Ilhas cruise
Ilhas cruise
Initialize knitr
1 Aim
Flow cytometry analysis of Ilhas cruise
2 Directory structure
- ../data/fcm : flow cytometry files
3 Samples
- Samples analyzed by Luan on C6 during Ilhas 1
- Glutar samples analyzed by Domi Nov 2018 on FACS Canot
4 Initialize
4.1 Load the necessary libraries
4.2 Set up directories and files
5 Station map for Ilhas 1
5.1 Read data
5.2 Do the map
map <- leaflet(width = 1500, height = 500) %>% addTiles() %>% setView(lng = mean(stations$lon),
lat = mean(stations$lat), zoom = 7) %>% addCircleMarkers(data = stations,
lat = ~lat, lng = ~lon, radius = 6, label = ~as.character(Stations), labelOptions = labelOptions(textsize = "10px",
noHide = T)) %>% addProviderTiles(providers$Esri.OceanBasemap)
map6 NifH
6.1 Read the data
6.2 Summarize the data
### Data Frame Summary
**nifH**
**N:** 628
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| No | Variable | Stats / Values | Freqs (% of Valid) | Text Graph | Valid | Missing |
+====+========================================+=================================+====================+=====================+==========+=========+
| 1 | X__1\ | 1\. diazo\ | 1 ( 0.2%)\ | \ | 627\ | 1\ |
| | [character] | 2\. GammaA\ | 68 (10.8%)\ | IIIIIIIIIIIIIII \ | (99.84%) | (0.16%) |
| | | 3\. Het1\ | 70 (11.2%)\ | IIIIIIIIIIIIIIII \ | | |
| | | 4\. Het2\ | 70 (11.2%)\ | IIIIIIIIIIIIIIII \ | | |
| | | 5\. Het3\ | 70 (11.2%)\ | IIIIIIIIIIIIIIII \ | | |
| | | 6\. Tricho\ | 70 (11.2%)\ | IIIIIIIIIIIIIIII \ | | |
| | | 7\. UCYN-A1\ | 70 (11.2%)\ | IIIIIIIIIIIIIIII \ | | |
| | | 8\. UCYN-A2/A3\ | 70 (11.2%)\ | IIIIIIIIIIIIIIII \ | | |
| | | 9\. UCYN-B\ | 70 (11.2%)\ | IIIIIIIIIIIIIIII \ | | |
| | | 10\. UCYN-C | 68 (10.8%) | IIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 2 | X__2\ | 1\. 72579\ | 18 ( 2.9%)\ | \ | 627\ | 1\ |
| | [character] | 2\. 72580\ | 18 ( 2.9%)\ | \ | (99.84%) | (0.16%) |
| | | 3\. 72581\ | 18 ( 2.9%)\ | \ | | |
| | | 4\. 72582\ | 18 ( 2.9%)\ | \ | | |
| | | 5\. 72583\ | 18 ( 2.9%)\ | \ | | |
| | | 6\. 72584\ | 18 ( 2.9%)\ | \ | | |
| | | 7\. 72585\ | 18 ( 2.9%)\ | \ | | |
| | | 8\. 72586\ | 18 ( 2.9%)\ | \ | | |
| | | 9\. 72587\ | 18 ( 2.9%)\ | \ | | |
| | | 10\. 72588\ | 18 ( 2.9%)\ | \ | | |
| | | [ 26 others ] | 447 (71.3%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 3 | X__3\ | 1\. 0\ | 165 (26.3%)\ | IIIII \ | 627\ | 1\ |
| | [character] | 2\. 0.113192915916443\ | 2 ( 0.3%)\ | \ | (99.84%) | (0.16%) |
| | | 3\. 0.113916300237179\ | 2 ( 0.3%)\ | \ | | |
| | | 4\. 0.115510120987892\ | 2 ( 0.3%)\ | \ | | |
| | | 5\. 0.11607997864484799\ | 2 ( 0.3%)\ | \ | | |
| | | 6\. 0.11760590225458099\ | 2 ( 0.3%)\ | \ | | |
| | | 7\. 0.11844657361507401\ | 2 ( 0.3%)\ | \ | | |
| | | 8\. 0.118625722825527\ | 2 ( 0.3%)\ | \ | | |
| | | 9\. 0.12107343971729299\ | 2 ( 0.3%)\ | \ | | |
| | | 10\. 0.121241882443428\ | 2 ( 0.3%)\ | \ | | |
| | | [ 405 others ] | 444 (70.8%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 4 | X__4\ | 1\. 0\ | 165 (26.4%)\ | IIIII \ | 626\ | 2\ |
| | [character] | 2\. 1.1370435953140301\ | 2 ( 0.3%)\ | \ | (99.68%) | (0.32%) |
| | | 3\. 1.16623687744141\ | 2 ( 0.3%)\ | \ | | |
| | | 4\. 1.18509209156036\ | 2 ( 0.3%)\ | \ | | |
| | | 5\. 1.1897661685943599\ | 2 ( 0.3%)\ | \ | | |
| | | 6\. 1.19127213954926\ | 2 ( 0.3%)\ | \ | | |
| | | 7\. 1.1913324594497701\ | 2 ( 0.3%)\ | \ | | |
| | | 8\. 1.1944773197174099\ | 2 ( 0.3%)\ | \ | | |
| | | 9\. 1.2147034406662001\ | 2 ( 0.3%)\ | \ | | |
| | | 10\. 1.2245016098022501\ | 2 ( 0.3%)\ | \ | | |
| | | [ 404 others ] | 443 (70.8%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 5 | X__5\ | 1\. 1\ | 626 (99.8%)\ | IIIIIIIIIIIIIIII \ | 627\ | 1\ |
| | [character] | 2\. dilution factor | 1 ( 0.2%) | | (99.84%) | (0.16%) |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 6 | X__6\ | 1\. 10\ | 68 (10.8%)\ | I \ | 627\ | 1\ |
| | [character] | 2\. 100\ | 558 (89.0%)\ | IIIIIIIIIIIIIIII \ | (99.84%) | (0.16%) |
| | | 3\. extraction volume | 1 ( 0.2%) | | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 7 | X__7\ | 1\. # uL extract in qPCR rxn\ | 1 ( 0.2%)\ | \ | 627\ | 1\ |
| | [character] | 2\. 1.6 | 626 (99.8%) | IIIIIIIIIIIIIIII | (99.84%) | (0.16%) |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 8 | X__8\ | 1\. 50\ | 68 (10.8%)\ | I \ | 627\ | 1\ |
| | [character] | 2\. 500\ | 558 (89.0%)\ | IIIIIIIIIIIIIIII \ | (99.84%) | (0.16%) |
| | | 3\. LOQ (gc/DNA extract) | 1 ( 0.2%) | | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 9 | X__9\ | 1\. 6.25\ | 68 (10.8%)\ | I \ | 627\ | 1\ |
| | [character] | 2\. 62.5\ | 558 (89.0%)\ | IIIIIIIIIIIIIIII \ | (99.84%) | (0.16%) |
| | | 3\. LOD (gc/DNA extract) | 1 ( 0.2%) | | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 10 | X__10\ | 1\. 0\ | 166 (26.5%)\ | IIIII \ | 627\ | 1\ |
| | [character] | 2\. 0.71065224707126873\ | 2 ( 0.3%)\ | \ | (99.84%) | (0.16%) |
| | | 3\. 0.72889804840088124\ | 2 ( 0.3%)\ | \ | | |
| | | 4\. 0.74068255722522491\ | 2 ( 0.3%)\ | \ | | |
| | | 5\. 0.74360385537147489\ | 2 ( 0.3%)\ | \ | | |
| | | 6\. 0.74454508721828749\ | 2 ( 0.3%)\ | \ | | |
| | | 7\. 0.74458278715610626\ | 2 ( 0.3%)\ | \ | | |
| | | 8\. 0.74654832482338118\ | 2 ( 0.3%)\ | \ | | |
| | | 9\. 0.75918965041637498\ | 2 ( 0.3%)\ | \ | | |
| | | 10\. 0.76531350612640625\ | 2 ( 0.3%)\ | \ | | |
| | | [ 404 others ] | 443 (70.7%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 11 | X__11\ | 1\. 0\ | 166 (26.5%)\ | IIIII \ | 627\ | 1\ |
| | [character] | 2\. 141.49114489555373\ | 2 ( 0.3%)\ | \ | (99.84%) | (0.16%) |
| | | 3\. 1412.9903316497812\ | 2 ( 0.3%)\ | \ | | |
| | | 4\. 142.39537715911877\ | 2 ( 0.3%)\ | \ | | |
| | | 5\. 144.387647509575\ | 2 ( 0.3%)\ | \ | | |
| | | 6\. 145.09996771812433\ | 2 ( 0.3%)\ | \ | | |
| | | 7\. 147.00737595558189\ | 2 ( 0.3%)\ | \ | | |
| | | 8\. 148.05822074413314\ | 2 ( 0.3%)\ | \ | | |
| | | 9\. 148.28215539455439\ | 2 ( 0.3%)\ | \ | | |
| | | 10\. 151.34179592132563\ | 2 ( 0.3%)\ | \ | | |
| | | [ 404 others ] | 443 (70.7%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 12 | X__12\ | 1\. DNQ\ | 391 (62.4%)\ | IIIIIIIIIIIIIIII \ | 627\ | 1\ |
| | [character] | 2\. ok\ | 69 (11.0%)\ | II \ | (99.84%) | (0.16%) |
| | | 3\. UD\ | 166 (26.5%)\ | IIIIII \ | | |
| | | 4\. UD,DNQ determination | 1 ( 0.2%) | | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 13 | X__13\ | 1\. 0\ | 30 ( 9.6%)\ | I \ | 314\ | 314\ |
| | [character] | 2\. 112.83602938056001\ | 2 ( 0.6%)\ | \ | (50%) | (50%) |
| | | 3\. 113.10359090566656\ | 2 ( 0.6%)\ | \ | | |
| | | 4\. 113.86081203818313\ | 2 ( 0.6%)\ | \ | | |
| | | 5\. 152.31474488973626\ | 2 ( 0.6%)\ | \ | | |
| | | 6\. 152.82844752073314\ | 2 ( 0.6%)\ | \ | | |
| | | 7\. 153.06229889392873\ | 2 ( 0.6%)\ | \ | | |
| | | 8\. 154.41058576107031\ | 2 ( 0.6%)\ | \ | | |
| | | 9\. 155.39805591106406\ | 2 ( 0.6%)\ | \ | | |
| | | 10\. 162.56695240736002\ | 2 ( 0.6%)\ | \ | | |
| | | [ 244 others ] | 266 (84.7%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 14 | X__14\ | 1\. na\ | 30 ( 9.6%)\ | I \ | 314\ | 314\ |
| | [character] | 2\. 0.58007761276764269\ | 2 ( 0.6%)\ | \ | (50%) | (50%) |
| | | 3\. 0.83600381363755727\ | 2 ( 0.6%)\ | \ | | |
| | | 4\. 102.60117112343485\ | 2 ( 0.6%)\ | \ | | |
| | | 5\. 103.94991242263217\ | 2 ( 0.6%)\ | \ | | |
| | | 6\. 106.09102501054609\ | 2 ( 0.6%)\ | \ | | |
| | | 7\. 107.01481017291994\ | 2 ( 0.6%)\ | \ | | |
| | | 8\. 109.82340240070108\ | 2 ( 0.6%)\ | \ | | |
| | | 9\. 110.13787057415267\ | 2 ( 0.6%)\ | \ | | |
| | | 10\. 113.75811627384483\ | 2 ( 0.6%)\ | \ | | |
| | | [ 244 others ] | 266 (84.7%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 15 | X__15\ | 1\. Het2_Ilhaus_ddPCR.DataRed\ | 2 ( 0.3%)\ | \ | 627\ | 1\ |
| | [character] | 2\. Tricho_Ilhaus_ddPCR.DataR\ | 2 ( 0.3%)\ | \ | (99.84%) | (0.16%) |
| | | 3\. UCYN-A23_Ilhas_ddPCR_data\ | 2 ( 0.3%)\ | \ | | |
| | | 4\. UCYN-B_Ilhas_ddPCR_datare\ | 2 ( 0.3%)\ | \ | | |
| | | 5\. UCYN-C_Ilhas_ddPCR_datare\ | 2 ( 0.3%)\ | \ | | |
| | | 6\. filename\ | 1 ( 0.2%)\ | \ | | |
| | | 7\. GammaA_Ilhaus_ddPCR.DataR\ | 1 ( 0.2%)\ | \ | | |
| | | 8\. GammaA_Ilhaus_ddPCR.DataR\ | 1 ( 0.2%)\ | \ | | |
| | | 9\. GammaA_Ilhaus_ddPCR.DataR\ | 1 ( 0.2%)\ | \ | | |
| | | 10\. GammaA_Ilhaus_ddPCR.DataR\ | 1 ( 0.2%)\ | \ | | |
| | | [ 612 others ] | 612 (97.6%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 16 | X__16\ | 1\. 4000\ | 626 (99.8%)\ | IIIIIIIIIIIIIIII \ | 627\ | 1\ |
| | [character] | 2\. vol filtered (ml) | 1 ( 0.2%) | | (99.84%) | (0.16%) |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 17 | X__17\ | 1\. 0\ | 166 (26.5%)\ | IIIII \ | 627\ | 1\ |
| | [character] | 2\. 109.99712347984311\ | 2 ( 0.3%)\ | \ | (99.84%) | (0.16%) |
| | | 3\. 117.93009191751484\ | 2 ( 0.3%)\ | \ | | |
| | | 4\. 17.766306176781718\ | 2 ( 0.3%)\ | \ | | |
| | | 5\. 18.222451210022029\ | 2 ( 0.3%)\ | \ | | |
| | | 6\. 18.517063930630624\ | 2 ( 0.3%)\ | \ | | |
| | | 7\. 18.590096384286873\ | 2 ( 0.3%)\ | \ | | |
| | | 8\. 18.613627180457186\ | 2 ( 0.3%)\ | \ | | |
| | | 9\. 18.614569678902658\ | 2 ( 0.3%)\ | \ | | |
| | | 10\. 18.663708120584531\ | 2 ( 0.3%)\ | \ | | |
| | | [ 404 others ] | 443 (70.7%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 18 | X__18\ | 1\. 0\ | 30 ( 9.6%)\ | I \ | 314\ | 314\ |
| | [character] | 2\. 10.717010125517811\ | 2 ( 0.6%)\ | \ | (50%) | (50%) |
| | | 3\. 18.137495964765542\ | 2 ( 0.6%)\ | \ | | |
| | | 4\. 18.375921994447737\ | 2 ( 0.6%)\ | \ | | |
| | | 5\. 18.917724490165703\ | 2 ( 0.6%)\ | \ | | |
| | | 6\. 19.387897104024919\ | 2 ( 0.6%)\ | \ | | |
| | | 7\. 19.414218142628673\ | 2 ( 0.6%)\ | \ | | |
| | | 8\. 19.926333799958279\ | 2 ( 0.6%)\ | \ | | |
| | | 9\. 20.109783858060858\ | 2 ( 0.6%)\ | \ | | |
| | | 10\. 231.62235319614422\ | 2 ( 0.6%)\ | \ | | |
| | | [ 244 others ] | 266 (84.7%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 19 | X__19\ | 1\. 0\ | 30 ( 9.6%)\ | I \ | 314\ | 314\ |
| | [character] | 2\. 0.14501940319191067\ | 2 ( 0.6%)\ | \ | (50%) | (50%) |
| | | 3\. 0.20900095340938932\ | 2 ( 0.6%)\ | \ | | |
| | | 4\. 0.89641078426605736\ | 2 ( 0.6%)\ | \ | | |
| | | 5\. 1.0949830268470675\ | 2 ( 0.6%)\ | \ | | |
| | | 6\. 1.6073569958379976\ | 2 ( 0.6%)\ | \ | | |
| | | 7\. 12.452925180716395\ | 2 ( 0.6%)\ | \ | | |
| | | 8\. 12.562675574238797\ | 2 ( 0.6%)\ | \ | | |
| | | 9\. 12.885218820447585\ | 2 ( 0.6%)\ | \ | | |
| | | 10\. 13.09354147301374\ | 2 ( 0.6%)\ | \ | | |
| | | [ 244 others ] | 266 (84.7%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 20 | **please note that much of the data is | 1\. DNQ\ | 209 (66.6%)\ | IIIIIIIIIIIIIIII \ | 314\ | 314\ |
| | DNQ (detected but below quantitation)\ | 2\. ok\ | 29 ( 9.2%)\ | II \ | (50%) | (50%) |
| | [character] | 3\. UD\ | 75 (23.9%)\ | IIIII \ | | |
| | | 4\. UD,DNQ determination | 1 ( 0.3%) | | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 21 | X__20\ | 1\. #384\ | 72 (11.5%)\ | IIIIIIIIIIIIIIII \ | 627\ | 1\ |
| | [character] | 2\. #385\ | 72 (11.5%)\ | IIIIIIIIIIIIIIII \ | (99.84%) | (0.16%) |
| | | 3\. #380\ | 54 ( 8.6%)\ | IIIIIIIIIIII \ | | |
| | | 4\. #382\ | 54 ( 8.6%)\ | IIIIIIIIIIII \ | | |
| | | 5\. #383\ | 54 ( 8.6%)\ | IIIIIIIIIIII \ | | |
| | | 6\. #391\ | 54 ( 8.6%)\ | IIIIIIIIIIII \ | | |
| | | 7\. #394\ | 54 ( 8.6%)\ | IIIIIIIIIIII \ | | |
| | | 8\. #398\ | 54 ( 8.6%)\ | IIIIIIIIIIII \ | | |
| | | 9\. #403\ | 54 ( 8.6%)\ | IIIIIIIIIIII \ | | |
| | | 10\. #381\ | 52 ( 8.3%)\ | IIIIIIIIIII \ | | |
| | | [ 2 others ] | 53 ( 8.5%) | IIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 22 | X__21\ | 1\. 5\ | 178 (28.4%)\ | IIIIIIIIIIIIIII \ | 627\ | 1\ |
| | [character] | 2\. 170\ | 54 ( 8.6%)\ | IIII \ | (99.84%) | (0.16%) |
| | | 3\. 160\ | 52 ( 8.3%)\ | IIII \ | | |
| | | 4\. 130\ | 36 ( 5.7%)\ | III \ | | |
| | | 5\. 87\ | 36 ( 5.7%)\ | III \ | | |
| | | 6\. 120\ | 18 ( 2.9%)\ | I \ | | |
| | | 7\. 140\ | 18 ( 2.9%)\ | I \ | | |
| | | 8\. 150\ | 18 ( 2.9%)\ | I \ | | |
| | | 9\. 155\ | 18 ( 2.9%)\ | I \ | | |
| | | 10\. 159\ | 18 ( 2.9%)\ | I \ | | |
| | | [ 11 others ] | 181 (28.9%) | IIIIIIIIIIIIIIII | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 23 | X__22\ | 1\. 12.5\ | 68 (10.8%)\ | I \ | 627\ | 1\ |
| | [character] | 2\. 125\ | 558 (89.0%)\ | IIIIIIIIIIIIIIII \ | (99.84%) | (0.16%) |
| | | 3\. LOQ (gc/L) | 1 ( 0.2%) | | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+
| 24 | X__23\ | 1\. 1.5625\ | 68 (10.8%)\ | I \ | 627\ | 1\ |
| | [character] | 2\. 15.625\ | 558 (89.0%)\ | IIIIIIIIIIIIIIII \ | (99.84%) | (0.16%) |
| | | 3\. LOD (gc/L) | 1 ( 0.2%) | | | |
+----+----------------------------------------+---------------------------------+--------------------+---------------------+----------+---------+7 Flow cytometry
7.1 Read the data
fcm <- read_xlsx(path = fcm_file, sheet = "fcm_Roscoff")
fcm <- fcm %>% arrange(CTD, Depth)
fcm_long <- fcm %>% select(Cruise:Depth, Proc_mL, Syn_mL, Pico_mL, Nano_mL,
Crypto_mL, Corrected_Bact_mL) %>% gather(Proc_mL, Syn_mL, Pico_mL, Nano_mL,
Crypto_mL, Corrected_Bact_mL, key = "Population", value = cell_mL)7.2 Summarize the data
7.2.1 Data Frame Summary
fcm
N: 238
| No | Variable | Stats / Values | Freqs (% of Valid) | Text Graph | Valid | Missing |
|---|---|---|---|---|---|---|
| 1 | Cruise [character] |
1. Ilhas 1 2. Ilhas 2 |
96 (40.3%) 142 (59.7%) |
IIIIIIIIII IIIIIIIIIIIIIIII |
238 (100%) |
0 (0%) |
| 2 | CTD [numeric] |
mean (sd) : 364.5 (32.58) min < med < max : 316 < 382 < 404 IQR (CV) : 62 (0.09) |
36 distinct values | 238 (100%) |
0 (0%) |
|
| 3 | Depth [numeric] |
mean (sd) : 125.7 (150.48) min < med < max : 5 < 86 < 1250 IQR (CV) : 136 (1.2) |
71 distinct values | 238 (100%) |
0 (0%) |
|
| 4 | Description [character] |
1. No Sample 2. 318-10m 3. 318-30m 4. 318-50m 5. 318-5m_Rate96 6. 318-60m 7. 319-1000m 8. 319-140m 9. 319-200m 10. 319-50m [ 221 others ] |
8 ( 3.4%) 1 ( 0.4%) 1 ( 0.4%) 1 ( 0.4%) 1 ( 0.4%) 1 ( 0.4%) 1 ( 0.4%) 1 ( 0.4%) 1 ( 0.4%) 1 ( 0.4%) 221 (92.9%) |
IIIIIIIIIIIIIIII |
238 (100%) |
0 (0%) |
| 5 | Time [numeric] |
mean (sd) : 3 (0) min < med < max : 3 < 3 < 3 IQR (CV) : 0 (0) |
3 : 229 (100.0%) | IIIIIIIIIIIIIIII | 229 (96.22%) |
9 (3.78%) |
| 6 | Rate [numeric] |
mean (sd) : 99.86 (3.3) min < med < max : 96 < 98 < 106 IQR (CV) : 4 (0.03) |
96 : 22 ( 9.6%) 97 : 32 (14.0%) 98 : 62 (27.1%) 99 : 35 (15.3%) 102 : 39 (17.0%) 106 : 39 (17.0%) |
IIIII IIIIIIII IIIIIIIIIIIIIIII IIIIIIIII IIIIIIIIII IIIIIIIIII |
229 (96.22%) |
9 (3.78%) |
| 7 | Delivered_Volume [numeric] |
mean (sd) : 299.59 (9.89) min < med < max : 288 < 294 < 318 IQR (CV) : 12 (0.03) |
288 : 22 ( 9.6%) 291 : 32 (14.0%) 294 : 62 (27.1%) 297 : 35 (15.3%) 306 : 39 (17.0%) 318 : 39 (17.0%) |
IIIII IIIIIIII IIIIIIIIIIIIIIII IIIIIIIII IIIIIIIIII IIIIIIIIII |
229 (96.22%) |
9 (3.78%) |
| 8 | Beads [numeric] |
mean (sd) : 653.09 (210.35) min < med < max : 335 < 590 < 1520 IQR (CV) : 336 (0.32) |
187 distinct values | 229 (96.22%) |
9 (3.78%) |
|
| 9 | Beads_mL [numeric] |
mean (sd) : 2194.71 (746.33) min < med < max : 1078.62 < 1990.2 < 5277.78 IQR (CV) : 1187.78 (0.34) |
208 distinct values | 229 (96.22%) |
9 (3.78%) |
|
| 10 | Proc [numeric] |
mean (sd) : 10118.47 (8689) min < med < max : 1 < 10272 < 60074 IQR (CV) : 10635 (0.86) |
210 distinct values | 225 (94.54%) |
13 (5.46%) |
|
| 11 | Proc_mL [numeric] |
mean (sd) : 89117.14 (61899.62) min < med < max : 23.81 < 99495.1 < 313959.6 IQR (CV) : 95707.51 (0.69) |
208 distinct values | 210 (88.24%) |
28 (11.76%) |
|
| 12 | Accuri_C6_Proc_mL [numeric] |
mean (sd) : 8441.15 (26214.68) min < med < max : 22.58 < 709.12 < 210795.56 IQR (CV) : 1436.77 (3.11) |
85 distinct values | 87 (36.55%) |
151 (63.45%) |
|
| 13 | Proc_FSC [numeric] |
mean (sd) : 1.19 (0.33) min < med < max : 0.37 < 1.18 < 3.49 IQR (CV) : 0.4 (0.28) |
193 distinct values | 210 (88.24%) |
28 (11.76%) |
|
| 14 | Proc_SSC [numeric] |
mean (sd) : 0.07 (0.06) min < med < max : 0.02 < 0.04 < 0.27 IQR (CV) : 0.02 (0.97) |
73 distinct values | 210 (88.24%) |
28 (11.76%) |
|
| 15 | Proc_Chl [numeric] |
mean (sd) : 0.83 (1.33) min < med < max : 0.05 < 0.21 < 6.14 IQR (CV) : 0.34 (1.6) |
170 distinct values | 210 (88.24%) |
28 (11.76%) |
|
| 16 | Syn [numeric] |
mean (sd) : 1773.57 (2621.37) min < med < max : 3 < 487 < 10851 IQR (CV) : 2387.5 (1.48) |
164 distinct values | 183 (76.89%) |
55 (23.11%) |
|
| 17 | Syn_mL [numeric] |
mean (sd) : 6096.81 (8482.88) min < med < max : 30.61 < 1668.3 < 34122.64 IQR (CV) : 8263.61 (1.39) |
173 distinct values | 178 (74.79%) |
60 (25.21%) |
|
| 18 | Accuri_C6_Syn_mL [numeric] |
mean (sd) : 1135.72 (1639.43) min < med < max : 0 < 723.67 < 10057.78 IQR (CV) : 1582.22 (1.44) |
66 distinct values | 88 (36.97%) |
150 (63.03%) |
|
| 19 | Syn_FSC [character] |
1. - 2. 1.032 3. 1.6339999999999999 4. 1.5009999999999999 5. 1.5109999999999999 6. 1.5840000000000001 7. 1.587 8. 1.643 9. 1.651 10. 1.8819999999999999 [ 156 others ] |
3 ( 1.7%) 3 ( 1.7%) 3 ( 1.7%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 158 (87.3%) |
IIIIIIIIIIIIIIII |
181 (76.05%) |
57 (23.95%) |
| 20 | Syn_SSC [character] |
1. 0.112 2. 0.109 3. 0.113 4. 9.2999999999999999E-2 5. 0.108 6. 0.115 7. 0.11600000000000001 8. 0.11700000000000001 9. 9.1999999999999998E-2 10. 0.10100000000000001 [ 52 others ] |
9 ( 5.0%) 7 ( 3.9%) 6 ( 3.3%) 6 ( 3.3%) 5 ( 2.8%) 5 ( 2.8%) 5 ( 2.8%) 5 ( 2.8%) 5 ( 2.8%) 4 ( 2.2%) 124 (68.5%) |
I IIIIIIIIIIIIIIII |
181 (76.05%) |
57 (23.95%) |
| 21 | Syn_PE [character] |
1. - 2. 0.64500000000000002 3. 6.0999999999999999E-2 4. 0.09 5. 0.10199999999999999 6. 0.10299999999999999 7. 0.128 8. 0.38400000000000001 9. 0.45100000000000001 10. 0.47399999999999998 [ 148 others ] |
3 ( 1.7%) 3 ( 1.7%) 3 ( 1.7%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 158 (87.3%) |
IIIIIIIIIIIIIIII |
181 (76.05%) |
57 (23.95%) |
| 22 | Syn_Chl [character] |
1. 0 2. - 3. 0.318 4. 0.37 5. 0.371 6. 0.38600000000000001 7. 0.42799999999999999 8. 0.52800000000000002 9. 0.69699999999999995 10. 0.183 [ 164 others ] |
4 ( 2.2%) 3 ( 1.6%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 2 ( 1.1%) 1 ( 0.5%) 164 (88.2%) |
IIIIIIIIIIIIIIII |
186 (78.15%) |
52 (21.85%) |
| 23 | Pico [character] |
1. 4 2. 2 3. 3 4. 8 5. - 6. 1 7. 10 8. 103 9. 16 10. 20 [ 167 others ] |
4 ( 1.9%) 3 ( 1.4%) 3 ( 1.4%) 3 ( 1.4%) 2 ( 0.9%) 2 ( 0.9%) 2 ( 0.9%) 2 ( 0.9%) 2 ( 0.9%) 2 ( 0.9%) 187 (88.2%) |
IIIIIIIIIIIIIIII |
212 (89.08%) |
26 (10.92%) |
| 24 | Pico_mL [numeric] |
mean (sd) : 1264.86 (1612.93) min < med < max : 0 < 933.85 < 15872.05 IQR (CV) : 1348.3 (1.28) |
185 distinct values | 194 (81.51%) |
44 (18.49%) |
|
| 25 | Accuri_C6_Pico_mL [numeric] |
mean (sd) : 7302.42 (17018.15) min < med < max : 0 < 358.34 < 79769.65 IQR (CV) : 2089.76 (2.33) |
84 distinct values | 88 (36.97%) |
150 (63.03%) |
|
| 26 | Pico_FSC [character] |
1. - 2. 1.1890000000000001 3. 1.4371050255792959 4. 1.5069999999999999 5. 1.827 6. 1.9379999999999999 7. 10.019 8. 10.086 9. 10.119 10. 10.164 [ 188 others ] |
1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 188 (95.0%) |
IIIIIIIIIIIIIIII |
198 (83.19%) |
40 (16.81%) |
| 27 | Pico_SSC [character] |
1. 0.56000000000000005 2. 0.69199999999999995 3. 0.45400000000000001 4. 0.47799999999999998 5. 0.51800000000000002 6. 0.55400000000000005 7. 0.57599999999999996 8. 0.60199999999999998 9. 0.62 10. 0.67600000000000005 [ 166 others ] |
3 ( 1.5%) 3 ( 1.5%) 2 ( 1.0%) 2 ( 1.0%) 2 ( 1.0%) 2 ( 1.0%) 2 ( 1.0%) 2 ( 1.0%) 2 ( 1.0%) 2 ( 1.0%) 176 (88.9%) |
IIIIIIIIIIIIIIII |
198 (83.19%) |
40 (16.81%) |
| 28 | Pico_Chl [character] |
1. - 2. 1.083 3. 1.1359999999999999 4. 1.385 5. 1.7010000000000001 6. 10.276 7. 10.31 8. 10.436999999999999 9. 10.452 10. 10.74 [ 188 others ] |
1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 1 ( 0.5%) 188 (95.0%) |
IIIIIIIIIIIIIIII |
198 (83.19%) |
40 (16.81%) |
| 29 | Nano [numeric] |
mean (sd) : 213.18 (167.36) min < med < max : 1 < 201 < 1379 IQR (CV) : 157 (0.79) |
166 distinct values | 213 (89.5%) |
25 (10.5%) |
|
| 30 | Nano_mL [numeric] |
mean (sd) : 757.5 (562.21) min < med < max : 20.41 < 710.69 < 4788.19 IQR (CV) : 513.25 (0.74) |
187 distinct values | 201 (84.45%) |
37 (15.55%) |
|
| 31 | Accuri_C6_Nano_mL [character] |
1. 0 2. - 3. 1640 4. 18.066847335140018 5. 352.30352303523034 6. 456.18789521228547 7. 471.11111111111109 8. 551.11111111111109 9. 555.55555555555554 10. 586.66666666666663 [ 65 others ] |
3 ( 3.4%) 2 ( 2.3%) 2 ( 2.3%) 2 ( 2.3%) 2 ( 2.3%) 2 ( 2.3%) 2 ( 2.3%) 2 ( 2.3%) 2 ( 2.3%) 2 ( 2.3%) 67 (76.1%) |
IIIIIIIIIIIIIIII |
88 (36.97%) |
150 (63.03%) |
| 32 | Nano_FSC [numeric] |
mean (sd) : 84.17 (41.1) min < med < max : 7.62 < 83.09 < 278.46 IQR (CV) : 49.18 (0.49) |
203 distinct values | 203 (85.29%) |
35 (14.71%) |
|
| 33 | Nano_SSC [numeric] |
mean (sd) : 5.27 (3.41) min < med < max : 0.93 < 4.36 < 22.95 IQR (CV) : 2.94 (0.65) |
198 distinct values | 203 (85.29%) |
35 (14.71%) |
|
| 34 | Nano_Chl [numeric] |
mean (sd) : 90.56 (68.54) min < med < max : 14.91 < 67.31 < 531.86 IQR (CV) : 55.57 (0.76) |
202 distinct values | 203 (85.29%) |
35 (14.71%) |
|
| 35 | Crypto [numeric] |
mean (sd) : 40.39 (86.52) min < med < max : 1 < 17 < 673 IQR (CV) : 25 (2.14) |
76 distinct values | 226 (94.96%) |
12 (5.04%) |
|
| 36 | Crypto_mL [numeric] |
mean (sd) : 154.26 (308.1) min < med < max : 10.31 < 63.97 < 2265.99 IQR (CV) : 106.41 (2) |
131 distinct values | 197 (82.77%) |
41 (17.23%) |
|
| 37 | Accuri_C6_Crypto_mL [numeric] |
mean (sd) : 149.82 (327.34) min < med < max : 0 < 15.56 < 1824.75 IQR (CV) : 148.39 (2.18) |
47 distinct values | 88 (36.97%) |
150 (63.03%) |
|
| 38 | Crypto_FSC [numeric] |
mean (sd) : 402.88 (232.95) min < med < max : 30.42 < 366.21 < 1335.48 IQR (CV) : 297.33 (0.58) |
197 distinct values | 197 (82.77%) |
41 (17.23%) |
|
| 39 | Crypto_SSC [numeric] |
mean (sd) : 33.94 (12.58) min < med < max : 4.99 < 36.94 < 51.91 IQR (CV) : 21.12 (0.37) |
195 distinct values | 197 (82.77%) |
41 (17.23%) |
|
| 40 | Crypto_PE [numeric] |
mean (sd) : 10 (3.88) min < med < max : 3.32 < 9.01 < 24.87 IQR (CV) : 5.22 (0.39) |
197 distinct values | 197 (82.77%) |
41 (17.23%) |
|
| 41 | Crypto_Chl [numeric] |
mean (sd) : 61.31 (57.69) min < med < max : 7.93 < 43.86 < 462.08 IQR (CV) : 37.59 (0.94) |
196 distinct values | 197 (82.77%) |
41 (17.23%) |
|
| 42 | Total_Euks_mL [numeric] |
mean (sd) : 1842.07 (2051.7) min < med < max : 0 < 1571.9 < 17730.64 IQR (CV) : 1266.68 (1.11) |
185 distinct values | 203 (85.29%) |
35 (14.71%) |
|
| 43 | X__1 [logical] |
All NA’s | 0 (0%) |
238 (100%) |
||
| 44 | Time_SYBR [numeric] |
mean (sd) : 2 (0) min < med < max : 2 < 2 < 2 IQR (CV) : 0 (0) |
2 : 229 (100.0%) | IIIIIIIIIIIIIIII | 229 (96.22%) |
9 (3.78%) |
| 45 | Rate_SYBR [numeric] |
mean (sd) : 44.82 (2.06) min < med < max : 43 < 44 < 48 IQR (CV) : 5 (0.05) |
43 : 94 (41.0%) 44 : 39 (17.0%) 45 : 34 (14.8%) 48 : 62 (27.1%) |
IIIIIIIIIIIIIIII IIIIII IIIII IIIIIIIIII |
229 (96.22%) |
9 (3.78%) |
| 46 | Delivered_Volume_SYBR [numeric] |
mean (sd) : 89.64 (4.12) min < med < max : 86 < 88 < 96 IQR (CV) : 10 (0.05) |
86 : 94 (41.0%) 88 : 39 (17.0%) 90 : 34 (14.8%) 96 : 62 (27.1%) |
IIIIIIIIIIIIIIII IIIIII IIIII IIIIIIIIII |
229 (96.22%) |
9 (3.78%) |
| 47 | Beads_SYBR [numeric] |
mean (sd) : 172.6 (54.72) min < med < max : 88 < 162 < 390 IQR (CV) : 88 (0.32) |
133 distinct values | 229 (96.22%) |
9 (3.78%) |
|
| 48 | Beads_mL_SYBR [numeric] |
mean (sd) : 1915.6 (573.32) min < med < max : 1023.26 < 1822.22 < 4534.88 IQR (CV) : 858.9 (0.3) |
174 distinct values | 229 (96.22%) |
9 (3.78%) |
|
| 49 | Beads_Fnat_Sybr [numeric] |
mean (sd) : 1.14 (0.15) min < med < max : 0.77 < 1.13 < 1.6 IQR (CV) : 0.19 (0.13) |
228 distinct values | 229 (96.22%) |
9 (3.78%) |
|
| 50 | Bact [numeric] |
mean (sd) : 43776.44 (21700.54) min < med < max : 2501 < 48315 < 117119 IQR (CV) : 27371 (0.5) |
229 distinct values | 229 (96.22%) |
9 (3.78%) |
|
| 51 | Bact_mL [numeric] |
mean (sd) : 489936.03 (247365.44) min < med < max : 29081.4 < 543162.79 < 1361848.84 IQR (CV) : 295296.51 (0.5) |
229 distinct values | 229 (96.22%) |
9 (3.78%) |
|
| 52 | Corrected_Bact_mL [numeric] |
mean (sd) : 404858.34 (200997.74) min < med < max : 29081.4 < 419682.26 < 1177317.59 IQR (CV) : 220259.55 (0.5) |
228 distinct values | 228 (95.8%) |
10 (4.2%) |
|
| 53 | Bact_FSC [numeric] |
mean (sd) : 1.29 (0.48) min < med < max : 0.6 < 1.23 < 5.05 IQR (CV) : 0.46 (0.37) |
212 distinct values | 229 (96.22%) |
9 (3.78%) |
|
| 54 | Bact_SSC [numeric] |
mean (sd) : 0.04 (0.02) min < med < max : 0.02 < 0.03 < 0.13 IQR (CV) : 0.01 (0.47) |
43 distinct values | 229 (96.22%) |
9 (3.78%) |
|
| 55 | Bact_DNA [numeric] |
mean (sd) : 0.23 (0.04) min < med < max : 0.17 < 0.22 < 0.35 IQR (CV) : 0.06 (0.17) |
113 distinct values | 229 (96.22%) |
9 (3.78%) |
7.3 Draw vertical profiles
for (one_cruise in c("Ilhas 1", "Ilhas 2")) {
df <- filter(fcm_long, Cruise == one_cruise)
p <- ggplot(df) + geom_point(aes(x = cell_mL, y = Depth, color = Population)) +
geom_path(aes(x = cell_mL, y = Depth, color = Population)) + ylim(300,
0) + scale_x_log10() + ggtitle(str_c("Flow cytometry - ", one_cruise)) +
ylab("Cell per mL") + facet_wrap(vars(CTD), ncol = 3) + scale_color_viridis_d()
print(p)
}
