observation groupings/color. INFO [2021-01-11 10:15:46] plot_cnv_observation:Done writing observation groupings/color. INFO [2021-01-11 10:15:46] plot_cnv_observation:Writing observation heatmap thresholds. INFO [2021-01-11 10:15:46] plot_cnv_observation:Done writing observation heatmap thresholds. INFO [2021-01-11 10:15:47] Colors for breaks: #00008B,#24249B,#4848AB,#6D6DBC,#9191CC,#B6B6DD,#DADAEE,#FFFFFF,#EEDADA,#DDB6B6,#CC9191,#BC6D6D,#AB4848,#9B2424,#8B0000 INFO [2021-01-11 10:15:47] Quantiles of plotted data range: 0.893594909607933,1.00086930321871,1.00086930321871,1.00086930321871,1.11168747489251 INFO [2021-01-11 10:15:48] plot_cnv_observations:Writing observation data to inferCNV/Astroglia/inferCNV1-3/infercnv.21_denoised.observations.txt INFO [2021-01-11 10:16:01] plot_cnv_references:Start INFO [2021-01-11 10:16:01] Reference data size: Cells= 423 Genes= 5394 INFO [2021-01-11 10:16:04] plot_cnv_references:Number reference groups= 2 INFO [2021-01-11 10:16:04] plot_cnv_references:Plotting heatmap. INFO [2021-01-11 10:16:04] Colors for breaks: #00008B,#24249B,#4848AB,#6D6DBC,#9191CC,#B6B6DD,#DADAEE,#FFFFFF,#EEDADA,#DDB6B6,#CC9191,#BC6D6D,#AB4848,#9B2424,#8B0000 INFO [2021-01-11 10:16:04] Quantiles of plotted data range: 0.893594909607933,1.00086930321871,1.00086930321871,1.00086930321871,1.11168747489251 INFO [2021-01-11 10:16:04] plot_cnv_references:Writing reference data to inferCNV/Astroglia/inferCNV1-3/infercnv.21_denoised.references.txt INFO [2021-01-11 10:16:13]

Making the final infercnv heatmap

INFO [2021-01-11 10:16:13] ::plot_cnv:Start INFO [2021-01-11 10:16:13] ::plot_cnv:Current data dimensions (r,c)=5394,1502 Total=8123186.37967838 Min=0.749570260465397 Max=1.46781862387323. INFO [2021-01-11 10:16:13] ::plot_cnv:Depending on the size of the matrix this may take a moment. INFO [2021-01-11 10:16:32] plot_cnv(): auto thresholding at: (0.888313 , 1.111687) INFO [2021-01-11 10:16:32] plot_cnv_observation:Start INFO [2021-01-11 10:16:33] Observation data size: Cells= 1079 Genes= 5394 INFO [2021-01-11 10:16:33] plot_cnv_observation:Writing observation groupings/color. INFO [2021-01-11 10:16:33] plot_cnv_observation:Done writing observation groupings/color. INFO [2021-01-11 10:16:33] plot_cnv_observation:Writing observation heatmap thresholds. INFO [2021-01-11 10:16:33] plot_cnv_observation:Done writing observation heatmap thresholds. INFO [2021-01-11 10:16:34] Colors for breaks: #00008B,#24249B,#4848AB,#6D6DBC,#9191CC,#B6B6DD,#DADAEE,#FFFFFF,#EEDADA,#DDB6B6,#CC9191,#BC6D6D,#AB4848,#9B2424,#8B0000 INFO [2021-01-11 10:16:34] Quantiles of plotted data range: 0.888312525107489,1.00086930321871,1.00086930321871,1.00086930321871,1.11168747489251 INFO [2021-01-11 10:16:34] plot_cnv_observations:Writing observation data to inferCNV/Astroglia/inferCNV1-3/infercnv.observations.txt INFO [2021-01-11 10:16:48] plot_cnv_references:Start INFO [2021-01-11 10:16:48] Reference data size: Cells= 423 Genes= 5394 INFO [2021-01-11 10:16:51] plot_cnv_references:Number reference groups= 2 INFO [2021-01-11 10:16:51] plot_cnv_references:Plotting heatmap. INFO [2021-01-11 10:16:51] Colors for breaks: #00008B,#24249B,#4848AB,#6D6DBC,#9191CC,#B6B6DD,#DADAEE,#FFFFFF,#EEDADA,#DDB6B6,#CC9191,#BC6D6D,#AB4848,#9B2424,#8B0000 INFO [2021-01-11 10:16:51] Quantiles of plotted data range: 0.888312525107489,1.00086930321871,1.00086930321871,1.00086930321871,1.11168747489251 INFO [2021-01-11 10:16:51] plot_cnv_references:Writing reference data to inferCNV/Astroglia/inferCNV1-3/infercnv.references.txt

image image image

My question are:

  1. because my data is about integration, the matrix with gene expression i extracted is right?

  2. why the png plot named “infercnv.18_HMM_pred.Bayes_Net.Pnorm_0.5.png” miss(it exists when i can get the right inferCNV results) and there is no file names “BayesNetOutput.HMMi6.hmm_mode-samples”. Besides, the “infercnv.17_HMM_predHMMi6.hmm_mode-samples.png” and “infercnv.19_HMM_predHMMi6.hmm_mode-samples.Pnorm_0.5.repr_intensities.png” are all blue? If it is because there is no any inferCNV between normal and patients, and Distribution of Expression are even?

image image

  1. There are several png plots in out_dir，“ infercnv.17.......”,“ infercnv.18....”,“ infercnv.19.....”, “infercnv”. My question is which one is the final inferCNV results and what do these plots mean?

Thanks in advance!

GeorgescuC commented 3 years ago

Hi @Yinglei1 ,

I think the issue you have is that no CNVs are identified, so the color range on the HMM plots gets shifted. This should have been fixed in version 1.5.1 of infercnv. If you are using an older version, please update your installation and try running things again.

Regards, Christophe.

Yinglei1 commented 3 years ago

Thank you a lot!