clustergram function  (MathWorks Inc)

Journal: Frontiers in Microbiology

Article Title: Identification of microbial metabolic functional guilds from large genomic datasets

doi: 10.3389/fmicb.2023.1197329

Figure Lengend Snippet: Resulting clustergram plot on the presence/absence pathway data for our composite dataset (red = present, black = absent) using a cut height of 0.9 with rows (genomes) and columns (functions) clustered based on Jaccard distance.

Article Snippet: We also analyzed our composite dataset using an agglomerative hierarchical clustering method using the clustergram function from the Statistics and Machine Learning toolbox v12.1 from MATLAB R2021a (The Math Works, ).

Techniques:

Journal: Frontiers in Microbiology

Article Title: Identification of microbial metabolic functional guilds from large genomic datasets

doi: 10.3389/fmicb.2023.1197329

Figure Lengend Snippet: The distribution of guild sizes (number of functions) and the number of mapback genomes for guilds generated with clustergram at cut heights of 0.9 (blue square) and 1 (purple plus sign) as well as for AB. AB approach 1 (red circle) defined guilds using a fixed size of 5 functions while AB approach 2 (green triangle) defined guilds using a minimum mapback genome cut-off of 100. Points were jittered using the built-in position_jitter function in the ggplot2 package v3.4.2 with h = 0.1, w = 0.35 using the random seed 123.

Article Snippet: We also analyzed our composite dataset using an agglomerative hierarchical clustering method using the clustergram function from the Statistics and Machine Learning toolbox v12.1 from MATLAB R2021a (The Math Works, ).

Techniques: Generated

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Molecular codes for cell type specification in Brn3 retinal ganglion cells

doi: 10.1073/pnas.1618551114

Figure Lengend Snippet: Sample characterization and validation. (A) Log-scale scatter plots comparing FPKM levels. (Left) Comparison of two samples (S1 vs. S2) derived from P3 Brn3aAP/WT RGC; R = 0.9915. (Center) Means of two P3 Brn3aAP/KO RGC samples (KO) vs. means of two P3 Brn3aAP/WT RGC samples (WT); R = 0.9922. (Right) Comparison of a P3 Brn3aAP/WT retinal supernatant (retina) with the mean of two P3 Brn3aAP/WT RGC samples (RGC); R = 0.7761. Red diagonals separate the twofold comparison lines, and the red corners enclose genes with less than two FPKM for both samples in the plot. (B) Clustergram across 18,185 transcripts that were expressed at greater than or equal to one FPKM in at least one of the samples. Clustering was performed on standardized sample values, first along the sample dimension (columns) and then along the transcript dimension (rows) (Materials and Methods). Branches are color-coded and labeled 1–7 as follows: branch 1, Brn3aAP P3 RGCs; branch 2, E15 retina and Brn3bAP RGCs; branch 3, P3 retinas; branch 4, Brn3bAP P3 RGCs; branch 5, SC and PTA; branch 6, whole-brain controls; branch 7, LGN. For each sample (along the bottom), numbers indicate biological replicates. Color scale represents units in SDs of the distribution across all observations for each given row (gene). [Dataset S2 shows cross-correlation matrix of all samples, and Fig. S1 shows additional scatter plots and principal component analysis (PCA).] (C and D) Visualization of mapped reads. (C) Reads from (Upper) Brn3aAP/KO and (Lower) Brn3aAP/WT P3 RGCs mapping to the Brn3a locus. (D) Reads from either (Upper) Brn3bAP/KO or (Lower) Brn3bAP/WT P3 RGCs mapping to the Brn3b locus. The x axis is in kilobases (notches every 0.5 kb). The y axis is scaled to the highest read stack (indicated in the bottom right corner). The AP cDNA inserted in the recombined alleles is indicated. Gray bars flanked by black notches represent reads. Thin blue lines represent spliced reads reaching across two exons. Exons (rectangles) and introns (lines) are shown for Brn3a (Pou4f1, three exons) and Brn3b (Pou4f2, two exons) in C, Lower and D, Lower. Coding regions within exons are blue. (E) Expression levels (FPKM) for Brn3a and Brn3b genes. Mouse WT P3 brain samples are (from top to bottom) whole brain (white; median of two samples), PTA (black; one sample derived from three mice), and SC and LGN (dotted and gray bars, respectively; each medians of three samples). For retina and RGCs, samples are (from top to bottom) P3 Brn3bAP/WT (dark red), Brn3bAP/KO (light red), Brn3aAP/WT (dark green), Brn3aAP/KO (light green), E15 Brn3bAP/WT (dark blue), and Brn3bAP/KO (light blue). Retina values represent individual retinal samples, and RGC samples represent medians of two samples. (F) Expression (FPKM) of the knocked in AP cDNA color-coded as in E. (G) Heat map for known general and subtype-specific RGC markers. Expression levels are normalized to the maximum level for each gene and displayed on a 64-level scale (red is high).

Article Snippet: Hierarchical clustering shown in and and – was performed using the Matlab Bioinformatics Toolbox clustergram function.

Techniques: Biomarker Discovery, Comparison, Derivative Assay, Labeling, Expressing

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Molecular codes for cell type specification in Brn3 retinal ganglion cells

doi: 10.1073/pnas.1618551114

Figure Lengend Snippet: TF repertoire of Brn3aAP and Brn3bAP RGCs and retinorecipient brain areas. (A–D) Venn diagrams representing TF genes enriched in Brn3AP RGCs. Numbers represent transcripts identified using the Twofold and DESeq (parentheses) criteria. Note that the DESeq criteria find a much smaller number of significantly differentially expressed TFs. (E) Venn diagram representing global TF expression in Brn3AP RGCs. Of a list of 2,437 TFs and transcriptional activity molecules (45, 46), 1,647 are expressed at more than one FPKM in Brn3AP RGCs. TF genes enriched in Brn3aAP and/or Brn3bAP RGCs at E15 and/or P3 number 322 by the Twofold criteria (more than two FPKM in RGCs and more than twofold in RGCs compared with retina) and 153 by the DESeq protocol. TF genes differentially expressed in RGCs in a Brn3a- and/or Brn3b-dependent manner are either 95 (Twofold criteria) or 43 (DESeq). (F) Venn diagram with TFs selectively expressed in LGN, SC, and PTA. Numbers represent transcripts identified using the Twofold criteria and DESeq (parentheses). (G) Examples for TFs expressed either selectively or jointly in three retinorecipient nuclei. Expression levels normalized to the maximum level of each gene and displayed on a 64-level heat map (red is high). (H) Clustergram of TFs believed to be important for RGC development. Sample names are labeled at the top, and hierarchical cluster major branches are color-coded and labeled a–c. TFs (highest expressed transcript) are annotated to the right, and hierarchical tree branches of interest are color-coded and labeled 1–5. Color scale bar is at the bottom, and units are in SDs (clustergram details are in Materials and Methods and Fig. 2B). Clustergrams of the complete sets of TFs regulated by Brn3s, enriched in RGCs, or selective for particular retinorecipient areas are provided in Figs. S2 and ​andS3.S3. Dataset S6 lists all transcripts in the Venn diagrams.

Article Snippet: Hierarchical clustering shown in and and – was performed using the Matlab Bioinformatics Toolbox clustergram function.

Techniques: Expressing, Activity Assay, Labeling

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Molecular codes for cell type specification in Brn3 retinal ganglion cells

doi: 10.1073/pnas.1618551114

Figure Lengend Snippet: Hierarchical clustering of Brn3-dependent and RGC-Enriched TFs. (A) The clustergram includes 107 transcripts referred to in Fig. 5 B and D. (B) The clustergram includes 388 transcripts referred to in Fig. 5 A and C. Clustering was performed first along the sample dimension and then along the individual gene dimension using the Matlab clustergram function with Euclidean distances and Ward's linkage method. Sample names are labeled at the bottom, and hierarchical cluster major branches are color-coded and labeled a–c. Hierarchical tree branches of interest are color-coded and labeled 1–4, and the transcript identifications are provided in Dataset S6. Color scale bar is at the bottom, and units are in SDs.

Article Snippet: Hierarchical clustering shown in and and – was performed using the Matlab Bioinformatics Toolbox clustergram function.

Techniques: Labeling

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Molecular codes for cell type specification in Brn3 retinal ganglion cells

doi: 10.1073/pnas.1618551114

Figure Lengend Snippet: Hierarchical clustering of TFs enriched in retinorecipient areas. The clustergram includes 206 transcripts referred to in Fig. 5F. Clustering and scale bars are the same as in Fig. S2. Sample names are labeled at the bottom. Transcript identifications are provided in Dataset S6. Hierarchical tree branches of interest are labeled 1–4.

Article Snippet: Hierarchical clustering shown in and and – was performed using the Matlab Bioinformatics Toolbox clustergram function.

Techniques: Labeling

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Molecular codes for cell type specification in Brn3 retinal ganglion cells

doi: 10.1073/pnas.1618551114

Figure Lengend Snippet: CSM repertoire of Brn3aAP and Brn3bAP RGCs and retinorecipient brain areas. (A–D) Venn diagrams representing adhesion molecule genes from several molecular families believed to be important in neurite formation that were enriched in Brn3AP RGCs. Expression criteria and comparison sets are identical to those in Fig. 5 A–D. The survey includes 822 genes, and the extended analysis is provided in Dataset S7. (E) Venn diagram for adhesion molecules enriched or selective for retinorecipient areas. Expression criteria and comparison are the same as in Fig. 5F (Dataset S7). For A–E, numbers represent transcripts identified using the Twofold and DESeq (parentheses) criteria. (F) Clustergram of a subset of adhesion molecules believed to be important for RGC development. Clustering algorithm and annotations are same as in Fig. 4. Sample names are labeled along the top, and hierarchical cluster major branches are color-coded and labeled a–d. Genes (highest expressed transcript) are annotated on the right, and hierarchical tree branches of interest are color-coded and labeled 1–4. The color scale bar is at the bottom, and units are in SDs. Clustergrams covering the complete sets of differentially regulated or expressed adhesion molecules and guidance receptors are provided in Dataset S7 and Figs. S4 and ​andS5S5.

Article Snippet: Hierarchical clustering shown in and and – was performed using the Matlab Bioinformatics Toolbox clustergram function.

Techniques: Expressing, Comparison, Labeling

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Molecular codes for cell type specification in Brn3 retinal ganglion cells

doi: 10.1073/pnas.1618551114

Figure Lengend Snippet: Hierarchical clustering of Brn3-dependent or RGC-enriched CSMs and guidance cues. (A) The clustergram includes 93 transcripts referred to in Fig. 6 B and D. These transcripts have exhibited more than twofold differentials between either Brn3aAP/WT vs. Brn3aAP/KO or Brn3bAP/WT vs. Brn3bAP/KO RGCs. (B) The clustergram includes 237 transcripts referred to in Fig. 6 A and C. These transcripts have exhibited more than twofold differentials between either Brn3aAP/WT or Brn3bAP/WT RGCs and corresponding retina supernatants. Clustering was performed as above. Sample names are labeled at the bottom, and hierarchical cluster major branches are color-coded and labeled a–d. Hierarchical tree branches of interest are color-coded and labeled 1–4, and the transcript identifications are provided in Dataset S7. Note that, for each branch, the transcripts are annotated in ascending order. Color scale bar is at the bottom, and units are in SDs.

Article Snippet: Hierarchical clustering shown in and and – was performed using the Matlab Bioinformatics Toolbox clustergram function.

Techniques: Labeling

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Molecular codes for cell type specification in Brn3 retinal ganglion cells

doi: 10.1073/pnas.1618551114

Figure Lengend Snippet: Hierarchical clustering of CSMs and guidance cues enriched in retinorecipient areas. The clustergram includes 206 transcripts referred to in Fig. 6E. These transcripts have exhibited more than twofold differentials between the indicated retinorecipient areas and the whole-brain homogenate. Clustering and scale bars are the same as in Fig. S2. Sample names are labeled at the bottom, and hierarchical cluster major branches are color-coded and labeled a–e. Transcript identifications are indicated to the right, and FPKM values for all samples can be recovered from Dataset S3 by searching with the transcript identifier (e.g., Palld-004). Hierarchical tree branches of interest are labeled 1–7.

Article Snippet: Hierarchical clustering shown in and and – was performed using the Matlab Bioinformatics Toolbox clustergram function.

Techniques: Labeling