Sample information : Acomys_dimidiatus

Estimated number of cells: The total number of barcodes identified as cells.
Median UMI counts per cell: Among barcodes identified as cells, the median number of UMI per cell.
Median genes per cell: The median number of genes per cell.
Mean reads per cell: The mean number of reads per cell.

479 Estimated number of cell

9,913

Median UMI counts per cell

1,245

Median genes per cell

45,460

Mean reads per cell

Beads to cells

(left) Beads to cells plot: In library, different mRNAs from the same cell will carry the same cell barcode and random unique molecular identifiers (UMIs). However, some mRNA from dead cells mixed in reflection system was inevitability. This graph shows the distribution of UMI counts in each barcode. Barcodes can be determined to be cell-associated based on their UMI counts or by their expression profiles. Therefore, the graph contains both cell-associated (Colored Regions) and background-associated barcodes (Gray Regions).
(right) Histogram: Histograms of number of beads per droplet.

Summary

Estimated number of cells: The total number of barcodes identified as cells.
Mean reads per cell: The mean number of reads detected per cell.
Mean UMI counts per cell: The average number of UMI counts per cell. This item refers the average abundance of expression in each cell.
Median UMI counts per cell: The median number of UMI counts per cell.
Total genes detected: The total number of genes detected.
Mean genes per cell: The mean number of genes detected per cell. This item refers the activity of gene expression in each cell.
Median genes per cell: The median number of genes detected per cell.
Sequencing saturation: The fraction of UMI originating from an already-observed UMI.
Fraction reads in cells: The fraction of uniquely-mapped-to-transcriptome reads with cell-associated barcode.
Plot: The distribution of nFeature and nCount in violin.

Sample name

Acomys_dimidiatus

Species

Acomys_dimidiatus

Estimated number of cells

479

Mean reads per cell

45,460

Mean UMI count per cell

10,032

Median UMI counts per cell

9,913

Total genes detected

8,461

Mean genes per cell

1,250

Median genes per cell

1,245

Fraction reads in cells

99.36%

Sequencing saturation

39.44%

Sequencing

Number of reads: Number of raw off-machine reads obtained by this sequencing program.
Reads pass QC: Number of reads after quality control (QC) that can be used for downstream analysis. QC includes filtering low quality reads and invalid barcodes.
Reads with exactly matched barcodes: Number of reads with barcodes that match the barcode whitelist before correction.
Reads with failed barcodes: Number of reads with invalid barcodes that fail to match the barcode whitelist.
Reads filtered on low quality: Number of reads in low quality. The QC will filter the average base quality < Q20 or 2 bases < Q10 in the first 15 bases.
Q30 bases in cell barcode: Fraction of cell barcode bases with Q-score ≥ 30.
Q30 bases in UMI: Fraction of UMI bases with Q-score ≥ 30.
Q30 bases in reads: Fraction of RNA read bases with Q-score ≥ 30.

mRNA

Number of reads

25,891,036

Reads pass QC

96.72%

Reads with exactly matched barcodes

100.0%

Reads with failed barcodes

0.0%

Reads filtered on low quality

0.0%

Q30 bases in cell barcode

87.51%

Q30 bases in UMI

87.66%

Q30 bases in reads

94.00%

Droplet index

Number of reads

218,724,924

Reads pass QC

96.18%

Reads with exactly matched barcodes

90.21%

Reads with failed barcodes

3.26%

Reads filtered on low quality

0.56%

Q30 bases in cell barcode

95.89%

Q30 bases in reads

96.75%

Mapping & Annotation

Reads pass QC: Number of reads after quality control (QC) that can be used for downstream analysis. QC includes filtering low quality reads and invalid barcodes.
Reads mapped to genome: Fraction of reads that mapped to the genome.
Plus strand: The number of reads in plus strand.
Minus strand: The number of reads in minus strand.
Mitochondria ratio: The fraction of reads mapped to mitochondria.
Mapping quality corrected reads: The number of reads that align to a single exonic locus but also align to 1 or more non-exonic loci.
Reads mapped to exonic regionse: Fraction of reads that mapped to an exonic region of genome.
Reads mapped to intronic regions: Fraction of reads that mapped to an intronic region of genome.
Reads mapped antisense to gene: Fraction of reads mapped to transcriptome, but on the opposite strand of their annotated gene. This part of reads will be filtered out cause them are opposite to theoretical direction.
Reads mapped to intergenic regions: Fraction of reads that mapped to intergenic regions of genome.

Reads pass QC

25,041,950

Reads mapped to genome

87.83%

Plus strand

48.85%

Minus strand

51.15%

Mitochondria ratio

0.00%

Mapping quality corrected reads

0.85%

Reads mapped to exonic regions

42.6%

Reads mapped to intronic regions

0.7%

Reads mapped antisense to gene

1.1%

Reads mapped to intergenic regions

56.8%

Include introns

True

Cluster

Left: The figure is automated clustering each cell-barcode by UMAP algorithm. The cells clustered into the same group have similar expression profiles. Each dot represents a cell, and is colored according to different cluster.
Right: This plot shows that the total UMI counts for each cell-barcode. Two-dimensional horizontal and vertical coordinates of each dot are obtained using the uniform manifold approximation and projection (UMAP) algorithm. Each dot represents a cell and is colored according to UMI counts. Cells with greater UMI counts likely have higher RNA content than cells with fewer ones.

Marker

Table: The table shows the top 30 differentially expressed genes for each cluster. Here a differential expression test was performed between each cluster and the rest of the sample for each gene. The p-value is a measure of the statistical significance of the expression difference, the smaller the P value, the closer to the theoretical value. Avg_log2FC is log fold-chage of the average expression between the markers for every cluster compared to all remaining cells.

Select:

gene	cluster	p_val_adj	p_val	avg_log2FC	pct.1	pct.2
g4440	0	0.06030466557319772	0.005530901280382039	3.146	0.186	0.026
g9347	0	0.0028475292147519364	0.00016133190669378574	3.118	0.256	0.041
g441	0	3.888984165688679e-08	7.593874406374342e-10	2.71	0.449	0.107
g1656	0	0.016938740921897108	0.0012603826455198587	2.703	0.244	0.063
g5359	0	0.0034719750564382442	0.0002039014936991099	2.651	0.263	0.044
g11998	0	0.0015792368725549013	8.316691222330545e-05	2.603	0.301	0.085
g9772	0	0.03406769785550614	0.0028423345548085005	2.579	0.224	0.056
g14143	0	0.0007666696685537002	3.629205531615149e-05	2.57	0.308	0.078
g6766	0	0.001425553261684953	7.317558902436076e-05	2.495	0.314	0.096
g9701	0	0.00022026194181152815	9.383940716230785e-06	2.466	0.34	0.093
g1147	0	0.04073763354855019	0.0034892144710962363	2.428	0.218	0.048
g11071	0	0.013532413015427522	0.0009528740525656065	2.405	0.25	0.059
g3552	0	0.05877531071465945	0.0053732458611922395	2.34	0.212	0.052
g13220	0	0.0009701209161251374	4.7788500749951294e-05	2.325	0.321	0.089
g2462	0	4.479701256842328e-12	4.903814985300773e-14	2.302	0.603	0.211
g6535	0	8.074961958812383e-06	2.5084940996310656e-07	2.243	0.442	0.167
g11094	0	0.025123656179652284	0.001984620177505077	2.236	0.244	0.07
g6503	0	0.02789419027706925	0.0022571186511178816	2.236	0.244	0.07
g5610	0	0.017439183853922787	0.001307938789044209	2.216	0.25	0.067
g3054	0	0.00028167790628757887	1.2375493811747177e-05	2.204	0.359	0.13
g792	0	0.02942300531290139	0.0024123781746416013	2.204	0.25	0.078
g11349	0	1.1640562704470753e-08	2.152470914288231e-10	2.203	0.513	0.174
g13311	0	0.05706407636640477	0.0051999217517315595	2.145	0.231	0.078
g6151	0	0.04917029516036737	0.00430603768268306	2.14	0.231	0.07
g13588	0	5.856719429586373e-18	2.5124979801480002e-20	2.138	0.833	0.53
g11314	0	0.002234864536847354	0.0001243060748305629	2.136	0.308	0.093
g8697	0	0.015333306175656852	0.0011046331520036814	2.132	0.263	0.081
g1677	0	3.197511685517407e-21	7.568074995307473e-24	2.104	0.853	0.481
g6276	0	0.03516072532807547	0.0029543331340749807	2.076	0.237	0.067
g6892	0	0.06662311014392298	0.006258235938075605	2.075	0.224	0.067
g7912	0	0.000254656342382985	1.1037619573700385e-05	2.069	0.391	0.159
g4337	0	0.09743261949335474	0.009904502446999783	2.067	0.199	0.048
g12226	0	0.004851741394969727	0.00030000412767712217	2.063	0.295	0.085
g7913	0	0.00022624943508548574	9.672498038417956e-06	2.053	0.385	0.137
g7962	0	0.012474879167533322	0.0008728724624620208	2.039	0.276	0.089
g8950	0	0.00037442919313171187	1.6782846970252765e-05	2.037	0.365	0.141
g2564	0	0.04244401445091531	0.0036479249106481943	2.032	0.256	0.096
g10660	0	0.013563183242707461	0.0009570471015934111	2.021	0.263	0.078
g2604	0	1.086413026432364e-08	1.992828628367058e-10	2.009	0.545	0.23
g11353	0	9.210135088879758e-06	2.9020100206085627e-07	2.007	0.429	0.141
g12794	0	5.51684217241389e-08	1.1098972417874099e-09	1.994	0.558	0.274
g5743	0	0.011082488655028356	0.0007656097931802132	1.989	0.288	0.1
g2243	0	0.06183868102318801	0.00573562914223948	1.975	0.244	0.089
g1732	0	6.4399101157936e-17	2.9532132187810885e-19	1.968	0.846	0.489
g10256	0	0.0027322250137897736	0.0001535866132012003	1.959	0.333	0.137
g7156	0	1.426923474238454e-19	4.85491714607758e-22	1.953	0.878	0.611
g3627	0	9.481948384216592e-06	3.043761537536983e-07	1.953	0.449	0.174
g12724	0	0.009723315883172197	0.0006577841768986585	1.953	0.288	0.1
g1733	0	2.429687656959502e-15	1.6533377547357557e-17	1.948	0.814	0.515
g7447	0	0.0030585445405464516	0.00017735938755831496	1.948	0.327	0.119
g2137	1	0.0662734774620448	9.413157007571379e-05	0.252	1.0	0.989
g7652	1	0.0017356204695649215	5.134971803446513e-07	0.204	1.0	1.0
g6916	1	0.06669482561208255	0.00012825928002323567	0.19	1.0	1.0
g7686	1	0.008225847867520291	3.6505242015622592e-06	0.189	1.0	1.0
g10225	1	0.026273966137196	2.332008828745207e-05	0.188	1.0	0.996
g2086	1	0.0017356204695649215	4.32628874582849e-07	0.173	1.0	1.0
g7146	1	0.06646267487609336	0.00010903206526689922	0.173	1.0	1.0
g13899	1	0.0662734774620448	9.803768855332071e-05	0.172	1.0	0.996
g9132	1	0.03547400031530295	3.673343227915986e-05	0.164	1.0	1.0
g4240	1	0.06646267487609336	0.00011798107966170419	0.159	1.0	1.0
g11858	1	0.06156353365448564	7.285625284554514e-05	0.146	1.0	1.0
g2176	1	0.015580712262211579	9.219356368172532e-06	0.144	1.0	1.0
g10553	1	0.026273966137196	2.1012620318157597e-05	0.12	1.0	1.0
g1135	2	5.9953240362725444e-05	1.9688786036279656e-06	0.859	0.752	0.621
g13667	2	0.024190980860026662	0.0018536875866115106	0.528	0.761	0.751
g11946	2	0.019350667231369155	0.0014255373197073727	0.424	0.795	0.777
g8909	2	3.6399369528247955e-05	1.1469032114669844e-06	0.421	1.0	1.0
g7145	2	1.328964248158293e-05	3.55832143367827e-07	0.403	0.974	0.964
g12397	2	9.826479384403893e-14	4.506225753202968e-16	0.402	1.0	0.997
g11513	2	5.5398488372353155e-14	2.458512797589637e-16	0.387	1.0	1.0
g12297	2	0.07208089291017886	0.007080135043248337	0.378	0.812	0.816
g11742	2	0.09719336832195552	0.010337578672113316	0.376	0.761	0.786
g2991	2	0.0013568718270713178	6.342773629504977e-05	0.37	0.991	0.977
g13245	2	0.028074128422161778	0.0022310180498543875	0.358	0.855	0.861
g11705	2	0.01689550437368753	0.0011984698655748487	0.354	0.966	0.958
g12309	2	0.019489357297111907	0.0014386374691211304	0.348	0.923	0.922
g13468	2	1.0223533015421683e-14	3.3271853008768786e-17	0.343	1.0	1.0
g5564	2	0.0007902112398278844	3.49516509923872e-05	0.342	1.0	0.981
g7525	2	3.763979512328157e-17	7.795223842099733e-20	0.33	1.0	1.0
g10195	2	1.4654966710649e-11	1.0839472419119082e-13	0.329	1.0	1.0
g685	2	0.002313757049996343	0.00011568785249981715	0.317	0.966	0.968
g6947	2	0.03869430169756692	0.003297029257070791	0.309	0.991	0.971
g667	2	1.3680083748367479e-09	1.618944822292009e-11	0.307	1.0	0.997
g8352	2	2.005242785423931e-06	4.360513157652631e-08	0.304	1.0	1.0
g1593	2	7.340042870600207e-15	2.2801908325829045e-17	0.271	1.0	0.997
g14096	2	2.517507127843448e-11	2.0482676336004385e-13	0.27	1.0	1.0
g9369	2	1.0418064959204795e-12	6.472762252760375e-15	0.269	1.0	1.0
g5792	2	4.4503429426750643e-11	3.818341578034818e-13	0.266	1.0	1.0
g1899	2	1.7082023642979344e-11	1.2887325529466665e-13	0.254	1.0	1.0
g2705	2	0.0015126531479616322	7.182864800232011e-05	0.254	0.991	0.987
g9056	2	2.1052205881439083e-09	2.5536699441982322e-11	0.25	1.0	0.997
g9366	2	3.202325616504024e-09	4.168707903141333e-11	0.239	1.0	0.997
g13626	2	6.0026123085134e-10	6.304518844740406e-12	0.238	1.0	1.0
g2246	2	3.361707618901228e-10	3.331869977313347e-12	0.237	1.0	1.0
g6287	2	0.0255446958418851	0.0019763130067020573	0.234	0.991	0.984
g7208	2	1.7956500987760836e-06	3.878179207415802e-08	0.232	1.0	0.997
g11639	2	4.5416765355826236e-08	6.987194670127114e-10	0.23	1.0	1.0
g3477	2	4.682653568518168e-05	1.5031595035036132e-06	0.229	1.0	0.994
g1863	2	1.8625732032653426e-05	5.317701601038627e-07	0.227	1.0	1.0
g11253	2	0.005585774447713166	0.00033217179407998414	0.224	0.991	0.994
g13509	2	1.767284129778137e-05	4.918410856091491e-07	0.221	1.0	1.0
g1168	2	0.00026472695249595425	1.0103484281650324e-05	0.221	1.0	0.997
g10225	2	1.8047981791542744e-05	5.126053999964802e-07	0.217	1.0	0.997
g3654	2	0.024449833390210545	0.0018843732538904874	0.213	0.923	0.958
g12124	2	0.00013107268394630425	4.595299718235815e-06	0.211	0.991	1.0
g13395	2	1.850812848983689e-11	1.4237021915259147e-13	0.21	1.0	1.0
g13484	2	7.128408848349637e-07	1.4024828059622808e-08	0.204	1.0	0.997
g12926	2	3.295522029063911e-07	6.1912913859632645e-09	0.203	1.0	1.0
g13007	2	0.043087583957995376	0.003728733227134215	0.203	1.0	1.0
g11723	2	0.03142826149230136	0.0025709805629057178	0.201	0.991	0.984
g12778	2	1.2187042127315283e-06	2.5419718046619153e-08	0.199	1.0	0.997
g10024	2	2.2586466376669946e-07	4.009431901184014e-09	0.198	1.0	1.0
g6515	2	2.9212832282945878e-08	4.278210644987636e-10	0.196	1.0	1.0

Saturation

Left: The plot shows the Sequencing Saturation metric as a function of downsampled sequencing depth in mean reads per cell, up to the observed sequencing depth. Sequencing Saturation is a measure of the observed library complexity, and approaches 1.0 (100%) when all converted mRNA transcripts have been sequenced. The slope of the curve near the endpoint can be interpreted as an upper bound to the benefit to be gained from increasing the sequencing depth beyond this point.
Right: The plot shows the Median Genes per Cell as a function of downsampled sequencing depth in mean reads per cell, up to the observed sequencing depth. The slope of the curve near the endpoint can be interpreted as an upper bound to the benefit to be gained from increasing the sequencing depth beyond this point.